Abstract:
Monkeypox virus (MPXV) is a re-emerging zoonotic orthopoxvirus that has become an important global public health concern following the 2022 multinational outbreak. The ongoing global outbreak, which started in 2022, has resulted in more than 100,000 cases across 122 countries, highlighting the urgent need for effective therapeutic interventions. To explore the broader chemical space of potential drug candidates, an AI-based generative model was first employed to design novel small-molecule compounds. This set was then complemented with additional ligands curated from medicinal plants. The physicochemical properties of all generated and curated ligands were computed to assess their drug-likeness and suitability for further evaluation. Next, an integrative network pharmacology approach was employed to explore the therapeutic mechanisms of all compounds against MPXV infection. We identified various overlapping genes between predicted compound targets and MPXV-associated genes via protein–protein interaction network and enrichment analysis. The complete ligand set was then subjected to molecular docking, molecular dynamics simulations, and binding free energy calculations to assess their stability in complex with the target receptor considered herein. Overall, this study combines an AI-driven approach with structure-based drug design to provide computational insights and identify potential drug-like molecules against MPXV.
Keywords: Monkeypox virus; network pharmacology; generative model, AI, molecular docking
Biography:
Jimoh Olayemi Balogun is an undergraduate Microbiology student at Lead City University, Ibadan, Nigeria, with an interest in bioinformatics, computational biology, drug discovery, and infectious diseases. My research experience involves immunoinformatics, Vaccine design, pathogen analysis, network pharmacology, molecular docking, and molecular dynamics simulations. I have presented my research at scientific conferences and received competitive opportunities in recognition of my interest in research. My current research interests include the application of artificial intelligence, network pharmacology, and molecular simulation techniques towards discovering potential drug-like molecules against the Monkeypox virus. I have a passion for using computational methods to solve novel challenges in infectious diseases.
