Browsing by Author "Agyapong, O."
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Item Computer–Aided Approaches To Discovery Of Novel Drugs Against The Human Hookworm Necator Americanus (Nematoda: Ancylostomatidae)(University of Ghana, 2017-07) Agyapong, O.There is a crucial need to develop novel anthelminthic drugs due to the mounting disease burden and increasing evidence of hookworm resistance to drugs such as albendazole and mebendazole, which for decades have been used to treat the infection. Consequently, it is exigent to develop alternative drugs with improved therapeutic efficacy. Natural products due to their unique active ingredients have been shown to possess exceptional structures with chemical diversity that is unmatched by any synthetic libraries. It is imperative to leverage natural products to augment hookworm drug discovery. Therefore, this study aimed to: (i) identify potential novel anthelminthic lead compounds by screening African natural product-derived ligands against beta tubulin of Necator americanus, a known hookworm receptor and (ii) develop support vector machine-based proteochemometric modelling (PCM) for bioactivity profiling of beta tubulins receptors. The 3D structure of the beta tubulin of hookworm with UniProt entry W2T758, was generated using homology modelling. The model was subjected to molecular dynamics simulations and active site interactions prediction. The first set of ligand libraries comprising 885 natural product compounds obtained from African medicinal plants database (AfroDb) combined with Dichapetalin A, were screened against the receptor. ZINC14760755 and ZINC28462577 compounds were found to be potential leads due to promising binding affinity, active site interactions and pharmacokinetic profiles. Additionally, a second set comprising 2297 compounds derived from Northern African Natural Product Database (NANPDB) were virtually screened. The compound S,5Z,8Z,11Z,13E,17Z-15-hydroxy-1-(2,4,6-trihydroxyphenyl)-15-methylicosa-5,8,11,13,17-pentaen-1-one exhibited plausible binding affinity, toxicity and pharmacokinetic profile. The aforementioned natural compounds are potential leads which can be experimentally characterised for possible pre-clinical trials. Support vector machine based proteochemometric modelling was also developed to predict the bioactivity relations between beta tubulin variants and small compounds using an interaction dataset retrieved from BindingDB. The model achieved reasonably good performance with a ROC-AUC of 87%, an MCC of 0.75 and a classification error of approximately 4%, although it was trained on a small dataset. The model allows the prediction of the likelihood of interactions between query datasets comprising ligands in SMILES format and protein sequences of beta tubulin targets. In future, larger bioactive datasets of beta tubulins originating from high throughput experiments can be utilised to possibly enhance the performance of the hookworm PCM model.Item Development of a proteochemometric-based support vector machine model for predicting bioactive molecules of tubulin receptors(Springer, 2021) Agyapong, O.; Miller, W.A.; Wilson, M.D.; Kwofie, S.K.Microtubules are receiving enormous interest in drug discovery due to the important roles they play in cellular functions. Targeting tubulin polymerization presents an excellent opportunity for the development of anti-tubulin drugs. Drug resistance and high toxicity of currently used tubulin-binding agents have necessitated the pursuit of novel drug candidates with increased therapeutic potency. The design of novel drug candidates can be achieved using efficient computational techniques to support existing efforts. Proteochemometric (PCM) modeling is a computational technique that can be employed to elucidate the bioactivity relations between related targets and multiple ligands. We have developed a PCM-based Support Vector Machine (SVM) approach for predicting the bioactivity between tubulin receptors and small, drug-like molecules. The bioactivity datasets used for training the SVM algorithm were obtained from the Binding DB database. The SVM-based PCM model yielded a good overall predictive performance with an area under the curve (AUC) of 87%, Matthews correlation coefficient (MCC) of 72%, overall accuracy of 93%, and a classification error of 7%. The algorithm allows the prediction of the likelihood of new interactions based on confidence scores between the query datasets, comprising ligands in SMILES format and protein sequences of tubulin targets. The algorithm has been implemented as a web server known as TubPred, accessible via http://35.167.90.225:5000/.Item In silico screening of isocitrate lyase for novel anti-buruli ulcer natural products originating from Africa(Molecules, 2018-06) Kwofie, S.K.; Dankwa, B.; Odame, E.A.; Agamah, F.E.; Doe, L.P.A.; Teye, J.; Agyapong, O.; Miller, W.A.; Mosi, L.; Wilson, M.D.Buruli ulcer (BU) is caused by Mycobacterium ulcerans and is predominant in both tropical and subtropical regions. The neglected debilitating disease is characterized by chronic necrotizing skin lesions attributed to a mycolactone, which is a macrolide toxin secreted by M. ulcerans. The preferred treatment is surgical excision of the lesions followed by a prolonged combination antibiotic therapy using existing drugs such as rifampicin and streptomycin or clarithromycin. These antibiotics appear not to be adequately potent and efficacious against persistent and late stage ulcers. In addition, emerging drug resistance to treatment poses great challenges. There is a need to identify novel natural product-derived lead compounds, which are potent and efficacious for the treatment of Buruli ulcer. Natural products present a rich diversity of chemical compounds with proven activity against various infectious diseases, and therefore, are considered in this study. This study sought to computationally predict natural product-derived lead compounds with the potential to be developed further into potent drugs with better therapeutic efficacy than the existing anti-buruli ulcer compounds. The three-dimensional (3D) structure of Isocitrate lyase (ICL) of Mycobacterium ulcerans was generated using homology modeling and was further scrutinized with molecular dynamics simulations. A library consisting of 885 compounds retrieved from the AfroDb database was virtually screened against the validated ICL model using AutoDock Vina. AfroDb is a compendium of “drug-like” and structurally diverse 3D structures of natural products originating from different geographical regions in Africa. The molecular docking with the ICL model was validated by computing a Receiver Operating Characteristic (ROC) curve with a reasonably good Area Under the Curve (AUC) value of 0.89375. Twenty hit compounds, which docked firmly within the active site pocket of the ICL receptor, were assessed via in silico bioactivity and pharmacological profiling. The three compounds, which emerged as potential novel leads, comprise ZINC38143792 (Euscaphic acid), ZINC95485880, and ZINC95486305 with reasonable binding energies (high affinity) of −8.6, −8.6, and −8.8 kcal/mol, respectively. Euscaphic acid has been reported to show minimal inhibition against a drug-sensitive strain of M. tuberculosis. The other two leads were both predicted to possess dermatological activity while one was antibacterial. The leads have shown promising results pertaining to efficacy, toxicity, pharmacokinetic, and safety. These leads can be experimentally characterized to assess their anti-mycobacterial activity and their scaffolds may serve as rich skeletons for developing anti-buruli ulcer drugs. © 2018 by the authors.Item Structure-Based Identification of Natural-Product-Derived Compounds with Potential to Inhibit HIV-1 Entry(Molecules, 2023) Ugwu-Korie, N.; Quaye, O.; Wright, E.; Languon, S.; Agyapong, O.; Broni, E.; Gupta, Y.; Kempaiah, P.; Kwofie, S.K.Broadly neutralizing antibodies (bNAbs) are potent in neutralizing a wide range of HIV strains. VRC01 is a CD4-binding-site (CD4-bs) class of bNAbs that binds to the conserved CD4- binding region of HIV-1 envelope (env) protein. Natural products that mimic VRC01 bNAbs by interacting with the conserved CD4-binding regions may serve as a new generation of HIV-1 en try inhibitors by being broadly reactive and potently neutralizing. This study aimed to identify compounds that mimic VRC01 by interacting with the CD4-bs of HIV-1 gp120 and thereby inhibit ing viral entry into target cells. Libraries of purchasable natural products were virtually screened against clade A/E recombinant 93TH057 (PDB: 3NGB) and clade B (PDB ID: 3J70) HIV-1 env protein. Protein–ligand interaction profiling from molecular docking and dynamics simulations showed that the compounds had intermolecular hydrogen and hydrophobic interactions with conserved amino acid residues on the CD4-binding site of recombinant clade A/E and clade B HIV-1 gp120. Four potential lead compounds, NP-005114, NP-008297, NP-007422, and NP-007382, were used for cell-based antiviral infectivity inhibition assay using clade B (HXB2) env pseudotype virus (PV). The four compounds inhibited the entry of HIV HXB2 pseudotype viruses into target cells at 50% inhibitory concentrations (IC50) of 15.2 µM (9.7 µg/mL), 10.1 µM (7.5 µg/mL), 16.2 µM (12.7 µg/mL), and 21.6 µM (12.9 µg/mL), respectively. The interaction of these compounds with critical residues of the CD4-binding site of more than one clade of HIV gp120 and inhibition of HIV-1 entry into the target cell demonstrate the possibility of a new class of HIV entry inhibitors.