International Journal o f Molecular Sciences Article In Silico Discovery of Potential Inhibitors Targeting the RNA Binding Loop of ADAR2 and 5-HT2CR from Traditional Chinese Natural Compounds Emmanuel Broni 1 , Carolyn Ashley 1, Miriam Velazquez 1,2, Sufia Khan 1,3, Andrew Striegel 1,4, Patrick O. Sakyi 5,6, Saqib Peracha 1, Kristeen Bebla 1,2, Monsheel Sodhi 2, Samuel K. Kwofie 7,8 , Adesanya Ademokunwa 1,9 and Whelton A. Miller III 1,2,* 1 Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA 2 Department of Molecular Pharmacology & Neuroscience, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA 3 Department of Biology, Loyola University Chicago, Chicago, IL 60660, USA 4 Department of Chemical and Biochemistry, College of Science, University of Notre Dame, Notre Dame, IN 46556, USA 5 Department of Chemistry, School of Physical and Mathematical Sciences, College of Basic and Applied Sciences, University of Ghana, Legon, Accra P.O. Box LG 56, Ghana 6 Department of Chemical Sciences, School of Sciences, University of Energy and Natural Resources, Sunyani P.O. Box 214, Ghana 7 Department of Biomedical Engineering, School of Engineering Sciences, College of Basic & Applied Sciences, University of Ghana, Legon, Accra P.O. Box LG 77, Ghana 8 Department of Biochemistry, Cell and Molecular Biology, West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana, Accra P.O. Box LG 54, Ghana 9 Department of Cognitive and Behavioral Neuroscience, Loyola University Chicago, Chicago, IL 60660, USA * Correspondence: wmiller6@luc.edu Citation: Broni, E.; Ashley, C.; Velazquez, M.; Khan, S.; Striegel, A.; Abstract: Adenosine deaminase acting on RNA 2 (ADAR2) is an important enzyme involved in Sakyi, P.O.; Peracha, S.; Bebla, K.; RNA editing processes, particularly in the conversion of adenosine to inosine in RNA molecules. Sodhi, M.; Kwofie, S.K.; et al. In Silico Dysregulation of ADAR2 activity has been implicated in various diseases, including neurological Discovery of Potential Inhibitors disorders (including schizophrenia), inflammatory disorders, viral infections, and cancers. Therefore, Targeting the RNA Binding Loop of targeting ADAR2 with small molecules presents a promising therapeutic strategy for modulating ADAR2 and 5-HT2CR from RNA editing and potentially treating associated pathologies. However, there are limited compounds Traditional Chinese Natural Compounds. Int. J. Mol. Sci. 2023, 24, that effectively inhibit ADAR2 reactions. This study therefore employed computational approaches 12612. https://doi.org/10.3390/ to virtually screen natural compounds from the traditional Chinese medicine (TCM) library. The ijms241612612 shortlisted compounds demonstrated a stronger binding affinity to the ADAR2 (<−9.5 kcal/mol) than the known inhibitor, 8-azanebularine (−6.8 kcal/mol). The topmost compounds were also Academic Editors: Bing Niu and observed to possess high binding affinity towards 5-HT2CR with binding energies ranging fromGuoping Zhou −7.8 to −12.9 kcal/mol. Further subjecting the top ADAR2–ligand complexes to molecular dynamics Received: 1 July 2023 simulations and molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations Revised: 2 August 2023 revealed that five potential hit compounds comprising ZINC000014637370, ZINC000085593577, Accepted: 6 August 2023 ZINC000042890265, ZINC000039183320, and ZINC000101100339 had favorable binding free energies Published: 9 August 2023 of−174.911,−137.369,−117.236,−67.023, and−64.913 kJ/mol, respectively, with the human ADAR2 protein. Residues Lys350, Cys377, Glu396, Cys451, Arg455, Ser486, Gln488, and Arg510 were also predicted to be crucial in ligand recognition and binding. This finding will provide valuable insights Copyright: © 2023 by the authors. into the molecular interactions between ADAR2 and small molecules, aiding in the design of future Licensee MDPI, Basel, Switzerland. ADAR2 inhibitors with potential therapeutic applications. The potential lead compounds were also This article is an open access article profiled to have insignificant toxicities. A structural similarity search via DrugBank revealed that distributed under the terms and ZINC000039183320 and ZINC000014637370 were similar to naringin and naringenin, which are conditions of the Creative Commons known adenosine deaminase (ADA) inhibitors. These potential novel ADAR2 inhibitors identified Attribution (CC BY) license (https:// herein may be beneficial in treating several neurological disorders, cancers, viral infections, and creativecommons.org/licenses/by/ inflammatory disorders caused by ADAR2 after experimental validation. 4.0/). Int. J. Mol. Sci. 2023, 24, 12612. https://doi.org/10.3390/ijms241612612 https://www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2023, 24, 12612 2 of 31 Keywords: adenosine deaminases acting on RNA (ADAR); anti-ADAR2; natural products; cancer; depression; anxiety disorders; autism spectrum disorder (ASD); molecular docking; molecular dynamics simulation 1. Introduction ADAR2 is a part of a family of proteins called ADARs for adenosine deaminase acting on double-stranded RNA [1]. ADAR family proteins catalyze the hydrolytic deamination of adenosine to inosine (A-to-I), resulting in a high diversity of outcomes, although ADAR3 has no known catalytic activity [2,3]. Some of the impacts of A-to-I editing come from the direct changes in RNA sequences in coding regions. This RNA recording emerges because inosine is structurally similar to guanosine and can be interpreted by the cellular translational machinery as such. A popular and well-understood example of such editing includes glutamate receptor GRIA2 transcripts. In ADAR2 null mice, the mice suffer from epileptic-like seizures and die briefly after conception [4]. This phenotype is a repercussion of increased calcium permeability through the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor associated with a lack of RNA editing of the Q/R site in the GluA2 subunit by ADAR2 [5]. However, the majority of ADAR editing occurs in non-coding regions, including inverted Alu repeats [6,7]. The functionality and biological relevance of ADARs are far from being fully established. ADARs have been clearly impli- cated in a wide variety of complications such as viral infections [8], metabolic disorders [9], autoimmune and inflammatory diseases [10–12], several cancers, and neurological dis- orders [13,14]. These issues can be related to the dysregulation of ADAR RNA-editing activities that may generate codon alterations or splice site modulations, antagonize RNAi pathways, or interrupt miRNA processing [15,16]. The idea of ADAR proteins having RNA-editing independent activities through protein–protein interactions, sequestration, and other mechanisms also increases the potential roles of ADARs [17–19]. Some specific instances of ADAR2’s crucial roles include neurological disorders such as schizophrenia and major depressive disorder, roles in both tumor suppression and tumor aggravation, and its role in the innate immune system and viral infections. ADAR2 is known to edit multiple sites in the 5-hydroxytryptamine 2C receptor (5-HT2CR). Results from mice studies support that the editing of 5-HT2CR pre-mRNAs led to changes in the regulation of lipolysis and metabolism [20]. Variations in RNA editing efficiency at these sites led to symptoms that encompassed excessive anxiety and anti-depressive behaviors [20]. Dysregulated editing of 5-HT2CR pre-mRNA has been reported with psychiatric disorders, suggesting a role of ADAR2 in schizophrenia, autism, depression, and bipolar disorder [21–24]. ADAR2 plays conflicting roles in cancer. In some cancers ADAR2 activity may lead to proto-oncogenic effects, and in others ADAR2 acts as a tumor suppressor. ADAR2 plays an impactful role in GBM as it regulates a multitude of miRNAs in glioblastoma cells [25]. The reduction of ADAR2 editing on some miRNAs is involved in increasing tumor growth and migration in glioblastoma multiforme (GBM), which lead to a downregulation of their inhibition and thereby promoted their oncogenic activities [25,26]. In contrast, ADAR2 editing of certain transcripts in hepatocellular carcinoma (HCC) results in the regulation and suppression of oncogenic miRNAs. Thereby, in HCC, the upregulation of ADAR2 editing results in inhibited tumorigenicity [27,28]. ADAR2 plays specific roles in monitoring the self-compared to non-self RNA, which is key for regulating the innate immune response. ADAR2’s role in the innate immune response makes it a target of some viruses that use it to escape immune detection, but ADAR2 also has anti-viral abilities [29]. Borna disease virus (BoDV) is an RNA virus that utilizes ADAR2 editing of its own genomic RNA to avoid immune detection. Upon knockdown of ADAR2, editing of the virus was also reduced and resulted in an intense innate immune response [30]. With a wide variety of significant roles, ADARs make valuable drug targets for future therapies. Currently, there are no full models of ADAR proteins, but structures of Int. J. Mol. Sci. 2023, 24, 12612 3 of 31 valuable domains and motifs have been identified. Common domains between ADAR family proteins include multiple double-stranded RNA binding domains (dsRBD) and a singular catalytic deaminase domain (CDD) [31]. These domains are both involved in substrate selectivity. In ADAR editing there are two types of editing and certain preferences for editing sites that are impacted by RNA substrate structure and length. One type of editing is hypermutation, which is nonselective and rapidly deaminates adenosines that are commonly occurring in duplex RNA that is long and complimentary, and the other is a highly selective and accurate editing of duplex RNA that is short or broken up by bulges, mismatches, and loops [32,33]. ADARs also have nearest neighbor preferences that impact which adenosines will be edited. ADAR2 has a 5′ nearest neighbor preference for uracil followed by A > C > G and a 3′ nearest neighbor preference for G followed by C > U∼A [34]. A structural study of ADAR2 depicting the CDD of ADAR2 in complex with dsRNA suggests that the 3′ preference is impacted by the CDD [35]. However, another study of ADAR2’s dsRBD complexed to duplex RNA supports that the second dsRBD of ADAR2 impacts the 3′ nearest neighbor preference of ADAR2 [36]. The dsRBDs increase binding to duplex RNA in a sequence-independent manner [37]. Site specificity is predominantly impacted by the CDD. In a domain-swapping study, the CDD of ADAR1 and ADAR2 were exchanged and the proceeding substrate editing corresponded to the CDD [38]. The ability for the ADAR2 CDD to effect substrate specificity has been further explained by structures depicting the base-flipping mechanism of ADAR showing an RNA binding loop near the ADAR2 active site, whose steric clashes complimented the evidence for nearest neighbor preferences [35]. This RNA binding loop covers the amino acids of 454 to 479 with interactions made primarily to the sugar phosphate backbone of the RNA [35]. Conservation of this loop across ADAR2 sequences of other species support its significance, although this region deviates between ADAR family members potentially influencing substrate specificity [39]. Interestingly, experiments using high-throughput mutagenesis determined that of the 18 conserved residues within the ADAR2 5′ RNA binding loop only six required the original wild type amino acid to maintain RNA editing efficiency [39]. The six residues, Phe457, Asp469, His471, Pro471, Arg474, and Arg477, are involved in stabilizing the ordered conformation of the 5′ binding loop upon substrate binding and may provide additional dsRNA binding contacts [39]. The other 12 conserved residues in the RNA binding loop are not required for efficient editing, indicating that they play other key functional roles. It has been suggested that their conservation may correlate to their importance in protein–protein interactions for ADAR2 regulation or editing independent activities [39]. Overall, the six key residues of the 5′ binding loop of ADAR2 have been confirmed as necessary for efficient ADAR2 editing activity, and while ADAR1 and ADAR2 share significant sequence similarity in the majority of their CDDs, the 5′ binding loop represents an area of distinction between the two. Thus, indicating that targeting the 5′ binding loop of ADAR2 should affect the editing of ADAR2 substrates without affecting subsequential ADAR1 substrates. This is incredibly important, as ADAR1 and ADAR2 can edit the same substrate at different editing sites such as in the 5-HT2CR. Within the five editing sites of the 5-HT2CR, ADAR1 edits sites A and B, ADAR2 edits site D, and sites C and E could be edited by either enzyme [40]. In a knockout study of ADAR2, it was shown that certain editing sites that relied on ADAR2, including the D site of 5-HT2CR, as well as the GluA2 Q/R site and the CYFIP2 K/E site, had reduced editing [40]. These ADAR2 knock out mice, in turn, did not develop enhanced ethanol intake or preference, even after chronic exposure to ethanol vapor, which did appear in the wild type mice. Therefore, ADAR2-dependent sites of the 5-HT2CR may contribute to alcohol intake. Additionally, as mentioned previously, altered RNA editing of the 5-HT2CR has been reported in several other complications, including major depression, depressed suicide victims, bipolar disorder, and schizophrenic patients, as well as in emotional influences such as anxiety and stress [21,41–46]. Thereby, the modulation of RNA editing of the 5-HT2CR may be therapeutic for these variable com- Int. J. Mol. Sci. 2023, 24, 12612 4 of 31 plications. However, the dearth of research on the screening of small molecule inhibitors that specifically target ADAR2 is surprising. Pharmacoinformatic-based approaches are beneficial for analyzing and interpreting data related to drugs and drug action. These approaches aid in studying the properties of drugs and their interactions with biological systems, as well as in analyzing and inter- preting large datasets generated by various sources, such as clinical trials, electronic health records, and drug databases. These, in turn, enable the identification of new, improved, safer, and more effective drug candidates, in addition to speeding up the process of repur- posing therapeutic agents for existing and emerging diseases. Using molecular docking, this study virtually screened TCM compounds that target the RNA binding loop of the ADAR2 protein. The topmost compounds were subjected to molecular dynamics simula- tions and molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations to corroborate their affinity to the ADAR2 protein. The topmost compounds were further docked against the 5-HT2CR in order to investigate their multi-target inhibitory potential against both ADAR2 and 5-HT2CR. The biological activity of the shortlisted compounds were predicted using a Bayesian-based algorithm, prediction of activity spectra of sub- stances (PASS) [47–49]. Furthermore, the pharmacokinetic and pharmacodynamics profiles of the shortlisted compounds were evaluated to determine their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. 2. Results and Discussion 2.1. Selecting Binding Site Previously, three potential binding sites of the human ADAR2 (hADAR2) protein were predicted [50] using Computed Atlas of Surface Topography of proteins (CASTp): 1. IHP binding site [35,51] comprising of residues Ala389, Leu390, Asn391, Asp392, Ile397, Arg400, Arg401, Leu404, Tyr408, Gln500, Leu512, Thr513, Met514, Lys519, Arg522, Trp523, Val526, Gly527, Ile528, Gln529, Gly530, Ser531, Leu532, Leu533, Lys629, Leu632, Tyr658, His659, Lys662, Leu663, Tyr668, Gln669, Lys672, Phe676, Trp687, Val688, Glu689, Lys690, Pro691, Thr692, Gln694, and Asp695. 2. RNA binding loop [35,39] comprising of residues Lys350, Val351, Gly374, Thr375, Lys376, Cys377, Ile378, Asn379, His394, Ala395, Glu396, Ile446, Thr448, Ser449, Pro450, Cys451, Gly452, Arg455, Ile456, Pro459, Lys483, Ile484, Glu485, Ser486, Gly487, Gln488, Gly489, Thr490, Leu511, Thr513, Cys516, Arg590, Lys594, and Ala595. 3. A third plausible binding site lined by residues Ser458, His460, Glu461, Pro462, Ile463, Glu466, Pro467, Ala468, Asp469, Arg470, His471, His552, Asp554, and His555. Recently, the IHP binding site [35,51] was virtually screened for potential anti-ADAR2 compounds, and nine compounds were shortlisted [50]. ADAR2 was also experimen- tally targeted using 8-azanebularine, nebularine, and coformycin. However, only 8- azanebularine was reported to inhibit ADAR2 reaction with an IC50 of 15 ± 3 mM [52]. Not much is reported about screening small molecule inhibitors against the ADAR2 RNA binding loop in literature. To the best of the authors’ knowledge, there is a dearth of studies which screen for small molecule inhibitors targeting the ADAR2 RNA binding site. Therefore, the RNA binding loop was selected for virtual screening in this study. 2.2. Molecular Docking of ADAR2 Molecular docking is the most popular and widely used computer-aided drug design technique for predicting the binding affinity and interactive modes of bioactive com- pounds and for performing receptor-based virtual screening studies [53,54]. Herein, AutoDock Vina embedded in PyRx was employed to virtually screen 8-azanebularine (known ADAR2 inhibitor) and natural compounds from the TCM library. The known inhibitor, 8-azanebularine, had a binding energy of −6.8 kcal/mol (Table 1). A previous study which shortlisted the top 10% of compounds after virtually screening against the ADAR2 IHP binding site reported the top compounds as having binding energies below Int. J. Mol. Sci. 2023, 24, 12612 5 of 31 −8.8 kcal/mol [50]. Herein, TCM compounds with binding energies below −9.5 kcal/mol were shortlisted. Table 1. Binding energies of some TCM compounds and 8-Azanebularine after docking against the RNA binding loop of ADAR2. The interacting residues, as well as the hydrogen bond lengths, are also provided. The common names and/or IUPAC names of the compounds have been provided. Binding Energy Interacting ResiduesCompound (kcal/mol) Hydrogen Bonds (Å) Hydrophobic Contacts 8-Azanebularine −6.8 Thr375 (2.94, 3.14), Ile484 (2.82, Lys376, Cys377, Ile378, His394,3.2), and Gly487 (3.21) Lys483, and Glu485 ZINC000095913861 ((2Z)-2,11,28-trimethyl-19-methylidene-13,30- Thr375, Lys376, Cys377, Ile378, dioxaheptacyclo[21.10.1.06,18.07,15.010,14.024,32.027,31]tetratriaconta- −12.0 Asn379 (2.92) and Gly489 (2.99) His394, Arg455, Ile456, Lys483, 1(33),2,6(18),7(15),10(14),11,16,23(34),24(32),27(31),28- Ile484, Glu485, Thr490, and undecaene-8,9,25,26-tetrone) Leu511 Ile378 (3.01), Arg455 (2.99), ZINC000085996580 (Lespedezol B2 or Lys483 (3.17), Ile484 (2.55, 2.88), Val351, Thr375, Lys376, Cys377, 8-[[2-(2,4-dihydroxyphenyl)-6-hydroxy-1-benzofuran-3-yl]methyl]-6H- −11.0 Gly487 (3.05), Leu511 (2.85), His394, Thr448, Cys451, [1]benzofuro[3,2-c]chromene-3,9-diol) Leu512 (3.11), Thr513 (2.97), Glu485, and Leu512 and Arg590 (2.8) ZINC000070454467 ((1S,2S,4R,6S,11R,12S,15S,18S,19S,20R,21S,23R,26S)- 15-hydroxy-11,18,21-trimethyl-5,17,24,28,29- Thr375, Lys376, Cys377, pentaoxanonacyclo[17.9.1.11,20.02,12.04,6.06,11.015,19.018,23.021,26]triacont- −10.9 His394 (3.15) and Gly487 (2.91) Lys483, Ile484, Ser486, Gln488, 8-ene-10,16,25,30-tetrone) Gly489, Arg590, and Ala595 Cys377 (3.08), Cys451 (3.15), Lys350, Val351, Thr375, Lys376, ZINC000042890265 (Disulfuretin) −10.6 Gly452 (3.19), Ser449 (2.7), and His394, Glu396, Thr448, Pro450,Arg455, Ile456, Lys483, Ile484, Arg590 (3.05) Gly487, Gly489, and Thr490 Val351, Thr375, Lys376, His394, Cys377 (3.01), Ile378 (3.19), Thr448, Pro450, Cys451, ZINC000039183320 (Neocalyxin A) −10.5 Asn379 (3.11), Glu396 (2.77), Arg455, Lys483, Ile484, Glu485, and Ser449 (3.14) Gln488, Gly489, Arg590, and Ala595 Val351, Thr375, Lys376, Cys377, ZINC000085593577 Lys483 (2.97), Ile484 (2.97), Ile378, His394, Glu396, Thr448, ((2S,3R)-2-[2-(4-aminophenyl)ethyl]-3,5-dihydroxy-8-[(1R)-1-hydroxy-2- −10.5 Gly487 (2.78), and Leu511 Ser449, Cys451, Arg455, phenylethyl]-2-methyl-3,4-dihydropyrano[3,2-g]chromen-6-one) (2.89) Glu485, Ser486, Gly489, Thr490, and Thr513 ZINC000070454124 ((3S,10S,11S,12S)-10,11-dihydroxy-7,18-bis(2- Lys376 (3.08), Cys377 (3.13), Val351, Thr375, His394, Glu396,Thr448, Ser449, Cys451, phenylethyl)-2,8,13,17-tetraoxapentacyclo[12.8.0.03,12.04,9.016,21]docosa- −10.2 Asn379 (3.07), Ile484 (2.94), Ser486 (2.85), and Gly487 (3.27) Arg455, Glu485, Ala595,1(14),4(9),6,15,18,21-hexaene-5,20-dione) Asn597, and Thr615 ZINC000103585067 ((1R,2S,5S,8S,9R,17R,18S,21S,24R,26S,27S)-5-hydroxy- Thr375 (2.9), Lys376 (3.29), 2,9,26-trimethyl-3,19,23,28- −10.2 Cys377 (3.0), Asn379 (3.33), Lys483, Ser486, Gln488, andtetraoxaoctacyclo[16.9.1.118,27.01,5.02,24.08,17.09,14.021,26]nonacosa- His394 (3.13), Ile484 (3.05), and Thr615 11,14-diene-4,10,22,29-tetrone) Gly487 (2.99) ZINC000014637370 ((8R)-8-(2,2-dimethyl-3,4-dihydrochromen-6-yl)-5- Cys377 (3.34), Asn379 (2.97), Thr375, Lys376, His394, hydroxy-2,2-dimethyl-3,4,7,8-tetrahydropyrano[3,2-g]chromen-6-one) −10.2 Ser486 (3.31), and Gly489 (3.19) Cys451, Lys483, Ile484, Glu485,Gly487, and Thr490 Val351, Thr375, Cys377, Ile378, ZINC000013384051 (Cassigarol E) −10.1 Asn379 (3.03), Glu396 (3.13), His394, Pro450, Arg455, Lys483,Ser449 (2.79), and Cys451 (2.97) Ile484, Glu485, Gln488, Gly489, and Leu511 Thr375, Lys376, Cys377, Ile378, ZINC000059586224 ((5S)-9-methoxy-14-methyl-5,19-diphenyl-4,12,18- Asn379, His394, Arg455, trioxapentacyclo[11.7.1.02,11.03,8.017,21]henicosa-1(21),2,6,8,10,13,16,19- −10.1 Gly489 (3.07) Lys483, Ile484, Glu485, Gly487, octaen-15-one) Gln488, Thr490, Leu511, Asn597, and Thr615 ZINC000070454074 ((1S,2R,7R,10R,13R,14S,16R,19R,20R)-19-[(2S)-2- Val351, Thr375, Lys376, Cys377, hydroxy-5-oxo-2H-furan-3-yl]-9,9,13,20-tetramethyl-4,15,18- −10.1 His394 (2.97), Arg455 (2.97, Cys451, Ile484, Gly487, and trioxahexacyclo[11.9.0.02,7.02,10.014,16.014,20]docosane-5,12,17-trione) 2.96, 3.2) and Arg590 (2.81) Gln488 ZINC000085530502 ((1S,2R,4S,7S,8S,11R,12R,17S,19R,20S,24S)-19- cyclohexyl-7-(furan-3-yl)-24-hydroxy-8,19-dimethyl-3,6,14,18- Thr375, Lys376, His394, Cys451, tetraoxaheptacyclo[18.3.2.01,11.02,4.02,8.012,17.012,20]pentacos-21-ene- −10.1 Cys377 (3.22) and Arg455 (3.31) Lys483, Ile484, Ser486, Gly487, 5,15,25-trione) Gln488, Gly489, and Thr490 ZINC000085532258 ((5E)-5-[(1S,2R,3S,11S,13S)-13-benzyl-11-[(S)-hydroxy- Val351, Thr375, Cys377, His394, [(1S,5R)-5-methylcyclohex-2-en-1-yl]methyl]-3-methyl-5-oxa-10- Glu396, Thr448, Ser449, Cys451, azatricyclo[8.4.0.02,6]tetradec-6-en-4-ylidene]-3-(hydroxymethyl)-4- −10.1 Asn379 (2.92) and Arg455 (3.32) Pro459, Lys483, Ile484, Glu485, methoxyfuran-2-one) Ser486, Gly487, Gln488, andGly489 Int. J. Mol. Sci. 2023, 24, 12612 6 of 31 Table 1. Cont. Binding Energy Interacting ResiduesCompound (kcal/mol) Hydrogen Bonds (Å) Hydrophobic Contacts ZINC000085532442 (5-[(1S,2R,3S,4E,11S,13S)-13-benzyl-11-[(1S)-2- Val351, Thr375, Lys376, Asn379, cyclopentyl-1-hydroxyethyl]-3-methyl-5-oxa-10- Cys377 (3.04), Ile378 (2.91), and His394, Glu396, Ser449, Cys451, 2,6 −10.1azatricyclo[8.4.0.0 ]tetradec-6-en-4-ylidene]-3- Gly489 (3.05) Arg455, Ile456 Lys483, Ile484, (hydroxymethyl)-4-methoxy-2,5-dihydrofuran-2-one) Glu485, Ser486, Gln488, andThr490 ZINC000095911347 ((1R,2S,4R,6S,11R,12S,15R,18S,19R,20S,21S,23R,26S)- 15-hydroxy-11,18,21-trimethyl-5,17,24,28,29- Lys376 (3.19), Cys377 (3.28), Thr375, Hs394, Ile484, Ser486, pentaoxanonacyclo[17.9.1.11,20.02,12.04,6.06,11.015,19.018,23.021,26]triacont- −10.1 Gly487, Gln488, Gly489, andand Arg455 (2.99) 8-ene-10,16,25,30-tetrone) Ala595 Gly374 (3.25), Lys376 (2.9), ZINC000095914813 (5-[(Z)-2-[(2S,3S)-3-(3,5-dihydroxyphenyl)-2-(4- Cys377 (3.07), Glu396 (2.96), Lys350, Val351, Thr375, His394, hydroxyphenyl)-2,3-dihydro-1-benzofuran-5-yl]ethenyl]benzene-1,3-diol) −10.1 Ser449 (2.54), Cys451 (3.16), Thr448, Pro450, Gly487, Gln488, and Arg455 (2.8) Gly489, Arg590, and Ala595 ZINC000085530478 ((1S,2R,4S,7S,8S,10S,13S,17R,18S,21S,25S,27R)-7- (furan-3-yl)-25-hydroxy-8,20,20-trimethyl-3,6,15,19- Thr375, Lys376, Cys377, tetraoxaoctacyclo[19.3.2.11,10.02,4.02,8.013,18.017,21.017,27]heptacos-22- −10.0 Arg455 (2.81) and Gly487 (3.06) His394, Cys451, Lys483, Ile484, ene-5,14,26-trione) Ser486, and Gln488 ZINC000085530490 ((1R,2R,3’R,7S,9S,10S,12S,13S,14R,16S,19S,20S)-19- (furan-3-yl)-12-hydroxy-13,20-dimethyl-3’-propan-2-ylspiro[4,8,15,18- Cys377, His394, Cys451, tetraoxahexacyclo[11.9.0.02,7.02,10.014,16.014,20]docosane-9,1’- −10.0 Thr375 (3.12) and Lys376 (2.89) Arg455, Lys483, Ile484, Ser486, cyclohexane]-5,11,17-trione) Gly487, Gln488, and Gly489 Val351, Gly374, Thr375, Lys376, ZINC000085543539 (3-[[(1R,3R)-3-[(1S,5S)-1,5-dimethylcyclohex-2-en-1- Ile484 (2.86, 3.2) and Gly487 Cys377, His394, Ala395,yl]cyclohexyl]methyl]-5-[(1R,4S)-4-(ethylamino)-1,2,3,4- −10.0 Glu396, Ser449, Cys451, tetrahydronaphthalen-1-yl]phenol) (2.86) Arg455, Lys483, Gly489, Arg590, and Thr615 Val351, Thr375, Cys377, His394, ZINC000085592995 ((1R,2R)-2-[(3S,4S)-4-hydroxy-8-[(3- Glu396, Thr448, Pro450, hydroxyphenyl)methyl]-6-methoxy-3,4-dihydro-2H-chromen-3-yl]- −10.0 Ser449 (2.55), Ser486 (3.19), andGly489 (2.88) Cys451, Arg455, Lys483, Ile484, 1,2,3,8,9,10-hexahydropyrano[3,2-f]chromen-1-ol) Glu485, Gly487, Gln488, and Arg590 ZINC000085633079 Ile378, His394, Arg455, Ile456, (9-[[(2S,4S)-5,5-dimethyl-4’-(3-methylbut-2-enoxy)spiro[1,3-dioxolane- −10.0 Lys376 (2.98), Cys377 (3.31), 2,7’-furo[3,2-g]chromene]-4-yl]methoxy]furo[3,2-g]chromen-7-one) and Thr490 (3.07) Lys483, Ile484, Glu485, Gln488, Gly489, Leu511, and Thr513 Lys376, Cys377, Ile378, Lys483, ZINC000101100339 (Qingdainone) −9.7 Asn379 (3.01) Ile484, Glu485, Gly487, Gly489, Thr490, Leu511, and Thr513 ZINC000085532375 ((5E)-5-[(1S,2R,3S,9S,12S,13S)-12-hydroxy-3-methyl- Thr375, Lys376, Cys377, 12-[(1S,5S)-5-methylcyclohex-2-en-1-yl]-5-oxa-17- Asn379, His394, Ile456, Lys483, azatetracyclo[7.7.1.02,6.013,17]heptadec-6-en-4-ylidene]-4-methoxy-3- −9.6 Arg455 (3.11) and Gly487 (3.05) Glu485, Ser486, Gly489, and methylfuran-2-one) Thr490 A total of 310 compounds met this threshold (below−9.5 kcal/mol) and were selected for further analysis. The highest binding affinity to ADAR2 was observed for ZINC000095913861 with a binding energy of−12.0 kcal/mol, followed by ZINC000085996580, ZINC000070454467, and ZINC000042890265, with binding energies of −11, −10.9, and −10.6 kcal/mol, respec- tively. Compounds ZINC000039183320 and ZINC000085593577 had a binding energy of −10.5 kcal/mol, while ZINC000070454124, ZINC000103585067, and ZINC000014637370 had a binding energy of −10.2 kcal/mol. Also, compounds ZINC000013384051, ZINC000059586224, ZINC000070454074, ZINC000085530502, ZINC000085532258, ZINC000085532442, ZINC000095911347, and ZINC000095914813 all had a binding energy of −10.1 kcal/mol. For the top 310 compounds, it was observed that their molecular weights ranged between 350 to 600 g/mol (Figure 1). All compounds which had binding energies lower than −11.0 kcal/mol had molecular weights greater than 500 g/mol (Figure 1). Only one compound (ZINC000014637370) with molecular weight less than 450 g/mol (408.49 g/mol) had a binding energy lower than −10.0 kcal/mol (−10.2 kcal/mol) (Figure 1). The binding energies of shortlisted compounds with large molecular weights suggest that the size and spatial characteristics of the RNA binding site may play a crucial role in facilitating ligand interaction and binding. Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 8 of 34 A total of 310 compounds met this threshold (below −9.5 kcal/mol) and were selected for further analysis. The highest binding affinity to ADAR2 was observed for ZINC000095913861 with a binding energy of −12.0 kcal/mol, followed by ZINC000085996580, ZINC000070454467, and ZINC000042890265, with binding energies of −11, −10.9, and −10.6 kcal/mol, respectively. Compounds ZINC000039183320 and ZINC000085593577 had a binding energy of −10.5 kcal/mol, while ZINC000070454124, ZINC000103585067, and ZINC000014637370 had a binding energy of −10.2 kcal/mol. Also, compounds ZINC000013384051, ZINC000059586224, ZINC000070454074, ZINC000085530502, ZINC000085532258, ZINC000085532442, ZINC000095911347, and ZINC000095914813 all had a binding energy of −10.1 kcal/mol. For the top 310 compounds, it was observed that their molecular weights ranged be- tween 350 to 600 g/mol (Figure 1). All compounds which had binding energies lower than −11.0 kcal/mol had molecular weights greater than 500 g/mol (Figure 1). Only one com- pound (ZINC000014637370) with molecular weight less than 450 g/mol (408.49 g/mol) had a binding energy lower than −10.0 kcal/mol (−10.2 kcal/mol) (Figure 1). The binding ener- gies of shortlisted compounds with large molecular weights suggest that the size and spa- Int. J. Mol. Sci. 2023, 24, 12612 tial characteristics of the RNA binding site may play a crucial role in7 offa3c1ilitating ligand interaction and binding. Figure 1. A plot oFfigmuroele 1c.u Ala rpwlote iogfh mt aogleaciunslatrt hweebiginhdt ianggaiennset rtghiee sbionfdtihnegt oenpe3rg10iecs oomf pthoeu tnodps 3a1f0te crompounds after docking with ADdAocRk2in. gO wniltyhc AoDmApoRu2n. Odsnlwy icthommpooluecnudlsa rwwithe imghotlsecaubloavr ew4e5ig0hgts/ maboolvhea 4d50b ign/dmionlg had binding en- energies below −e1r0g.i5esk cbaell/omwo −l1. 0.5 kcal/mol. 2.3. ADMET Prediction 2.3. ADMET Prediction The prediction of a molecule’s absorption, distribution, metabolism, excretion, and The prediction of a molecule’s absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties is of utmost importance in the drug discovery and develop- toxicity (ADMET) properties is of utmost importance in the drug discovery and develop- ment process. Although more accurate, traditional experimental approaches to assess these ment process. Although more accurate, traditional experimental approaches to assess properties can be time-consuming, costly, and sometimes ethically challenging as compared these properties can be time-consuming, costly, and sometimes ethically challenging as to the computational approach. Notwithstanding, advancements in computational drug compared to the computational approach. Notwithstanding, advancements in computa- studies have provided powerful platforms that can predict these properties with remark- tional drug studies have provided powerful platforms that can predict these properties able accuracy. The 310 shortlisted compounds were subjected to ADMET profiling in order with remarkable accuracy. The 310 shortlisted compounds were subjected to ADMET pro- to select the ligands with the most desirable safety profiles (Table 2). Lipinski’s and Veber’s filing in order to select the ligands with the most desirable safety profiles (Table 2). rules were applied to the compounds. A total of 136 compounds failed Lipinski’s rule, Lipinski’s and Veber’s rules were applied to the compounds. A total of 136 compounds while 177 failed Veber’s rule. The topmosfat icloemd pLoipuinnds,kZi’IsN ruCl0e0, 0w09h5i9le1 3187671 f,awiliethd aVbebinedr’ins gruelnee. rgy of−12.0 kcal, passed both Lipinski’s and Veber’s rules with a TPSA of 94.56 Å2 (Table 2). However, ZINC000070450936 and ZINC000070454365, with binding energies of−11.2 and−11.1 kcal/mol, respectively, failed both Lipinski’s and Veber’s rules. ZINC000070450936 and ZINC000070454365 had TPSA values of 178.53 and 180.3 Å2, respectively. Overall, a total of 121 compounds passed both Lipinski’s and Veber’s rules and were shortlisted for further analyses. Of the 121 compounds, only five comprising ZINC000014637370, ZINC000085532375, ZINC000085547677, ZINC000085547700, and ZINC000101100339 were predicted as blood–brain barrier (BBB) permeants. The 121 shortlisted compounds were further subjected to toxicity tests using OSIRIS DataWarrior [55], of which a total of 90 were shortlisted. Compounds that were predicted to have two or more toxicity risks were eliminated. Additionally, compounds with tu- morigenic and mutagenic effects were eliminated since ADAR2 inhibition is implicated in certain cancers [56], including lung cancer [57]. Furthermore, ADAR2 inhibition may promote tumor growth since ADAR2 has been shown to suppress tumors [25,58,59]. Com- pounds with tumorigenic and mutagenic effects may be involved in promoting the growth of tumors and the spread of cancers during ADAR2 inhibition. Int. J. Mol. Sci. 2023, 24, 12612 8 of 31 Table 2. ADME prediction for some shortlisted TCM compounds. ESOL No. of No. of Compound MW (g/mol) Consensus TPSA (Å2) BBB GIlogP o/w Permeant Absorption Solubility Lipinski’s Rule Veber’s RuleClass Violations Violations ZINC000095913861 556.6 5.97 94.56 No Low Poorlysoluble 1 0 ZINC000085996580 508.48 4.47 136.66 No Low Poorlysoluble 1 0 ZINC000070454467 526.53 4.47 137.96 No Low Poorlysoluble 1 0 ZINC000042890265 538.46 5.27 173.98 No High Poorlysoluble 1 0 ZINC000039183320 474.6 3.93 94.45 No High Moderatelysoluble 1 0 ZINC000085593577 487.54 3.55 126.15 No High Moderatelysoluble 0 0 ZINC000070454124 564.58 3.38 119.34 No High Moderatelysoluble 1 0 ZINC000103585067 510.53 1.27 125.43 No High Soluble 1 0 ZINC000014637370 408.49 4.58 64.99 Yes High Moderatelysoluble 0 0 ZINC000013384051 486.47 3.44 139.84 No Low Poorlysoluble 1 0 ZINC000059586224 486.51 5.7 61.81 No Low Poorlysoluble 0 0 ZINC000070454074 500.54 2.17 128.73 No High Soluble 1 0 ZINC000085530502 578.65 3.31 124.8 No High Moderatelysoluble 1 0 ZINC000085532258 561.71 4.27 88.46 No High Poorlysoluble 1 0 ZINC000085532442 548.7 4.36 88.46 No High Poorlysoluble 1 0 ZINC000095911347 526.53 1.37 137.96 No High Poorlysoluble 1 0 ZINC000095914813 454.47 4.01 110.38 No High Poorlysoluble 0 0 ZINC000085530478 536.57 2.32 124.8 No High Moderatelysoluble 1 0 ZINC000085530490 568.65 3.35 124.8 No High Moderatelysoluble 1 0 ZINC000085543539 471.72 7.08 32.26 No Low Poorlysoluble 1 0 ZINC000085592995 490.54 3.47 97.61 No High Moderatelysoluble 0 0 ZINC000085633079 556.56 5.46 102.64 No Low Poorlysoluble 1 0 ZINC000101100339 363.37 3.25 63.47 Yes High Moderatelysoluble 0 0 ZINC000085532375 481.62 3.91 68.23 Yes High Moderatelysoluble 0 0 A total of nine compounds, including ZINC000013310993, ZINC000014686335, ZINC000085547677, ZINC000103559699, ZINC000085548190, ZINC000085567825, ZINC000085761575, ZINC000085976998, and ZINC000095914856, were predicted to be highly mutagenic, while 12 were predicted to have low mutagenicity. A total of 100 compounds were predicted to have no mutagenic effects. For tumorigenicity, three compounds, in- cluding ZINC000103578914, ZINC000103559699, and ZINC000085976998, were predicted as high; eleven (including ZINC000085594038, ZINC000085594040, ZINC000085594044, ZINC000085594057, ZINC000103527863, ZINC000103543220, ZINC000085547700, ZINC000085594065, ZINC000095914212, ZINC000085547677, and ZINC000085548190) were predicted as low; 109 were predicted to have none (Table S1). A total of 76 compounds were predicted to have high reproductive effects while two (ZINC000085532375 and ZINC000013310993) were predicted as low, leaving 97 compounds with no reproduc- tive effects. A total of 29 compounds were predicted to have high irritancy, while three (ZINC000103543220, ZINC000103578914, and ZINC000085548190) were low. A total of 89 compounds were predicted as non-irritants. In all, a total of 58 compounds were pre- dicted as non-tumorigenic, non-mutagenic, and non-irritant, and had no reproductive effect (Table S1). The known inhibitor, 8-azanebularine, was also predicted as a non-tumorigenic, non- mutagenic, and non-irritant, and had no reproductive effect (Table S1). The topmost Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 11 of 34 contacts with Lys376, Cys377, Ile378, His394, Lys483, and Glu485 (Figure 2a and Table 1). The pyrimidine ring of 8-azanebularine was observed to be involved in hydrophobic con- tacts with Cys377, Lys483, and Glu485; the hydroxides attached to the furan were involved in all five hydrogen bonds observed; the triazole formed hydrophobic interactions with Lys376 and Ile378 (Figure 2a,b). ZINC000095913861, which had the least binding energy Int. J. Mol. Sci. 2023, 24, 12612 (−12.0 kcal/mol), was observed to form two hydrogen bonds with Asn379 (2.92 Å) 9aonfd31 Gly489 (2.99 Å) and hydrophobic contacts with Thr375, Lys376, Cys377, Ile378, His394, Arg455, Ile456, Lys483, Ile484, Glu485, Thr490, and Leu511 (Table 1, Figures S1a and S2a). comZIpNoCun00d0,0Z8I5N9C960508000 9i5n9te1r3a8c6t1e,dw withitha bthined AinDgAeRne2r gvyiao tfe−n 1h2y.0dkrocgale/nm booln, wdsa swpirthed riectsei-d duaess nIloen37-t8u (m3.o0r1i gÅe)n, iAc,rng4o5n5-m (2u.9ta9g Åe)n,i Lc,yasn4d83n (o3n.1-7ir Årit)a, nIlte,4b8u4t (h2.a5d5 anhdig 2h.8r8e pÅr)o, dGulcyt4iv87e (e3f.f0e5ct Å)(, TLaebule51S1 )(.2C.8o5m Åp)o, uLneud5s1Z2I N(3C.1010 Å00)8, 5T9h9r6551830 (a2n.9d7 ZÅIN), Can0d00 A07r0g4559404 (627.8w Åit)h (Tbainbdlein 1g, Fenigeurgreiess S1bo fa−n1d1 .S02abn)d. I−t 1a0ls.9o kfcoarlm/medo l,hryedsrpoepcthiovbeliyc, ianlsteorpacatsisoends twheittho xVicailt3y5r1i,s kThfirlt3e7r5. ,H Loyws3e7v6e,r , CyZs3IN77C, 0H00is0389545,9 4T0h5r74,4w8,h Cicyhsh4a5d1,a Gbliun4d8in5g, aender gLyeuo5f1−21. 1Z.1INkCca0l/00m0o7l0,4w54as46p7r,e dwichtiecdh thoahda vae binndoinmgu etnageregnyic iotfy ,−l1o0w.9 tkucmalo/rmigoeln, iwciatys, ahlisgoh orbesperrovdeudc toiv feoerfmfe cttws,oa hnyddhriogghenir rbitoanndcsy wriistkhs , Hias3n9d4w (3a.s15th Åu)s aenlidm Ginlayt4e8d7( (T2a.b9l1e ÅS1),) .anAdls hoy, tdwropohfothbeicfi bvoencdosm wpiothu nTdhsr3w7h5i,c Lhyws3e7re6,p Creyds3ic7t7ed, Lyass48B3B, BIlpe4e8rm4, eSaenrt4s8(6Z, IGNlCn0408080, 8G5l5y4478697,7 Aarngd59Z0IN, aCn0d0 A00l8a559457 (7T0a0b) lfea i1le, dFitghuerteosx Sic1icty arnidsk Sfi2lct)e.r ZIN(TCab0l0e0S014)2.890265 (disulfuretin), an aurone derivative made up of two sulfuretins, was arranged in a cis isomeric form, establishing five hydrogen bonds with Cys377 (3.08 Å), 2.4. ADAR2–Ligand Interaction Profiling Cys451 (3.15 Å), Gly452 (3.19 Å), Ser449 (2.7 Å), and Arg590 (3.05 Å), and 15 hydrophobic bonds wPriothte irne–sliidguaensd Linytse3r5a0ct, ioVnasl3a5r1e, cTruhcri3a7l5in, Ldyrus3g7d6i,s cHoivse3r9y4,,m Gollue3c9u6la, rTrhecr4o4g8n,i tPiorno,4a5n0d, Arugn45d5e,r Isltea4n5d6i,n Lgytsh4e83m, Ielceh4a8n4,i sGmlys4o8f7b, Giollyo4g8ic9a, lapnrdo Tcehsrs4e9s0. (TThaebrleef 1o,r eF,igvuisrueas lSiz1idn ganadn dS2adn)a. - ZINlyCzi0n0g00th3e9s1e83in3t2e0r awctaiso nalssios oebssseenrvtieadl atos tfhoermy p firvoev ihdyedirnosgigehnt sboinntdost hweitbhi nCdyins3g7m7 (o3d.0e1s Åan)d, Ilei3n7t8e r(m3.1o9le Åcu),l aArscno3n7t9a (c3ts.1e1x Åis)t,i nGglub3e9t6w (e2e.7n7p Åro),t eainnds Saenrd44s9m (a3l.l14m Åol)e, caunlde 1li5g hanyddsro(pTahbolbeic1 , Figures 2, S1 and S2). The known inhibitor, 8-azanebularine, interacted with the ADAR2 contacts with Val351, Thr375, Lys376, His394, Thr448, Pro450, Cys451, Arg455, Lys483, via hydrogen bonds with residues Thr375 (bond lengths of 2.94 and 3.14 Å), Ile484 (bond Ile484, Glu485, Gln488, Gly489, Arg590, and Ala595 (Table 1, Figures S1e and S2e). lengths of 2.82 and 3.2 Å), and Gly487 (bond length of 3.21 Å), and formed hydrophobic ZINC000014637370, which has a benzopyrano pyran fused to a benzopyran (or contacts with Lys376, Cys377, Ile378, His394, Lys483, and Glu485 (Figure 2a and Table 1). chrTohme epnyer)i,m inidteinraecrtiendg wofit8h- aCzyans3e7b7u l(a3r.3in4e Åw),a As osnb3se7r9v (e2d.9t7o Åbe), iSnevro4l8v6e d(3i.n31h Åyd),r oanpdho Gbliyc4c8o9n - (3.1ta9c Åts)w viitah hCyydsr3o7g7e, nL ybso4n8d3,sa annddG relus4id8u5;etsh Tehhry3d7r5o, xLidyse3s7a6t,t aHchise3d94to, Cthyes4fu5r1a, nLywse4r8e3i,n Ivleo4lv84ed, Gluin48a5ll, fiGvlye4h8y7d, arongde Tnhbro4n90d svioab hseyrdvreodp;htohbeitcr biaoznodles f(oFrigmuerde 2hcy,ddr).o Tpwhoob oicf tihnete trharceteio onxsywgeitnh atoLmyss3 i7n6 thane dbeIlnez3o7p8y(rFaignu-breen2zao,bp)y. rZaInNoC p0y0r0a0n9 c5o9r1e3 w86e1r,ew inhvicohlvheadd inth heyldearostgbeinn bdoinngdse nweirtghy Cy(s−37172 .0ankdca lG/lmy4o8l)9,, wwahs ioleb stehrev eodthtoerf otrwmo twhyodhroygdernog beonnbdosn d(As swni3t7h9A asnnd37 S9e(r24.9826)Å w) aerned forGmlyed48 w9 i(t2h.9 t9hÅe )oxayngdehny bdornopdhedob tioc tchoen tmacitdsdwlei tbheTnzher3n7e5 i,nL ythse3 7b6e,nCzyosp3y7r7a,nIole 3p7y8r,aHn icso3r9e4 , (FiAgurgr4e 525c,)I. le456, Lys483, Ile484, Glu485, Thr490, and Leu511 (Table 1, Figures S1a and S2a). (a) (b) Figure 2. Cont. IntI.n Jt.. MJ. oMl. oSl.ciS. c2i0. 22032, 32,42, 4x, F1O26R1 2PEER REVIEW 1120 ooff 3314 (c) (d) FiFgiugruer e2.2 .PProrotetienin–l–ilgiganandd ininteteraracctitoionn mmaappss ffoorr AADDAARR22 ccoompplleexxeedd wiitthh 88--aazzaanneebbuullaarriinnee ((aa,,bb)) aanndd ZZININCC00000001041643673377307 0(c(,cd,d).) .FoFro rththe e22DD ininteterraacctitoionn mmaappss ((aa,,cc)),, tthhee lliiggaanndd iiss ccoolloorreedd vviioolleett,, hhyyddrrooggeenn bobnodnd lelennggththss aarree llaabbeelllleedd ggrreeeenn,,a annddh yhdyrdorpohpohboibc icco cnotancttascatsre asrheo swhnowasnr eads arercds awrictsh wspiothk essptookweasr tdos- wards the ligand. For the 3D profiles (b,d), the ligands are shown as sticks while the protein is rep- the ligand. For the 3D profiles (b,d), the ligands are shown as sticks while the protein is represented resented as ribbons with lines. as ribbons with lines. AZnIaNlyCz0i0n0g0 8th5e9 9m65o8l0ecinutlearra icntetedrawcittihonthse oAf DmAuRlt2ipvleia pterontheiynd–rloiggaenndb ocnodmspwleixthesr ehseidlpu etso idIelen3t7if8y( 3cr.0it1icÅal) ,rAesrigd4u5e5s (i2n.9v9olÅve),dL iyns 4li8g3a(n3d.1 b7iÅnd),inIlge 4a8s4 w(2e.l5l5 aas ncdom2.m88oÅn )b, iGnldyi4n8g7 p(3a.tt0e5rÅns),, wLheiuch5 1w1il(l2 a.8id5 iÅn )t,heL edue5si1g2n (a3n.1d1 oÅpt)i,mTizhart5i1o3n o(2f .l9i7gaÅnd),s faonrd thAerragp5e9u0ti(c2 .p8urÅp)os(eTsa.b Flerom1, thFei ginutreersaSc1tibonan pdroSfi2ble)s. , reItsiadlusoes fTohrmr3e7d5, Lhyyds3r7o6p,h Coybsi3c7i7n, tHeriasc3t9i4o,n Csyws4i5th1, VAarlg345515, , TLhyrs347853,, IlLe4y8s347, 6G, lCuy4s8357, 7G, Hlyi4s8379,4 ,GTlhnr448488, ,aCnyds 4G5l1y,4G8l9u 4w8e5r,ea ncdomLemuo5n1 2r.eZsiIdNuCe0s0 i0n0v7o0l4v5e4d4 6i7n, wlighainchd bihnaddinag binin tdhien RgNenAe brginydoinfg− s1it0e. 9ofk tchael/ AmDoAl,Rw2.a s also observed to form two hydrogen bonds with His394 (3.15 Å) and Gly487 (2.91 Å), and hydrophobic bonds with Thr375, 2.L5y. sP3r7e6d,ictiCony so3f 7B7i,oloLgyicsa4l8 A3,ctivIliety4 8o4f ,theS Sere4le8c6te,d GHlint 4C8o8m, poGulnyd4s8 9, Arg590, and Ala595 (TabIlne s1i,liFcoig uprreesdiSc1ticoann odf Sb2ico)l.ogZiIcNalC a0c0t0iv0i4t2y8 h90el2p6s5 t(od ipsurilofurirteiztien )c,oamnpaouurnodnse fdoerr ifvuarttihveer exmpaedriemuepntoafl twtesotisnuglf.u Trehteisnes ,pwreads iacrtrioannsg ecdanin bae cmisaisdoem uesriincgf oar mva,reisettayb olifs haipnpgrfiovacehheysd, rino-- clguedninbgo nstdrsucwtuitrhe-Cbyasse3d77 m(3e.t0h8odÅs),, mCyasc4h5in1e( 3l.e1a5rnÅin),gG allyg4o5r2ith(3m.1s9, Åan),dS qeru4a4n9ti(t2a.t7ivÅe )s,taruncd- tuArreg-a5c9t0iv(3it.y0 5reÅla),tiaonndsh1i5ph (yQdSrAopRh) ombiocdbeolsn.d Ins wsiiltihcor epsriedduiecstiLoyns c3a5n0 ,aVlsaol3 b5e1 ,uTshedr3 t7o5 ,eLvyalsu3a7t6e, thHe isp3o9t4e,nGtilaul3 t9o6x,iTcihtry4 4o8r, tPhreor4a5p0e,uAtircg 4e5ffi5,cIalcey45 o6f, Lay cso4m83p, oIlue4n8d4,, aGsl yw4e8l7l, aGsl yto4 8i9d,eanntdifyT hnro4v9e0l co(Tmabploeu1n, dFisg wurietshS d1edsairneddS b2ido)l.oZgIiNcaCl 0p0r0o0p3e9r1t8i3e3s.2 0Hweraesinal,s oproebdsiecrtvioend toof faocrmtivfiitvye shpyedcrtorga eonf bonds with Cys377 (3.01 Å), Ile378 (3.19 Å), Asn379 (3.11 Å), Glu396 (2.77 Å), and Ser449 substances (PASS) was employed to determine the biological activity of the shortlisted (3.14 Å), and 15 hydrophobic contacts with Val351, Thr375, Lys376, His394, Thr448, Pro450, compounds [47,48,60]. Cys451, Arg455, Lys483, Ile484, Glu485, Gln488, Gly489, Arg590, and Ala595 (Table 1, FiguCroems Sp1oeuanndds SZ2IeN).CZ0IN00C008050909164568307, 3Z7I0N, wCh00ic0h04h2a8s9a02b6e5n,z aonpdyr ZanINo Cpy0r0a0n10fu11se0d03t3o9a wbeenre- pzreodpiycrtaedn t(oor bceh irnohmibeintoer),s ionft evraarcitoeuds wdeitahmCinysa3s7e7s, (i3n.c3l4uÅdi)n, gA bsnla3s7t9ci(d2i.n97-SÅ, p),teSreirn4,8 c6re(3a.t3in1iÅne),, orannidthGinley 4c8y9cl(o3d.1e9amÅ)invaisaeh, ygdlurocogseanmbionned-6s-pahnodsrpehsaidteu,e dseTohxry3c7y5t,idLiynse3,7 A6,THP,i sa3n9d4, cCyytos4si5n1e, dLeayms4i8n3a,sIeles4. 8S4i,nGcelu A48D5A, GRl2y 4a8l7so, a bnedloTnhgrs4 9t0o vtihaeh dyedarmopihnoabseic fbaomnidlys,( Fthigeusere c2ocm,dp).oTuwnodso fmthaey ptohsrseeesso xayngtie-nAaDtoAmRs2i anctthiveibtye naznodp ayrrea nw-boernthzyo poyf rfaunrothpeyrr eaxnpceorriemwenerteali ntevsotlivnegd. Cinohmypdorougnedns ZbINonCd0s0w00i4th28C9y0s236757 (aPnad: 0G.3ly1248 a9n, dw Phiil: e0t.h12e7o)t, hZeIrNtwC0o0h0y0d8r5o9g9e6n58b0o n(Pdas: (0A.2s7n03 7a9ndan Pdi:S 0e.r148886)), anwde rZeIfNorCm00e0d0w14i6th37t3h7e0o (xPyag: e0n.2b5o5n adnedd Ptoi: t0h.e21m3i)d wdelereb eanlszoe npereinditchteedb eton zboep uysraefnuol piny rdaen- mceonretia(F tirgeuartem2ecn).t. ZINC000101100339 was predicted as an antineurotic (Pa: 0.512 and Pi: 0.105) while ZINC000085532375 was predicted to be beneficial in neurodegenerative dis- eases treatment (Pa: 0.377 and Pi: 0.083). Also, ZINC000095913861 (Pa: 0.458 and Pi: 0.080), ZINC000014637370 (Pa: 0.336 and Pi: 0.168), and ZINC000042890265 (Pa: 0.278 and Pi: Int. J. Mol. Sci. 2023, 24, 12612 11 of 31 Analyzing the molecular interactions of multiple protein–ligand complexes help to identify critical residues involved in ligand binding as well as common binding patterns, which will aid in the design and optimization of ligands for therapeutic purposes. From the interaction profiles, residues Thr375, Lys376, Cys377, His394, Cys451, Arg455, Lys483, Ile484, Glu485, Gly487, Gln488, and Gly489 were common residues involved in ligand binding in the RNA binding site of the ADAR2. 2.5. Prediction of Biological Activity of the Selected Hit Compounds In silico prediction of biological activity helps to prioritize compounds for further ex- perimental testing. These predictions can be made using a variety of approaches, including structure-based methods, machine learning algorithms, and quantitative structure-activity relationship (QSAR) models. In silico prediction can also be used to evaluate the potential toxicity or therapeutic efficacy of a compound, as well as to identify novel compounds with desired biological properties. Herein, prediction of activity spectra of substances (PASS) was employed to determine the biological activity of the shortlisted compounds [47,48,60]. Compounds ZINC000085996580, ZINC000042890265, and ZINC000101100339 were predicted to be inhibitors of various deaminases, including blastcidin-S, pterin, creati- nine, ornithine cyclodeaminase, glucosamine-6-phosphate, deoxycytidine, ATP, and cyto- sine deaminases. Since ADAR2 also belongs to the deaminase family, these compounds may possess anti-ADAR2 activity and are worthy of further experimental testing. Com- pounds ZINC000042890265 (Pa: 0.312 and Pi: 0.127), ZINC000085996580 (Pa: 0.270 and Pi: 0.188), and ZINC000014637370 (Pa: 0.255 and Pi: 0.213) were also predicted to be useful in dementia treatment. ZINC000101100339 was predicted as an antineurotic (Pa: 0.512 and Pi: 0.105) while ZINC000085532375 was predicted to be beneficial in neurode- generative diseases treatment (Pa: 0.377 and Pi: 0.083). Also, ZINC000095913861 (Pa: 0.458 and Pi: 0.080), ZINC000014637370 (Pa: 0.336 and Pi: 0.168), and ZINC000042890265 (Pa: 0.278 and Pi: 0.239) were predicted as neurotransmitter uptake inhibitors. Selective serotonin reuptake inhibitors (SSRIs) such as sertraline and fluoxetine, which are neu- rotransmitter uptake inhibitors, exhibit beneficial effects in the treatment of depression, anxiety disorders, and certain forms of obsessive-compulsive disorder [61–63]. Sertraline and fluoxetine have also been found to be helpful in managing depression in individuals with epilepsy due to their ability to lower the risks of triggering seizures [64]. ZINC000042890265 and ZINC000101100339 were predicted to possess antialcoholic properties with Pa values of 0.228 and 0.220, respectively, with corresponding Pi values of 0.097 and 0.102. Abnormal ADAR2 editing of 5-HT2CR is implicated in increased alco- hol intake [40], making ADAR2 a therapeutic target for alcoholism. ZINC000042890265 was further suggested to be useful in treating prion disease (Pa: 0.296 and Pi: 0.121), which is associated with increased RNA editing of FKRP and Rragd in mice. Compounds ZINC000042890265, ZINC000085593577, and ZINC000014637370 were predicted as an- tidyskinetic with Pa values of 0.460, 0.287, and 0.408, respectively, with corresponding Pi values of 0.076, 0.228, and 0.099. These compounds may prove useful in treating dyskinesia, which manifests in most neurologic disorders [65–70]. Compounds ZINC000042890265 (Pa: 0.725 and Pi: 0.013), ZINC000095913861 (Pa: 0.499 and Pi: 0.057), ZINC000085996580 (Pa: 0.595 and Pi: 0.033), ZINC000070454467 (Pa: 0.269 and Pi: 0.193), ZINC000039183320 (Pa: 0.514 and Pi: 0.053), ZINC000014637370 (Pa: 0.727 and Pi: 0.013), and ZINC000101100339 (Pa: 0.248 and Pi: 0.215) were predicted to possess anti-inflammatory properties. Compounds ZINC000070454467, ZINC000095913861, ZINC000101100339, ZINC000014637370, ZINC000085996580, ZINC000039183320, ZINC000042890265, ZINC000085593577, and ZINC000085532375 were predicted as antineoplastics with Pa values of 0.995, 0.928, 0.793, 0.670 0.594, 0.533, 0.532, 0.317, and 0.290; and corresponding Pi values of 0.003, 0.005, 0.013, 0.031, 0.046, 0.062, 0.062, 0.143, and 0.158. They were also predicted as chemopreventive, chemoprotective, antimutagenic, anticarcinogenic, antimetastatic, and beneficial for treating prostate cancer, prostate disorders, prolifera- tive diseases, and preneoplastic conditions. Furthermore, they were predicted to possess Int. J. Mol. Sci. 2023, 24, 12612 12 of 31 antileukemic properties and may demonstrate activity against various types of cancers, including breast, cervical, lung, ovarian, renal, gastric, colon, colorectal, uterine cancers, as well as carcinoma, melanoma, and sarcoma. Although ADAR2 is implicated in var- ious cancers, it has been reported that ADAR2 is downregulated in esophageal squa- mous cell carcinoma (ESCC) [58]. These compounds may help in suppressing cancer growth and progression owing to ADAR2 inhibition. Furthermore, ZINC000042890265, ZINC000085996580, ZINC000014637370, and ZINC000101100339 were predicted as Pin1 inhibitors with Pa values of 0.663, 0.374, 0.324, and 0.252, respectively, with corresponding Pi values of 0.010, 0.103, 0.142, and 0.222. Increased Pin1-ADAR2 interactions have been shown to contribute to ADAR2 stability [71,72], and these interactions increase as neurons mature [71]. Pin1 is essential for editing GluA2 transcripts in cell lines and plays a role in regulating ADAR2 levels and its catalytic activity [72]. Pin1 is also implicated in promoting multiple cancer-driving processes [73], supporting the potential anti-cancer prediction of these compounds. ZINC000095913861 (Pa: 0.561 and Pi: 0.021), ZINC000085996580 (Pa:0.395 and Pi: 0.054), ZINC000039183320 (Pa: 0.194 and Pi: 0.174), ZINC000014637370 (Pa: 0.354 and Pi: 0.065), and ZINC000085532375 (Pa: 0.201 and Pi: 0.166) were predicted as dermatologic and may be beneficial in treating ulcers, pigmentation, and other skin-related issues in melanoma, as ADAR2 has been reported to play a crucial role in the stemness of melanoma and melanoma relapse [74]. Compounds ZINC000095913861 (Pa: 0.315 and Pi: 0.045), ZINC000085996580 (Pa: 0.293 and Pi: 0.060), ZINC000042890265 (Pa: 0.308 and Pi: 0.050), ZINC000039183320 (Pa: 0.284 and Pi: 0.066), ZINC000085593577 (Pa: 0.209 and Pi: 0.157), ZINC000014637370 (Pa: 0.283 and Pi: 0.067), ZINC000101100339 (Pa: 0.205 and Pi: 0.162), and ZINC000085532375 (Pa: 0.243 and Pi: 0.108) were predicted as RNA synthesis inhibitors. ZINC000095913861 (Pa: 0.224 and Pi: 0.066), ZINC000085996580 (Pa: 0.254 and Pi: 0.047), ZINC000042890265 (Pa: 0.189 and Pi: 0.104), ZINC000039183320 (Pa: 0.174 and Pi: 0.130), ZINC000085593577 (Pa: 0.200 and Pi: 0.089), ZINC000014637370 (Pa: 0.241 and Pi: 0.054), ZINC000085532375 (Pa: 0.205 and Pi: 0.084) were further predicted as RNA directed DNA polymerase inhibitors. Also, ZINC000042890265 (Pa: 0.364 and Pi: 0.084), ZINC000101100339 (Pa: 0.274 and Pi: 0.181) were predicted as RNA-directed RNA polymerase (RdRp) inhibitors. The com- pounds were also predicted to possess antiviral properties. BoDV, a non-segmented RNA virus [75,76], exploits the host’s ADAR2 throughout its life cycle to edit its genomic RNA in order to evade immune response [30]. A study showed that the knockdown of ADAR2 limits A-to-I editing of BoDV genomic RNA, leading to a strong host immune response [30]. This is not surprising, as both ADAR1 and ADAR2 regulate autoimmune responses [30,77]. Furthermore, BoDV is characterized by neurological disorders, including ataxia (affecting coordination, balance, and speech) and abnormal depressive behavior [76,78,79]. A structural similarity search via DrugBank revealed that ZINC000095913861 is sim- ilar to tanshinone I (Tan-I) with a score of 0.717. Tan-I, found in Salvia miltiorrhiza, has been shown to be effective in treating anti-inflammatory diseases, including mastitis [80], inflammation due to osteoarthritis [81], and neuro-inflammation [82]. Tan-I also possesses chemoprotective, chemopreventive, and anti-cancer properties against MCF-7 and MDA- MB-231 human breast cancer cells [83,84], colorectal cancer [85,86], hepatic carcinoma [84], gastric cancer [87], cervical cancer [88], ovarian cancer [89], and glioblastoma [90], among others. The broad-spectrum anti-cancer activity of Tan-I warrants the experimental testing of ZINC000095913861 on ADAR2 and cancer cell lines. Furthermore, Tan-I has been shown to possess neuroprotective properties, reverses cognitive and motor impairments, and enhances learning and memory in mice [91–93]. ZINC000070454467 is structurally similar to beta-escin (0.729), escin (0.729), and gly- cyrrhizic acid (0.703). The anti-cancer and anti-inflammatory properties of escin and beta-escin are recorded in literature [94–96]. Escin demonstrated anti-inflammatory activity in a mouse model of global cerebral ischemia, improved learning and memory recovery, and reduced hippocampal damage [97]. Escin was also reported to upregulate the ex- pression of granulocyte-macrophage colony-stimulating factor (GM-CSF), which is known Int. J. Mol. Sci. 2023, 24, 12612 13 of 31 for its neuroprotective properties [97]. Oral administration of escin in a Parkinson’s dis- ease mouse model inhibited neuro-inflammatory cytokine expressions in the substantia nigra [98]. The substantia nigra plays a crucial role in dopamine regulation, motor move- ments, learning, mood, and decision making [99,100]. Dysregulation of dopamine signaling has been associated with schizophrenia [101]. Also, glycyrrhizic acid inhibited kynurenine aminotransferase 2 (KAT2), with IC50 and Ki values of 4.51 ± 0.20 and 10.42 ± 1.62 µM, respectively. KAT2 catalyzes the conversion of kynurenine to kynurenic acid (KYNA) in brain tissues, and the accumulation of KYNA has been linked to schizophrenia [102]. ZINC000039183320 and ZINC000014637370 were predicted to be similar to naringin (scores of 0.746 and 0.704, respectively) and hesperidin (0.744 and 0.833, respectively). Furthermore, ZINC000014637370 is structurally similar to sakuranetin (0.862), naringenin (0.848), taxifolin (0.772), dihydromyricetin (0.772), and silibinin (0.709). Naringin and narin- genin are known adenosine deaminase (ADA) inhibitors [103,104], with naringin inhibiting the deamination of cordycepin with Ki values of 58.8 and 168.3 µmol/L in mouse and human erythrocytes, respectively [103]. Taxifolin also inhibited the human ADA with IC50 of 400 µM [105]. The experimental testing of ZINC000039183320 and ZINC000014637370 as potential ADAR2 inhibitors is warranted since ADAR2 also belongs to the deaminase class of proteins. Hesperidin was shown to prevent and reverse ketamine-induced schizophrenia- like behaviors, including hyperactivity, social withdrawal, and cognitive impairment in mice [106]. Silibinin (10 µM) and naringenin (10 µM) were also shown to possess neuro- protective properties in zebrafish by reversing behavioral changes induced by bisphenol A (17.52 µM) [107]. Dihydromyricetin (DHM) is believed to counteract the intoxication effects of ethanol in mice and may be useful in treating alcohol use disorder [108]. DHM possesses neuroprotective activity and counteracts changes, including increased anxiety levels, re- duced exploratory behaviors, and increased serum corticosterone levels and activation in NF-κB pathway, caused by socially isolating mice [109]. 2.6. Molecular Dynamics Simulations 2.6.1. Analyzing RMSD, RMSF, and Rg The unbound ADAR2 protein and the ADAR2–ligand complexes were subjected to 100 ns molecular dynamics (MD) simulations. Understanding the molecular motion and conformational changes of macromolecules upon small molecule binding is germane to drug discovery [110,111]. MD simulations provide a platform to computationally study these atomic motions and fluctuations by using Newtonian physics approximations, taking into consideration the forces at play between bonded and non-bonded atoms [110,112]. Notwithstanding this, MD simulations have limitations, requiring lengthy simulation periods in order to correctly explain some dynamical properties and the paucity of math- ematical descriptions of some of the physical and chemical forces that govern protein dynamics [113]. However, MD simulations have been shown to be comparable with ex- perimental results and are very useful in drug discovery [113–115]. The root mean square deviation (RMSD), radius of gyration (Rg), and root mean square fluctuation (RMSF) were analyzed after the MD simulations. Herein, the ADAR2-8-azanebularine complex demonstrated the greatest stability with an average RMSD of 0.196 ± 0.025 nm, followed by ADAR2–ZINC000101100339 and ADAR2–ZINC000014637370 complexes with average RMSD values of 0.201± 0.028 and 0.210± 0.023 nm, respectively (Figure 3). The ADAR2–ZINC000085532375, ADAR2–ZINC000042890265, ADAR2–ZINC000039183320, and ADAR2–ZINC000085593577 complexes also had average RMSD values of 0.211 ± 0.030, 0.230 ± 0.031, 0.238 ± 0.031, and 0.247 ± 0.030 nm, respectively (Figure 3). The unbound ADAR2 had an average RMSD of 0.217 ± 0.031 nm (Figure 3) [50] throughout the 100 ns, implying that the ADAR2 achieved higher stability when in complex with 8-azanebularine, ZINC000101100339, ZINC000014637370, and ZINC000085532375 (Figure 3). Although ADAR2 has loop regions, which may account for the slight increase in RMSD values [116], the RMSDs obtained Int. J. Mol. Sci. 2023, 24, 12612 14 of 31 Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 16 of 34 herein are within the acceptable range, as RMSDs up to 3 Å (0.3 nm) are typical for most proteins after MD simulations [117]. Fiigurre 3.. RoRoot omt emane asnqusaqruea dreevdiaetviioanti o(RnM(RSDM)S pDl)otp olof tthoef utnhbeounbdo AunDdARA2D pArRot2eipnr oantedin AaDnAdR2– lAigDaAndR 2c–olimgapnldexecos mthprleoxuegshothurto uthgeh o1u0t0t hnes 1M00Dn simMuDlastiomnusl.a tAioDnAs.R2A–8D-AazRa2n–e8b-uazlarnienbeu, lAarDinAe,R2– ZAIDNACR020–0Z10IN11C000303190, 11A00D3A39R,2A–ZDIANRC20–0Z0I0N1C4603070307104,6 37a3n7d0 , aAnDdAARD2A–ZRI2N–ZCI0N00C008050503825357352 37c5omcopmle-xes dpleemxeosndstermatoends tlroawteedr laovweerargaev eRrMagSeDRsM thSDans tthea nutnhbeounbdo AunDdAARD2A. R2. Thhee aavvereargaegeR gRvga lvuaelsuoefsa lolfA aDllA AR2D–AligRa2n–dlicgoamnpdl ecxoems sphloewxeeds tshhaotwupeodn tlhigaatn udpboinnd ilnigga, nd bAiDndAiRn2g,d AemDoAnRst2r adteedmloownsetrr,aRtegdim lopwlyeinr,g Rggre iamteprlcyoimngp agcrtenaetsesra cnodmstpaabcletnfeoslds ianngdc osmtapbalere fdold- itnogt hceoumnpbaoruendd tsot atthee[ 1u1n8]b.oTuhnedu sntbaoteu n[1d1A8]D. AThRe2 uhandboaunnadv eAraDgAe RRg2 ohfa2d. 0a7n0 ±av0e.r0a0g8en Rmg of 2th.0ro7u0 gh±o u0t.t0h0e81 0n0mns stihmrouulagtihoonupte ritohde w1h0i0le tnhes AsDimAuRl2a–tZioINn Cp00e0ri0o4d28 9w02h6i5lea ntdhAe DAADRA2–R2– ZZIINNCC000000008452583920327655 caonmd pAleDxAesRh2–adZIRNgCv00a0lu0e8s55o3f223.7054 9co±m0p.l0e0x6esa nhdad2 .R0g54 va±lu0e.s0 0o7f 2n.m04,9 ± respectively (Figure 4). The ZINC000042890265 demonstrated higher stability than all ten 0.006 and 2.054 ± 0.007 nm, respectively (Figure 4). The ZINC000042890265 demonstrated ligands, including IHP, which were previously shown to be good ADAR2 binders in the hIHigPhbeirn sdtianbgilsititye t[h50a]n. Tahlle teAnD lAigRa2n-d8-sa, zianncelubudlianrgin IeHcPom, wplheixchd ewmeornes ptrraetvediocuosmlyp sahraobwlenR tgo be g(2o.0o5d8 A±D0A.0R072 nbmin)dteortsh iant othfeA IDHAPR b2i–nZdIiNnCg 0s0it0e0 4[52809].0 T26h5e aAnDd AARD2A-8R-2a–zZaInNeCbu00la0r0i8n5e5 3c2o3m75plex dcoemmpolnesxtersat(eFdig cuorme p4)a.raFboler tRhge (120.005n8s ±s i0m.0u0l7a tniomn) pteor itohda,t AofD AADRA2–RZ2I–NZCIN00C0000140603472387900,265 aAnDdA ARD2–AZRIN2–CZ0I0N00C309108030382505,3A2D37A5R c2o–mZIpNleCx0e0s0 (0F8i5g5u9r3e5 747),. aFnodr AthDeA 1R020– nZsI NsiCm0u00la1t0i1o1n0 0p3e3r9iod, AcoDmApRle2x–eZsIaNlsCo0h0a0d01a4v6e3r7a3g7e0R, gAvDaAluRes2–oZf I2N.0C5800±0003.090188,323.2006,4 A±D0A.0R112,–2Z.I0N65C±0000.00865,5a9n3d577, a2n.0d6 5A±D0A.0R027–nZmIN, rCe0sp00e1ct0i1v1e0ly03(F3i9g ucorem4p).lexes also had average Rg values of 2.058 ± 0.008, 2.064F ±o r0.t0h1e1,R 2M.0S6F5 ±a n0a.0ly6s, easn,dr e2s.i0d6u5e ±i n0.d0e0x7e nsm38, 0r–e3sp90e,ct4i6v0e–ly4 7(8F,ig4u9r2e– 541).5 , 585–595, and 650–655 were observed to have high fluctuations for all the ADAR2–ligand complexes (Figure S3). On the other hand, at residue positions 352–359, 369–375, 394–397, 445–455, 482–486, and 512–560, very low fluctuations were observed (Figure S3), implying that these regions could be involved in strong interactions with the various ligands and thus have higher stability [119]. IntI.n Jt.. MJ. Mol.o lS. cSic. i2. 0220233, ,2244, ,x1 2F6O12R PEER REVIEW 15 of 3117 of 34 FFiigguurree4 .4R. aRdaidusiuosf goyf rgatyiorant(iRogn) (pRlogt)o pf ltohte uonf bthouen udnAbDouAnRd2 pArDotAeinR2an pdrAotDeAinR a2n–ldig aAnDdAcoRm2p–lleigxeasnd com- tphlreoxuegsh otuhtrothueg1h0o0unts tMheD s1i0m0u nlast ioMnsD. Osnimavuelraatgioen, asl.l tOhen AaDvAerRa2g–el,i gaalnld tchoem AplDexAesRd2e–mligoannstdra tceodmplexes ldowemeroRngsttrhaatnedth leowunebro Rugn dthAaDn AthRe2 u, inmbpoluynindg AhiDghAeRr 2co, mimppalcytninesgs haingdhfeorl dcoinmg.pactness and folding. 2.6.2. Analyzing Snapshots and Hydrogen Bonds For the RMSF analyses, residue indexes 380–390, 460–478, 492–515, 585–595, and 650– The hydrogen bond interactions between the ADAR2 and each ligand were evaluated u6s5i5n gw“egrme xohbbseornvde”d( Ftiog uhraev5e) .hSingahp flshuocttsuaatt2io5nnss fionrte arvlla tlhs ew AerDe aAlsRo2g–elnigearantded cotomvpislueaxleizse (Figure tSh3e)p. Oosnit itohne ooftthheerl ihgaanndd,s aatt rtheseisdeutiem peosstietpios.nTs h3e5s2n–a3p5s9h, o3t6s9s–h3o7w5e, d39th4e–389-a7z, a4n4e5b–u4l5a5ri,n 4e82–486, wanasdn 5o1t2s–t5a6b0le, vinertyhe loRwN Aflubcitnudaitnigonssit ewoefreth oebAseDrAveRd2 .(FTihgeu8r-ea Sz3an),e ibmuplalryiinnegr ethmaat itnheedsein regions tchoeuRldN Abeb iinndvionlgvepdoc ikne tsutrnotnilg7 5inntse,rwachteiroenist mwoitvhe dthtoe tvhaerrieoguiso nlisguarnrodusn adned bthyuress hidauvees higher Ssetar4b5i8li,tyH i[s141690],. Glu461, Pro462, Ile463, Glu466, Pro467, Ala468, Asp469, Arg470, His471, His552, Asp554, and His555, and remained there until the end of the simulation. This r2e.g6i.o2n. Awnaaslypzrienvgio Sunslaypsphreodtsic atendd vHiaydCrAoSgTepn aBsoandpso tential binding site of the ADAR2 protein [50]. According to “gmx hbond”, 8-azanebularine formed only one hydrogen bond The hydrogen bond interactions between the ADAR2 and each ligand were evaluated with ADAR2 at times 25, 50, 75, and 100 ns. However, from the protein–ligand interaction musaipnsg, 2“gHm-bxo hnbdosnwde”r e(Foibgsuerrev e5d). aStn2a5pnshsowtsit aht S2e5r 4n5s8 in(btoenrvdallesn wgtehrse oafls2o.9 g6eannedra3t.e0d9 tÅo) visual- aizned tohnely poonseitwioans oofb stherev elidgaant tdims aest 5th0e[sGel uti4m66e (s3t.3e5psÅ. )T],h7e5 s[Anaspp5s0h3ot(3s .0sh1oÅw)]e, dan tdhe1 080-anzsanebu- [lAarsipn5e0 3w(2a.s6 6nÅot) ].stable in the RNA binding site of the ADAR2. The 8-azanebularine re- mainAeldl t ihne tphoet eRnNtiaAl lbeianddcionmg pooucnkdest uexncteilp 7t 5Z InNs,C w00h0e0r8e5 5it3 m23o7v5ewde troe othbese rrevgeidonto sbuirnrdounded sbtayb lryeisnidtuhesR NSeAr4b5in8d, inHgiss4it6e0t,h rGoulug4h6o1u,t Pthreos4i6m2u, laIlteio4n6.3C, oGmlup4o6u6n,d PZrIoN4C6070, 0A08l5a5436283, 7A5 sp469, mAorvge4d70a,w Haiys4fr7o1m, Hthies5A5D2,A ARs2pp5r5o4t,e ainnadt H25isn5s5,5im, apnlydi nregma apionseitdiv tehbeirned uingtiel nthereg eyn(dre opfu tl-he sim- suiolant)i,own.h Tichhisc oruegldioinnfl wuaesn cperethveiobuinsldyi npgreadffiicntietyd. vHiao wCeAvSeTr,pa tas5 0a npsoZteINntCia0l0 b0i0n8d5i5n3g23 s7i5te of the bAinDdAs Rto2 ApDroAtRei2n in[5a0]d. iAffecrceonrtdrienggi otno, “sgumrroxu hnbdoenddb”y, r8e-saizdauneesbAurlga4r3in5e, Lfeourm43e6d, L oyns4ly3 7o,ne hy- Vdarlo4g40e,nP broo5n7d1 ,wPritoh5 7A2,DLAeuR527 3a,t Ttyimr5e7s4 ,2a5n, d50T,h 7r557, 5a.nIdt r1e0m0a ninse. dHinowtheivsebri,n fdrionmg rtehgeio pnrotein– until the end of the 100 ns simulation period. At times 50 and 100 ns, no hydrogen bonds ligand interaction maps, 2 H-bonds were observed at 25 ns with Ser458 (bond lengths of with ADAR2 were observed. However, at 75 ns, ZINC000085532375 formed a hydrogen b2o.9n6d awnidth 3L.0e9u 5Å7)3 aonfdle onngltyh o3.n0e0 wÅ,aws ohbicsherwvaesda alsto tipmreedsi c5t0e d[Gvliua4“6g6m (x3.h3b5o Ånd)]”, .75 [Asp503 (3.01 Å)], and 100 ns [Asp503 (2.66 Å)]. Int. J. Mol. Sci. 2023, I2n4t,. 1J.2 M61o2l. Sci. 2023, 24, x FOR PEER REVIEW 16 of 31 18 of 34 Figure 5. Plot showFiignugrteh 5e. nPulomt bsherowofinhgy dthroeg neunmbboenrd osff ohrymdreodgbeent wboenednsA fDorAmRe2d abnedtwtheens hAoDrtAlisRt2ed and the shortlisted compounds throucgohmopuotuthneds1 0th0rnosugMhDoust imthue la1t0i0o nn.s CMoDm psoimunudlatZioINn.C C00o0m0p4o28u9n0d2 6Z5INfoCrm00e0d04t2h8e90265 formed the greatest number ogf rheyadtersotg neunmbobnerd sofw hiythdrAoDgeAnR b2otnhdros uwgihtho uAtDthAeRs2im thurloautigohnopuetr tihode .simulation period. Compound ZINAC0ll0 t0h0e4 2p8o9t0e2n6ti5alf olermade dcotmhephouignhdes tenxucempbt eZrINofCh0y0d0r0o8g5e5n32b3o7n5d ws ewriet hobserved to bind ADAR2 (7) at 17 sntsa.bAlyt 2in5 tnhse, hRyNdAro bgienndbinogn dssitwe tihthroCuygsh3o77ut( 3th.1e4 sainmdu3la.1t5ioÅn.) ,CAormg4p5o5u(n2d.9 ZÅI)N, C000085532375 Gln488 (2.99 Å),manodveGdl ya4w8a9y( 2fr.8o9mÅ t)hwe AerDe AobRs2e rpvreodte, ianlt hato u25g hns“,g imxplhybinogn da” pporseidtiivcete bdin3d. ing energy (re- At 50 ns, only onpeulhsyiodnr)o, gwehnicbho ncoduwldi tihnflCuyesn3c7e7 t(h3e. 1b7inÅd)inwga asffimnaitiny.t aHinoewde,vwerh, ialet 5f0o rnms iZnIgNC000085532375 new bonds withbLinyds3s5 t0o (A2.D69AÅR)2, Sine ra4 4d9iff(2e.r7e6nta nredg3io.2n9, Åsu)r,raonudndGelnd5 b9y1 (r2e.s8id2uÅe)s. Artg7453n5,s ,Leu436, Lys437, four hydrogen bVoanld4s40w, ePrreof5o7r1m, Pedro: 5t7w2o, Lweiuth57S3e,r 4T4y9r5(724.7, 6aanndd T2h.9r507Å5.) Iatn rdemonaeineeadc hinw tihtihs binding region Arg455 (2.78 Å) uanndtilG thlne4 e8n8d( 2o.f7 5thÅe )1.0A0t nths esiemnudlaotfiothne pseimrioudla. tAiot nti,mtherse 5e0h aynddro 1g0e0n nbso, nndo shydrogen bonds were formed witwh irtehs iAduDeAsRS2er w44e9re(2 o.6b8seÅrv),eAdr. gH45o5w(e2v.9e9r, Åa)t, 7a5n dnsG, lZuI4N8C5 0(20.04058Å55),3a2l3t7h5o ufogrhmed a hydrogen only one was prebdoincdte wd ivtiha L“egum5x73h obfo lnedn”g.thT h3e.0n0u Åm, bwehriocfhh wyadsr oaglseon pbroenddicstefodr vmiae d“gbmy xth hebond”. ADAR2–ZINC000042C8o9m02p6o5ucnodm ZplIeNxCm00a0k0e4s2Z8I9N02C6050 f0o0r4m28e9d0 t2h6e5 hainghinetsetr nesutminbgecra onfd hidyadtreogen bonds with to probe further AsinDcAe Rli2g a(n7)d abt i1n7d innsg. Aant d25a cntsi,v hityydhraovgeenb ebeonnsdhso wwinthto Cbyes3in7fl7 u(3e.n1c4e danbdy 3t.h1e5 Å), Arg455 (2.9 formation of muÅlt)i,p Glelnh4y8d8r (o2g.9e9n Åbo),n adnsd[ G12ly0,418291 ](.2.A89n oÅt)h werecreo mobpsleerxvwedo, ratlhthmouengthi o“ngimngx ihsbond” predicted ADAR2–ZINC0030. 0A8t5 5509 3n5s7, 7o.nZlyIN oCne0 0h0y0d8r5o5g9e3n5 7b7ownda swpirthed Cicytse3d7v7 i(a3“.1g7m Åx) hwbaosn md”aitnotafoinrmed, while forming 1, 1, 2, and 3 hynderowg ebnonbdosn wdsitwh iLthysA35D0A (2R.629a Åt t)i,m Seers42459, (520.7, 67 5a,nadn 3d.2190 Å0 )n, sa,nrdes Gpelnct5i9v1e l(y2.82 Å). At 75 ns, (Figure 5). Howfoeuvre rh, yfrdormogethne bionntdersa wcteioren fmorampesd, :o tnweo[ Gwliyth4 8S9er(424.999 (2Å.7)]6, athndre e2.9[A0 sÅn)3 a9n1d one each with (2.71 Å) and His3A9r4g(435.51 3(2a.n78d Å3.)2 0anÅd) ]G, tlhnr4e8e8[ (A2s.7n53 9Å1).( 2A.7t 5thÅe) e, nHdis o3f9 4th(e2 .s8i2mÅu)l,aatinodn,G thlyr4e8e7 hydrogen bonds (2.77 Å)], and four [Asn391 (3.32 Å), His394 (2.84 Å), Gln488 (3.13 Å), and Gly489 (2.91 Å)] were formed with residues Ser449 (2.68 Å), Arg455 (2.99 Å), and Glu485 (2.45 Å), although were formed at 25, 50, 75, and 100 ns, respectively. only one was predicted via “gmx hbond”. The number of hydrogen bonds formed by the 2.7. MM/PBSA CAalDcuAlaRti2o–nZsIfNorCt0h0e0A0D42A8R9022–6L5ig caonmd pCloemx pmleaxkeses ZINC000042890265 an interesting candidate 2.7.1. AnalyzingtBo ipndroinbge FfurertehEern esringyce ligand binding and activity have been shown to be influenced by the formation of multiple hydrogen bonds [120,121]. Another complex worth mentioning The molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) method is is ADAR2–ZINC000085593577. ZINC000085593577 was predicted via “gmx hbond” to a computational technique that is used to calculate the binding free energy of a small form 1, 1, 2, and 3 hydrogen bonds with ADAR2 at times 25, 50, 75, and 100 ns, respectively molecule to a protein [122–125]. The binding free energy is a measure of the strength of (Figure 5). However, from the interaction maps, one [Gly489 (2.99 Å)], three [Asn391 (2.71 the interaction between the small molecule and the protein, and it is an important factor Å) and His394 (3.13 and 3.20 Å)], three [Asn391 (2.75 Å), His394 (2.82 Å), and Gly487 (2.77 Int. J. Mol. Sci. 2023, 24, 12612 17 of 31 in drug discovery, as molecules with a favorable binding free energy are more likely to be effective as drugs. The g_mmpbsa tool was used to perform the MM/PBSA calculations of the protein–ligand complexes using the complete 100 ns simulation trajectories [122]. The binding free energy, van der Waals (vdW), electrostatic, polar solvation, and solvent accessible surface area (SASA) energies were computed using this method (Table 3). Table 3. Energy terms contributing to ADAR2 binding to the top compounds and 8-Azanebularine from MM/PBSA calculations. All energy values are presented in kJ/mol as energy ± standard deviation. Compound vdW Electrostatic Polar Solvation SASA Binding ZINC000042890265 −185.615 ± 1.989 −81.409 ± 2.341 174.426 ± 3.098 −24.866 ± 0.150 −117.236 ± 4.040 ZINC000039183320 −110.150 ± 2.956 −23.952 ± 1.891 82.789 ± 2.665 −15.755 ± 0.366 −67.023 ± 3.022 ZINC000101100339 −156.644 ± 1.535 12.671 ± 1.635 95.394 ± 2.438 −16.419 ± 0.171 −64.913 ± 2.029 ZINC000014637370 −218.832 ± 1.310 −42.038 ± 1.376 108.673 ± 1.974 −22.854 ± 0.099 −174.911 ± 2.104 ZINC000085532375 −69.224 ± 5.194 289.884 ± 7.174 18.341 ± 2.572 −9.868 ± 0.750 228.669 ± 3.288 ZINC000085593577 −224.512 ± 2.058 −47.130 ± 1.820 158.815 ± 2.933 −24.585 ± 0.180 −137.369 ± 2.365 8-Azanebularine −49.600 ± 2.917 227.826 ± 11.031 75.515 ± 7.041 −7.374 ± 0.412 246.374 ± 5.841 8-Azanebularine rerun −109.745 ± 1.390 310.967 ± 6.418 123.630 ± 5.771 −13.942 ± 0.096 310.779 ± 2.145 The vdW energies of all the complexes ranged from −49.600 (8-azanebularine) to −224.512 kJ/mol (ZINC000085593577) (Table 3), while the electrostatic energies ranged from 310.967 (8-Azanebularine re-run) to −81.409 kJ/mol (ZINC000042890265). ADAR2– ZINC000042890265 and ADAR2–ZINC000085532375 complexes demonstrated the highest and least polar solvation energies, with values of 174.426 and 18.341 kJ/mol, respec- tively (Table 3). The vdW, electrostatic, and polar solvation energies were major con- tributors to the binding free energies of the ADAR2–ligand complexes than the SASA energies. A similar trend was observed for ligands which bound in the IHP binding site of ADAR2 [50]. The SASA energies ranged from −24.866 (ADAR2–ZINC000042890265) to −7.374 kJ/mol (ADAR2-8-Azanebularine), with the ADAR2-8-azanebularine re-run demonstrating a SASA energy of −13.942 kJ/mol (Table 3). ADAR2–ZINC000085593577, ADAR2–ZINC000014637370, ADAR2–ZINC000101100339, ADAR2–ZINC000039183320, and ADAR2–ZINC000085532375 complexes had SASA energies of −24.585, −22.854, −16.419, −15.755, and −9.868 kJ/mol, respectively (Table 3). This implies that ZINC000042890265, ZINC000085593577, ZINC000014637370, ZINC000101100339, and ZINC000039183320, with lower SASA energy values than 8-azanebularine and ZINC000085532375, are situated within a hydrophobic environment at the active site of ADAR2, resulting in reduced exposure to water molecules from the surrounding physio- logical medium [126]. The known ADAR2 inhibitor, 8-azanebularine, had a binding free energy of 246.374 kJ/mol (Table 3). A re-run of the MM/PBSA calculation after another MD simula- tion of the ADAR2-8-azanebularine complex revealed a binding free energy of 310.779 kJ/mol. These two different simulation runs show that 8-azanebularine does not form strong bonds with ADAR2. This is not surprising, as 8-azanebularine was ex- perimentally reported to inhibit ADAR2 reaction with a weak IC50 of 15 ± 3 mM [52]. Generally, the MM/PBSA method is most accurate for compounds with IC50 values in the micromolar and nanomolar ranges [127]. All the potential lead compounds, except ZINC000085532375, had favorable binding free energy with the ADAR2 protein. Com- pound ZINC000085532375 was observed to have a binding free energy of 228.669 kJ/mol (Table 3) and was thus eliminated. Both 8-azanebularine and ZINC000085532375 demon- strated very high electrostatic energies of 227.826 and 289.884 kJ/mol which influenced their binding free energy values. Both ligands were also observed to be unstable in the RNA bind- ing pocket during the MD simulations. Compound ZINC000014637370, on the other hand, demonstrated the highest binding affinity to the ADAR2 protein with a binding energy of −174.911 kJ/mol, followed by ZINC000085593577, ZINC000042890265, ZINC000039183320, Int. J. Mol. Sci. 2023, 24, 12612 18 of 31 and ZINC000101100339 with binding free energies of −137.369, −117.236, −67.023, and Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW −64.913 kJ/mol, respectively (Table 3). 21 of 34 2.7.2. Analyzing Per-Residue Energy Contributions Glu58P8e (r4-r.2es7i0d5u ±e 0e.n1e0r9g5y kJd/mecoml),p Porsoit5io92n s(−w4.e6r0e41p ±e r0fo.3r0m9e1d kJo/mn oela),c hancdo Lmypsl5e9x4 a(f−t3e.r82t5h2e ± 0M.70M79/ PkBJ/SmAolc)o. Fmopru thtaet iAonDsAtRo2–inZvIeNsCtig0a0t0e03t9h1e83e3n2e0rg cyomcopnletrxi,b ountelyd Pbhye4e5a7c hconamtriibnuoteadc iedn- e(rFgiyg uarbeosv6e athned tSh4rae–sSh4ogld) [ w12i3th,1 a2 5v]a. luFero omf −t8h.1e8i6n6t e±r 0a.c6t1io8n2 kmJ/ampso,l r(Fesigiduurees S4Tbh)r.3 F7o5r, ALyDsA37R62,– ZCINysC307070, 1H0i1s1309043,3C9,y Cs4y5s13,7A7 (r−g54.5757,3L6 y±s 04.8237,8I7l ek4J8/m4,oGl)l aun4d85 A, rGgl5y1408 (7−,6G.4l3n1448 8±, 0a.1n4d61G klyJ/4m89ol) cwonetrreiboubtseedrv seidgntiofibceanintlvyo tlov eZdINinCm00o0st10o1f1th00e3A39D bAiRn2d–inligg ainnd thine tRerNacAti obninsd(Tinagb lleo1o)p. W(Fihgiulere Sm4co).l eFcuorla rthdeo cAkDinAgRh2a–sZdINemCo00n0s0tr1a4t6e3d7a3n70a bciolmityplteoxp, rCoydsu3c7e7 co(−n5f.o4r9m45a ti±o n0s.2r3e4s6e mkbJ/lminogl), experimentally determined protein–ligand complex structures [128,129], it is more ap- Arg455 (−8.5618 ± 0.3376 kJ/mol), Ser486 (−6.6641 ± 0.1840 kJ/mol), Gln488 (−13.2511 ± propriate to analyze the protein–ligand interactions from MD simulations. Molecular 0.4194 kJ/mol), and Gly489 (−5.1627 ± 0.2240 kJ/mol) contributed favorable energies, while docking can provide a conformation/pose that serves as a favorable starting point for Gcloun3d9u6 c(t6in.0g73m5o ±le c0u.7la3r59d yknJ/ammoicl)s wsimasu ulantfioavno-braasbeled finorv elsigtiagnadti obnisnd[1in28g] .(FDigouckrein Sg4pgo).s eFsor AnDeeAdRt2o–bZeINveCri0fi0e0d08b5y5M93D57s7im, Luylast3i5o0n s(−a5n.d65t9h8e i±n t0e.2ra9c5t7io knJs/mcaonl)b, eCbyest4te5r1u (n−d5e.2r8st1o4o d± f0r.o1m461 ksJi/mmuolla),t iAonrgs4t5h5a n(−d7.o2c6k0i7n g± p0o.3s8e2s1[ 1k3J0/m]. oMl),o raenodv eLre, uth5e11M (−M5/.8P4B5S8A ± m0.2e0th5o1d kcJ/omnsoild) ecrosntthreib- uetneder fgaevtiocrsaobflyp,r wotheiinle– Gligluan39d6i n(9te.5r0a3c1ti o±n 1s.,2i5n5c0lu kdJi/nmgotlh) ecodnytnriabmuitcedb euhnafvaivoorroafbtlhe eesnyesrtgeym to ZdINurCin0g00m0o8l5e5c9u3la5r77d ybninadminicgs (sFimiguulraet iSo4nds.). FFigiguurere 66. .PePr-erre-sriedsuideu eeneenrgeyrg dyedcoemcopmopsiotsioitnio pnloptlso tosf othf et hAeDAADRA2–Rl2ig–alingda ncdomcopmlepxleesx. eAs.DAARD2A cRo2m- pcleoxmepdl exweidthw iZthINZCIN00C00004020849208296052,6 5Z, IZNINCC00000003093198138332302,0 , ZZIINNCC000000110011110000333399,, ZZININCC00000001041643673377307,0, ZZININCC000000008855553322337755, ,ZZIINNCC000000008855559933557777,, 88--aazzaanneebbuullaarriinnee,, aanndd8 8--aazzaanneebbuulalarirninee( r(er-er-urun)na) raereco cloolroerded bbluluee, ,ggrreeeenn,, rreedd,, oorraannggee,, ppuurrpplele, ,b brorwown,np, ipnikn,ka,n adncdy acny,arne,s rpeescptievcetliyv.eGlyr.i dGlriinde slianreess ahroew snhoalwonng atlhoeng thye-a yx-iasxtios htoel hperlepa dreaabdilaitbyi.lity. FTohr eApDeAr-rRe2s–idZuINe Cen0e0r0g0y85d5e3c2o3m75p o(Fsiitgiounrea Sn4aely) saensdr eAveDaAleRd2a-8w-aizdaenerabnuglaerionfee (nFeirgguyre Sc4ofn) tcroibmuptiloenxessa, mseovnegrathl ereAsiDduAeRs2 croenstirdiubeust,ehdi gsihglnigihfitcianngt tehneeirrgviaersy dinuge rtool etshein dsytanbaimlizicin nga- tuthree AofD tAheR 2li–glaignadn dbicnodminpgl epxreos.ceNsso. tDabulyri,nkge ythree scidouuresseL oyfs 3t5h0e, 1C0y0s 3n7s7 M, CDy ss4i5m1u, Alartigo4n5,5 ,8- Ser486, Gln488, and Arg510 exhibited significant energy contributions, suggesting their azanebularine and ZINC000085532375 exhibited mobility and explored different binding crucial involvement in ligand recognition and binding. Glu396, on the other hand, was cavities of ADAR2. This movement led to interactions with multiple residues at different observed to contribute high energy which is unfavorable for ligand binding. Residues stCaygse3s7 7o,f Cthyse4 5si1m, Aulragt4io55n,, arnedsuGltlinn4g8 8inw vearerypirnegd iecnteedrgvyia cboontthridbouctkioinngs. aFnodr MthMe /APDBSAAR2a-s8- aizmanpeobrtualnatrifnoer cliogmanpdlebxi,n ad tiontgailn ofth 3e8 RreNsAidubeinsd cionngtrloiboupt.eTdh feasveorreasbullet senfuerrtghieers cworhrioleb o5r2a rtees- idthueesp croednitcrtibiountsedo bentaeirngeidesv aibaomveo l+e5c uklJa/mr dool.c Fkoinr gth. eL AyDs3A50R2(L–yZsI8N6C7 0in00A08D5A53R213)7,5w choimchpliesx, a total of 39 ADAR2 residues contributed energies below −5 kJ/mol, while 52 residues con- tributed above +5 kJ/mol. The instability of 8-azanebularine in the RNA binding site and binding site hopping could be responsible for its weak IC50 value previously reported [52]. Int. J. Mol. Sci. 2023, 24, 12612 19 of 31 conserved across ADAR proteins, is positioned to face the major groove of the RNA and is in close proximity to the phosphate group adjacent to the flipped-out 8-azanebularine moiety, although Lys350 is not involved in direct interactions with the RNA substrate in the ADAR2–RNA structure [131]. Cys451 and Glu396 are involved in coordinating the zinc ion and ensuring its presence in the catalytic site [16,51]. In the hADAR2, Arg455 and Arg376 are reported to form symmetrical interactions with the phosphate groups located upstream and downstream of the flipped base, helping to anchor the flipped base in a proper orientation for catalytic activity [132]. Therefore, Arg455 mutation to alanine disrupts the symmetrical interactions and reduces steric hindrance on one side, potentially weakening substrate binding [132]. For the ADAR2–ZINC000042890265 complex, seven residues contributed energies above +5 or below−5 kJ/mol. Lys350 (−6.1117± 0.6947 kJ/mol), Lys376 (−11.2861± 0.5054 kJ/mol), Cys451 (−6.6857 ± 0.1919 kJ/mol), Arg455 (−8.3875 ± 0.6062 kJ/mol), and Gln488 (−7.4301 ± 0.4431 kJ/mol) contributed favorably to ZINC000042890265’s binding, while Glu396 (10.1660 ± 0.7664 kJ/mol) and Glu485 (11.4984 ± 0.5526 kJ/mol) contributed positive energy values above the +5 kJ/mol threshold (Figure S4a). Other residues worth mentioning include Arg349 (−4.340 ± 0.1412 kJ/mol), Arg481 (−3.4924 ± 0.1009 kJ/mol), Ser486 (−3.1868 ± 0.1074 kJ/mol), Gly487 (4.1502 ± 0.2038 kJ/mol), Arg510 (−3.3549± 0.1858 kJ/mol), Glu588 (4.2705± 0.1095 kJ/mol), Pro592 (−4.6041 ± 0.3091 kJ/mol), and Lys594 (−3.8252 ± 0.7079 kJ/mol). For the ADAR2–ZINC000039183320 complex, only Phe457 contributed energy above the threshold with a value of −8.1866 ± 0.6182 kJ/mol (Figure S4b). For ADAR2–ZINC000101100339, Cys377 (−5.7736 ± 0.2787 kJ/mol) and Arg510 (−6.4314 ± 0.1461 kJ/mol) contributed significantly to ZINC000101100339 binding in the RNA binding loop (Figure S4c). For the ADAR2–ZINC000014637370 complex, Cys377 (−5.4945 ± 0.2346 kJ/mol), Arg455 (−8.5618 ± 0.3376 kJ/mol), Ser486 (−6.6641 ± 0.1840 kJ/mol), Gln488 (−13.2511 ± 0.4194 kJ/mol), and Gly489 (−5.1627 ± 0.2240 kJ/mol) contributed favorable energies, while Glu396 (6.0735 ± 0.7359 kJ/mol) was unfavorable for ligand binding (Figure S4g). For ADAR2– ZINC000085593577, Lys350 (−5.6598 ± 0.2957 kJ/mol), Cys451 (−5.2814 ± 0.1461 kJ/mol), Arg455 (−7.2607 ± 0.3821 kJ/mol), and Leu511 (−5.8458 ± 0.2051 kJ/mol) contributed favorably, while Glu396 (9.5031 ± 1.2550 kJ/mol) contributed unfavorable energy to ZINC000085593577 binding (Figure S4d). For ADAR2–ZINC000085532375 (Figure S4e) and ADAR2-8-azanebularine (Figure S4f) complexes, several residues contributed significant energies due to the dynamic nature of the ligand binding process. During the course of the 100 ns MD simulation, 8-azanebularine and ZINC000085532375 exhibited mobility and explored different binding cavities of ADAR2. This movement led to interactions with multiple residues at different stages of the simulation, resulting in varying energy contributions. For the ADAR2-8-azanebularine complex, a total of 38 residues contributed favorable energies while 52 residues con- tributed energies above +5 kJ/mol. For the ADAR2–ZINC000085532375 complex, a total of 39 ADAR2 residues contributed energies below −5 kJ/mol, while 52 residues contributed above +5 kJ/mol. The instability of 8-azanebularine in the RNA binding site and binding site hopping could be responsible for its weak IC50 value previously reported [52]. 2.8. Re-Docking of Top Compounds against the 5-HT2C Receptor Since the aberrant ADAR2 editing of the 5-HT2C receptor causes major depressive disorder (MDD), suicidal behavior, anxiety disorders, and schizophrenia, this study sought to screen the top compounds against the 5-HT2CR to determine their potential binding affinities. All the compounds were observed to firmly dock in the ritanserin binding site. Ritanserin had a binding energy of −12.7 kcal/mol, the same as previously re- ported [50]. The least binding energy was observed for ZINC000095913861 (−12.9 kcal/mol) (Table 4), the same compound with the least binding energy to ADAR2 (−12.0 kcal/mol) (Table 1). ZINC000014637370, which demonstrated the strongest binding to ADAR2 (−174.911 kJ/mol) from the MM/PBSA calculations, was observed to have a binding Int. J. Mol. Sci. 2023, 24, 12612 20 of 31 energy of −10.9 kcal/mol. ZINC000085593577, which had a binding free energy of −137.369 kJ/mol with ADAR2, had a binding energy of −11.4 kcal/mol with 5-HT2CR. Experimental testing is required to determine the potential polypharmacologic activities against ADAR2 and 5HT2CR. Table 4. Binding energies of top compounds and ritanserin after docking against 5-HT2CR. The interacting residues, as well as the hydrogen bond lengths, are also provided. Interacting Residues Compound Binding Energy Hydrogen Bonds (Å) Hydrophobic Bonds Ser110, Tyr118, Val135, Ser138, Thr139, Ile142, Ritanserin −12.7 Asp134 (2.82) and Tyr358 (2.93) Val208, Ser219, Ala222, Phe223, Trp324, Phe327, Phe328, Asn351, and Val354 Tyr118, Asp134, Ser138, Val208, Leu209, ZINC000095913861 −12.9 - Val215, Ser219, Ala222, Phe223, Phe327, Phe328, Asn331, Asn351, Val354, and Tyr358 Asp134, Ser138, Leu209, Phe214, Val215, ZINC000101100339 −12.5 - Gly218, Ser219, Ala222, Phe223, Trp324, Phe327, Phe328, and Val354 Ser110 (2.82), Leu209 (2.81), Ile114, Tyr118, Ile131, Asp134, Val135, ZINC000085996580 −12.1 Ala222 (2.85), Asn331 (3.00), and Thr139, Ile142, Val208, Phe223, Trp324, Asn351 (2.78) Phe327, Phe328, Leu350, and Val354, Ser110, Tyr118, Trp130, Val135, Ser138, ZINC000085593577 −11.4 Asp134 (3.00, 3.06, and 3.07) andAsn331 (3.21) Leu209, Phe214, Val215, Ser219, Trp324,Phe327, Phe328, Val354, and Tyr358 Asp134, Val135, Ser138, Val208, Leu209, ZINC000085532375 −11.2 Asn331 (3.06) Val215, Gly218, Ser219, Ala222, Phe223, Phe327, Phe328, Leu350, Asn351, and Val354 Asp134, Val135, Val208, Leu209, Val215, ZINC000014637370 −10.9 - Trp324, Phe327, Phe328, Asn331, Leu350, Asn351, and Val354 Thr139 (2.83), Leu209 (2.92), and Asp134, Val135, Ser138, Val208, Val215,ZINC000039183320 −10.3 Asn331 (3.30) Phe327, Phe328, Glu347, Leu350, Asn351,and Val354 ZINC000070454467 −8.4 Leu209 (3.01) Asp134, Val135, Val208, Trp324, Phe327,Phe328, Asn331, Leu350, and Val354 Trp130, Asp134, Val135, Ser138, Leu209, ZINC000042890265 −7.8 Val215 (2.75) and Ser219 (2.52) Phe214, Phe223, Trp324, Phe327, Phe328, Asn331, Leu350, and Val354 2.9. Provenance of Potential Lead Compounds Various databases, including ZINC15 [133], PubChem [134,135], ChEMBL [136–138], and LOTUS [139], as well as existing literature, were searched to identify the sources of the five potential lead compounds. The existing literature was also investigated for the pharmacological activities of the plant sources. Structures of the shortlisted compounds and known inhibitors used in this study are provided (Figure 7). Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 23 of 34 2.9. Provenance of Potential Lead Compounds Various databases, including ZINC15 [133], PubChem [134,135], ChEMBL [136–138], and LOTUS [139], as well as existing literature, were searched to identify the sources of the five potential lead compounds. The existing literature was also investigated for the Int. J. Mol. Sci. 2023, 24, 12612 21 of 31 pharmacological activities of the plant sources. Structures of the shortlisted compounds and known inhibitors used in this study are provided (Figure 7). FFiiggurree 77. .TwTow-doi-mdeimnseinosniaoln satrluscttruurcetsu oref sthoef knthoewnk ninohwibnitoinrhs iubsietodr sin uthseisd stiundyth ainsds tthued yshoanrtdlisttehde schomorptloisutendsc.o mpounds. ZZIINCC000000004422889900226655 ((ddiissuullffuurreettinin),),a anna auuroronneed dereirvivaatitvive,ec, acnanb ebefo fuonudndin inC oCtointiunsucso cgoggy-- ggyrigari(ak n(konwonwans a“ss “msmokoeketr teree”e)”[)1 [4104,01,4114]1.].D Disiusulflufureretitnind deemmoonnssttrraatteedd ssttrroonngg aannttiiooxxiiddaattiivvee aaccttiivviittyy iinn aa 22,,22--ddiipphheennyyll--11--ppiiccrryyllhhyyddrraazzyyll ((DDPPPPHH)) aassssaayy wwiitthh aann IICC5500 ooff 99..77 µμgg//mmLL [[114400]].. TThhee eetthhyyll aacceettaattee ((EEttOOAAcc)) aanndd eetthhyyll aallccoohhooll ((EEttOOHH)) eexxttrraaccttss ooff CC.. ccooggggyyggrriiaa hhaavvee aallssoo bbeeiinngg rreeppoorrtteedd ttoo ppoosssseessss ssttrroonngg aannttiiooxxiiddaattiivvee pprrooppeerrttiieess [[114400,,114411]].. FFuurrtthheerrmmoorree,, CC.. ccooggggyyggrriiaa eexxttrraaccttss hhaavvee ddeemmoonnssttrraatteedd ccyyttoottooxxiicc aaccttiivviittieiessa aggaaininssttg gliloiobblalasstotommaac ecelllsl,s,H Hepep-G-G2,2M, MCCF-F7-, A7,5 A495,4a9n, adnHdC HTC11T611w6i twhiItCh 5I0Cva vluaeluseosf o4f5 .4658.6±8 ±2 .22.62,66, 56.54.74±7 ±2 2.450 .488, ,4 488.2.233± ± 22..3300,, 3322..4400 ±± 22..0022,, aanndd 3333..1133 ±± 22..0033 μµgg//mmLL, ,rreessppeecctitviveelyly [[114411]]. .TThhisis mmaakkeess ZZIINNCC000000004422889900226655 aann iinntteerreessttiinngg ccaannddiiddaattee ttoo tteesstt ffoorr iittss ppootteennttiiaall aannttii--ccaanncceerr aaccttiivviittyy aaggaaiinnsstt bbrraaiinn ccaanncceerr,, hheeppaattoocceelllluullaarr ccaarrcciinnoommaa,, bbrreeaasstt ccaanncceerr,, hhuummaann nnoonn--ssmmaallll cceellll lluunngg ccaanncceerr,, aanndd hhuummaann ccoolloorreeccttaall ccaarrccii-- noma. The anti-inflammatory, anti-microbial, hepatoprotective, and antidiabetic activity of noma. The anti-inflammatory, anti-microbial, hepatoprotective, and antidiabetic activity C. coggygria have been highlighted in the literature [142–144]. ZINC000039183320 (neoca- of C. coggygria have been highlighted in the literature [142–144]. ZINC000039183320 (neo- lyxin A), a diarylheptanoid derivative, is also found in the seeds of Alpinia blepharocalyx and calyxin A), a diarylheptanoid derivative, is also found in the seeds of Alpinia blepharocalyx A. roxburghii [145–147]. EtOH extracts of the seeds of A. blepharocalyx possess antiprolifera- and A. roxburghii [145–147]. EtOH extracts of the seeds of A. blepharocalyx possess antipro- tive activity against both human HT-1080 fibrosarcoma and murine colon 26-L5 carcinoma liferative activity against both human HT-1080 fibrosarcoma and murine colon 26-L5 car- cells, with neocalyxin A showing ED50 values 10.7 and >100 µM against the two cell lines, rceinspomecati vceelllys,[ 1w4i5th]. nHeoocwaelyvxeirn, nAe oshcaolwyxining AEDd5e0 mvaolnusetsr a1t0e.d7 a4n3%d >in10h0ib μitMio nagoafinthset tmheu rtwinoe ccoelllo lnin2e6s-,L r5escpareccitnivoemlya [c1e4ll5s].a Ht 5o0wevµg/emr, Lne[o14ca5l]y. xin A demonstrated 43% inhibition of the muriCneo mcoploonu n26d-LZ5I NcaCrc0i0n0o1m01a1 c0e0l3ls3 9at( 5q0in μggd/aminLo [n1e4)5]c.a n be found in Isatis tinctoria, also knowCnoamspboaunnladn gZeInN(CB0L0G01)0[114108]0.3B3L9 G(qiisnugsdeadinionnter)a dciatnio nbael fCohuinnde sienm Iseadtiisc itniencttoorpiare, vaelsnot aknndowtrne aats rbeasnpliarnatgoerny (vBiLruGs) i[n1f4e8c]t. iBonLsGs ius cuhseads iinn fltruaedniztiaon[1a4l 9C,1h5i0n]e.seE xmtreadcitcsinoef tIo. tpinrecvtoerniat hanadve trsehaot wrenspstirroatnogrya nvtiir-uins flinamfecmtiaotnosr ysuacchti vaist yin[fl1u51e,n1z5a2 ][.14A9l,s1o5,0]t.h Eexhtyradcrtos aolcf oIh. otilnicctloeraiaf ehxatvrea csthoofwI.nt isntcrtoonriga awnatsi-sinhflowamnmtoaptoorsys eascstiavnittiy- d[1e5p1re,1s5s2iv].e Aplrsoop, etrhteie hsyadnrdocaalcnorheodluicc elesatfr eesxs-- itnradcut coefd I.b teinhcatvoiroiar awl adsi ssohrodwerns tion pmoiscsee[s1s5 a3n],tim-daekpirnegssqiivneg pdraoinpoernteieasn ainndte craenst rinedguccaen dstirdeastse- tinodtuesctedfo brehitasvnioeruarlo dpirsootredcetirvs einp mroipcee r[t1i5e3s]., mNaokisnogu rqciengindfaoinrmonaeti aonn iwntaesrefsotiunngd cafonrdicdoamte- pounds ZINC000014637370 (PubChem CID: 163005156) and ZINC000085593577 (PubChem CID: 162813068). Int. J. Mol. Sci. 2023, 24, 12612 22 of 31 3. Materials and Methods 3.1. Protein and Ligands Preparation The hADAR2 structure (PDB ID: 5ed2) was obtained from the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank [154,155]. This structure consists of a mutant E488Q of the hADAR2 deaminase domain complexed with inositol hexakisphos- phate (IHP) and a double-stranded ribonucleic acid (dsRNA) [35]. To prepare the structure for molecular docking, the dsRNA, IHP ligand, and zinc atoms bound to the hADAR2 protein were removed using PyMOL (version 2.3.0). The resulting structure was processed using the Protein Preparation Wizard in Maestro (Schrödinger, LLC, New York, NY, USA) and optimized using the OPLS4 force field to address any steric hindrance and optimize protein energies [156]. For the screening of potential ligands, a total of 35,161 natural products from the Traditional Chinese Medicine (TCM) database were obtained from TCM@Taiwan, which is the largest non-commercial TCM database and a catalog of the ZINC15 database [133,157]. The compounds were pre-filtered based on molecular weight using OSIRIS DataWarrior 5.5.0 [55], similar to previous studies [130,158]. Compounds with molecular weights below 150 g/mol or above 600 g/mol were excluded, resulting in a final set of 25,196 compounds within the specified range. 8-azanebularine was extracted from PubChem with CID 10106291 and was used as a standard or control in the study. 3.2. Molecular Docking Studies AutoDock Vina embedded in PyRx version 0.9.2 was used for the molecular dock- ing process. The TCM compounds and the known inhibitor were virtually screened against the ADAR2 protein targeting the RNA binding site using grid box dimensions of 27.319 × 30.006 × 33.189 Å3 and the protein centered at x = 18.670 Å, y = 38.261 Å, and z = 77.541 Å. Prior to molecular docking, ligand structures in structure-data file (sdf) format were subjected to energy minimization using the UFF force field and 25,189 compounds were successfully converted to AutoDock’s Protein Data Bank, Partial Charge, and Atom Type (PDBQT) format. An exhaustiveness of 8 was set for the molecular docking process. After docking, the pose with the lowest binding energy (highest binding affinity) was selected for each compound since AutoDock Vina generates up to nine conformations for each ligand. The docking results were analyzed and ligands with binding energies below −9.5 kcal/mol were selected for further analysis. 3.3. ADMET Profiling The ADMET profiles of top compounds with favorable binding energies were pre- dicted using SwissADME [159]. The SMILES format of each compound was used as inputs for SwissADME. Lipinski and Veber’s rules were used as filters to shortlist compounds with relatively safe ADME profiles. While Lipinski’s rule allows up to one violation of the four criteria, Veber’s rule requires that compounds with good oral bioavailability should not violate any of the two criteria. For a compound to pass Veber’s rule, it should not have more than ten rotatable bonds and its topological polar surface area (TPSA) should not exceed 140 Å2 [160]. Lipinski’s rule of five expects safe drugs to have not more than 5 hydrogen bond donors; less than 10 hydrogen bond acceptors; molecular mass should not exceed 500 Da; and an octanol–water partition coefficient (logP) not more than 5 [161,162]. OSIRIS DataWarrior 5.5.0 was also employed to predict toxicity risks of the shortlisted compounds [55]. DataWarrior was used to evaluate the mutagenic, tumorigenic, repro- ductive effect, and irritant risks of compounds. After uploading the sdf format of the top compounds into DataWarrior, the “Chemistry” tab, “From Chemical Structure”, and then “Calculate Properties” were selected. Under the “LE, Tox, Shape” tab, “Mutagenic”, “Tumorigenic”, “Reproductive Effects”, and “Irritant” were selected in order to predict the toxicity risks. Int. J. Mol. Sci. 2023, 24, 12612 23 of 31 3.4. Visualizing ADAR2–Ligand Interactions The ADAR2–ligand interaction profiles involving the top compounds were deter- mined using LigPlot+, a widely used tool for visualizing and analyzing protein–ligand interactions [163]. Each ADAR2–ligand complex was uploaded, and under the “LIGPLOT” tab the ligand was selected prior to clicking the “Run” button. LigPlot+ generates 2D schematic diagrams that depict the specific hydrogen bonds and hydrophobic interactions between the protein and ligand. The LigPlot+ analysis provides valuable insights into the binding mode and binding interactions between the protein and ligand, aiding in the interpretation of their functional significance. 3.5. Biological Activity Prediction of Shortlisted Compounds The prediction of activity spectra of substances (PASS) was used to predict the likely pharmacological activity of shortlisted compounds (available at http://www.way2drug. com/passonline/predict.php, accessed on 23 May 2023) [47,48,60]. PASS utilizes structural information and statistical analysis to estimate the biological activity profiles of substances. By analyzing the chemical structure and physicochemical properties of the compounds, PASS generates predictions regarding their potential activities across a wide range of pharmacological targets and therapeutic areas. These predictions provide valuable insights into the possible biological activities of the compounds, enabling the identification and prioritization of promising candidates for further experimental validation. The SMILES format of the compounds was used as inputs for the activity prediction. The “Pa > Pi” filter was selected to only display results that had a probability of activity greater than the probability of inactivity. 3.6. Molecular Dynamics Simulations Study GROningen MAchine for Chemical Simulations (GROMACS) version 5.1.5 was em- ployed for molecular dynamics (MD) simulations of the unbound ADAR2 protein and selected ADAR2–ligand complexes [164,165]. The ligand topologies of the compounds were generated using LigParGen [166] for the OPLS force field. To solvate each ADAR2–ligand complex, a cubic box was employed, and the “TIP4P” water model and the OPLS/AA force field were utilized [167,168]. In order to neutralize the system charges, sodium or chlorine ions were added to the solvated complexes. The systems underwent initial equilibration in the constant number, constant-volume, and constant-temperature (NVT) ensemble, as well as in the isothermal-isobaric or constant number, constant-pressure, and constant- temperature (NPT) ensemble before the 100 ns MD simulation. After the MD simulations, the root mean square deviation (RMSD), radius of gyration (Rg), and root mean square fluctuation (RMSF) of each system were analyzed. Additionally, the hydrogen bond count was monitored throughout the simulation for each system. Snapshots of each complex were generated at 25 ns intervals (time step = 0, 25, 50, 75, and 100 ns). 3.7. Molecular Mechanics Poisson-Boltzmann Surface Area Calculation After MD simulations, the resulting complexes were subjected to MM/PBSA calcula- tions to determine the energy terms (vdW, electrostatic, polar solvation, SASA, and binding free energies) using the g_mmpbsa tool [122]. The MM/PBSA calculations were performed using the complete 100 ns simulation trajectories which have time steps of 1 ns. Also, the energy contribution of each ADAR2 residue was calculated for each of the ADAR2–ligand complexes. The decomposition of the free energy at the per-residue level helps to identify key residues, contributing significantly to the overall binding affinity. 3.8. Re-Docking Hit Compounds against the 5-HT2CR The top compounds were virtually against the 5-HT2CR structure (PDB ID: 6BQH) [169] using AutoDock Vina embedded in PyRx. Ritanserin, which was bound to the 6BQH struc- ture [169], was extracted and used as the control. Amino acid residues, which are in contact with ritanserin after visualizing the 5-HT2CR-ritanserin interaction map (Trp130, Asp134, Int. J. Mol. Sci. 2023, 24, 12612 24 of 31 Val135, Ser138, Thr139, Ile142, Phe320, Trp324, Phe327, Phe328, Leu350, Asn351, Val354, and Tyr358), were selected via PyRx, and the docking grid box was set to cover these residues. The grid box had dimensions of 23.8457393391 × 21.0061927432 × 22.651986164 Å3, and the protein was centered at x = 37.2017597536 Å, y = 29.7121195973 Å, and z = 53.165999618 Å. 4. Conclusions Although aberrant ADAR2 editing is implicated in several disorders, including neuro- logical disorders, cancers, viral infections, alcoholism, metabolic disorders, and inflamma- tory disorders, very few attempts have been made to identify small molecule inhibitors targeting the ADAR2. This study employed molecular docking and dynamics simulations to shortlist compounds from a total of 35,161 traditional Chinese medicine by targeting the RNA binding loop of the ADAR2 protein. Shortlisted compounds were further sub- jected to MD simulations and MM/PBSA calculations, and they demonstrated higher binding affinity to ADAR2 than the control, 8-azanebularine. By decomposing the over- all binding free energy into individual residue contributions, residues Lys350, Cys377, Glu396, Cys451, Arg455, Ser486, Gln488, and Arg510 were identified as key residues that play critical roles in stabilizing the protein–ligand complexes. The observed interac- tions and energy contributions provide valuable insights into the molecular mechanisms governing ligand recognition and binding. The findings reported herein will pave the way for further investigations and rational design of novel ligands targeting the RNA binding loop of the hADAR2 protein. A total of five potential ADAR2 inhibitors compris- ing ZINC000042890265, ZINC000039183320, ZINC000101100339, ZINC000014637370, and ZINC000085593577 were identified in this study. Safety and toxicity predictions also sug- gested that the compounds possess insignificant toxicities. Re-docking the top compounds against the serotonin 2C receptor also showed that they possess remarkably strong binding affinity to 5-HT2CR in the same binding site as ritanserin, a known 5-HT2CR inhibitor. This additional finding indicates that the potential versatility of the identified potential com- pounds as multi-target agents, capable of treating diseases associated with aberrant RNA editing as well as serotonin receptor-related disorders. The significance of this study lies in the identification of novel compounds from traditional Chinese medicine library, offering new possibilities for treating a wide range of disorders, including neurological disorders, cancers, viral infections, alcoholism, metabolic disorders, and inflammatory disorders, all of which are linked to aberrant RNA editing. The insights gained from this research will pave the way for further experimental validations and investigations in vitro and in vivo to confirm the efficacy and safety of the potential ADAR2 inhibitors. The findings represent a significant step forward in the field of drug discovery targeting ADAR2, and the potential therapeutic benefits of these compounds warrant further exploration. Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijms241612612/s1. Author Contributions: W.A.M.III and E.B. conceptualized the project. 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