Dr. Vibhu Jha

Biography

Dr Vibhu Jha is an Assistant Professor in Computational Drug Design at the Institute of Cancer Therapeutics, University of Bradford, UK. His research focuses on structure-based drug discovery, molecular modelling, artificial intelligence, and machine learning approaches to investigate protein–ligand and protein–protein interactions for the development of novel therapeutics, particularly in oncology.

Dr Jha obtained his B. Pharm. degree from Chhattisgarh Swami Vivekananda Technical University (CSVTU), India, and his M.S. Pharm. (Medicinal Chemistry) from the National Institute of Pharmaceutical Education and Research (NIPER), India. During his master's studies, he conducted research at the CSIR–Central Drug Research Institute (CDRI), Lucknow, on the design and synthesis of antidiabetic agents. Prior to his PhD, he served as a Junior Lecturer at ITM University, Gwalior.

He completed his PhD with Excellent Honours at the University of Pisa, Italy (2017–2021), where he employed molecular modelling and virtual screening approaches to identify novel anticancer compounds. During his doctoral studies, he also spent six months as a visiting researcher at the Institute of Cancer Therapeutics, gaining experience in medicinal chemistry and translational drug discovery.

Following his PhD, Dr Jha worked as a Research Scientist at the University of Dundee, UK, on structure-based design of antitubercular and antimalarial agents. He subsequently joined the University of Gothenburg, Sweden, as a postdoctoral researcher, where his work expanded into computational and theoretical biochemistry, biomolecular simulations, teaching, and student supervision.

Dr Jha has authored more than 25 peer-reviewed publications and maintains active international collaborations with research groups across the United Kingdom, Sweden, Spain, India, Italy, and Jordan. His current research interests span computational chemical biology, biomolecular simulations, AI-assisted therapeutic discovery, and mechanistic studies of disease-relevant biomolecular systems. He currently supervises /co-supervises PhD and Master's researchers and has been awarded Fellowship of the Higher Education Academy (FHEA) in recognition of his contributions to teaching and academic practice.

Research

My research lies at the interface of computational chemical biology, medicinal chemistry, and biochemistry, with a focus on understanding biomolecular interactions and accelerating therapeutic discovery. I employ a broad range of computational approaches, including molecular docking, virtual screening, molecular dynamics simulations, enhanced sampling methods, and binding free-energy analyses to investigate protein–ligand and protein–protein interactions, elucidate molecular mechanisms of disease, and support the rational design of novel therapeutics. These studies are complemented through close collaborations involving medicinal chemistry, biochemical characterization, and experimental validation.

Current research interests include:

• Cancer metabolism and enzyme-targeted therapeutics: Development of selective modulators of one-carbon metabolism enzymes and aldehyde dehydrogenase (ALDH) isoforms implicated in tumour progression, stemness, and therapeutic resistance.

• Signal transduction and kinase-targeted therapeutics: Structural and mechanistic studies of EGFR and Src family kinases and associated signalling networks involved in tumour progression, metastasis, and therapeutic resistance, alongside the discovery of small-molecule modulators targeting disease-relevant signalling pathways.

• Cytoskeleton-targeted drug discovery: Discovery and mechanistic characterization of novel tubulin-targeting agents and multi-target anticancer compounds through integrated computational, medicinal chemistry, and biochemical approaches.

• Neurodegenerative diseases and drug repurposing: Investigation of cholinergic signalling pathways, acetylcholinesterase modulation, and disease-associated biomolecular networks to identify novel therapeutic and repurposing opportunities for Alzheimer's disease and related disorders.

• Network and systems pharmacology: Integration of biological networks, multi-omics data, and artificial intelligence approaches to identify disease-associated pathways, uncover polypharmacological mechanisms, and support translational therapeutic discovery.

In parallel, I develop and apply AI and machine learning methodologies to enable virtual screening, molecular property prediction, hit prioritisation, drug repurposing, and rational therapeutic design across oncology and neurodegenerative disease research.

Research collaborator

• Prof. Raj Kumar (Department of Pharmaceutical Sciences and Natural Product, Central University of Punjab)
• Prof. Leif Eriksson (Department of Chemistry and Molecular Biology, University of Gothenburg)
• Prof. Tiziano Tuccinardi (Department of Pharmacy, University of Pisa)

Professional activities

Publications