Featured in Stanford University's Top 2% Scientists List for 2023 and 2024. Pioneering researcher combining computational methods with medicinal chemistry to develop innovative therapeutic solutions.
Specialized in computational approaches to drug development, including repurposing existing compounds for novel therapeutic applications. Expert in identifying potential drug candidates through advanced in silico modeling techniques.
Applies genomics approaches to identify novel drug targets. Utilizes network pharmacology and systems biology to understand complex disease mechanisms and identify intervention points for therapeutic development.
Proficient in molecular docking, dynamic simulation, QSAR modeling, and pharmacophore development. Leverages R/Python programming for data mining and analysis of complex biological datasets to accelerate drug discovery.
Dr. Mujwar's interdisciplinary approach combines computational methods, medicinal chemistry, and biological validation to develop novel therapeutic agents. His work spans multiple disease areas with particular emphasis on cancer, infectious diseases, and neurological disorders.
Maulana Azad National Institute of Technology, Bhopal, India
Doctoral research focused on exploring riboswitches as pathogenic drug targets. Developed computational methods for designing molecules targeting bacterial riboswitches. Recipient of a prestigious Doctoral Fellowship funded by the Ministry of Human Resources Department, Government of India.
Progressed from Assistant Professor at GLA University to Associate Professor at Chitkara University, establishing himself as a leading researcher in computational drug design. Developed computational drug design laboratory facilities and mentored numerous graduate students.
Completed a three-month Postdoctoral Internship at the University of Lodz, Poland, gaining hands-on training in advanced cell culture techniques for the evaluation of novel anticancer drugs, expanding his expertise beyond computational methods.
Throughout his career, Dr. Mujwar has maintained a consistent focus on integrating computational approaches with experimental validation, building a strong foundation for translational research in drug discovery and development.
Dr. Mujwar has made significant contributions to the field of computational and medicinal chemistry through his innovative research approaches. His work spans multiple therapeutic areas, with particular focus on:
Conducted extensive research on anticancer mechanisms, including work on doxorubicin's multiple mechanisms of action and development of novel pyrazolo-tetrazolo-triazine sulfonamides with anticancer properties.
Contributed to the development of indene-derived hydrazides targeting acetylcholinesterase for Alzheimer's disease treatment, combining computational design with biological evaluation.
With over 75 publications in peer-reviewed journals and a cumulative impact factor exceeding 230, Dr. Mujwar has established himself as a prolific researcher. His work appears in prestigious journals including BBA-Reviews on Cancer, International Journal of Molecular Sciences, and Computers in Biology and Medicine.
Kciuk, M., Gielecińska, A., Mujwar, S., Kołat, D., et al. (2023). Doxorubicin—An Agent with Multiple Mechanisms of Anticancer Activity. Cells, 12(4), p.659. (IF: 7.666)
Gielecińska, A., Kciuk, M., Yahya, E.B., Ainane, T., Mujwar, S. and Kontek, R. (2023). Apoptosis, necroptosis, and pyroptosis as alternative cell death pathways induced by chemotherapeutic agents? Biochimica et Biophysica Acta (BBA)-Reviews on Cancer, p.189024. (IF: 11.2)
Kciuk, M., Mujwar, S., et al. (2022). Preparation of Novel Pyrazolo [4, 3-e] tetrazolo [1, 5-b][1, 2, 4] triazine Sulfonamides and Their Experimental and Computational Biological Studies. International Journal of Molecular Sciences, 23(11), 5892. (IF: 6.208)
Shinu, P., Sharma, M., Gupta, G.L., Mujwar, S., et al. (2022). Computational Design, Synthesis, and Pharmacological Evaluation of Naproxen-Guaiacol Chimera for Gastro-Sparing Anti-Inflammatory Response by Selective COX2 Inhibition. Molecules, 27(20), p.6905. (IF: 4.927)
Dr. Mujwar's publication record demonstrates his versatility as a researcher and his ability to apply computational methods to diverse therapeutic challenges. His work is characterized by a strong emphasis on translational potential and practical applications in drug discovery.
Dr. Mujwar's technical expertise encompasses both theoretical understanding and practical application of computational tools in drug discovery. His programming skills allow him to develop custom solutions for complex research problems, while his knowledge of medicinal chemistry principles ensures biological relevance of computational predictions.
Dr. Mujwar maintains active research collaborations with scientists across multiple countries, including Poland, Morocco, and the United States. These international partnerships have resulted in numerous high-impact publications and expanded the scope of his research.
Serves on the editorial boards of respected scientific journals including Acta Biochimica Polonica and Discover Molecules. In these roles, he contributes to maintaining scientific rigor and identifying cutting-edge research for publication.
Regularly reviews manuscripts for numerous international journals in the fields of computational chemistry, medicinal chemistry, and drug discovery, helping to ensure the quality and integrity of published research.
Dr. Mujwar's international engagement reflects his standing in the global scientific community. Through these collaborations and editorial responsibilities, he contributes to the advancement of scientific knowledge and facilitates the exchange of ideas across national boundaries.
Dr. Mujwar employs a comprehensive, multi-stage approach to drug discovery that integrates computational prediction with experimental validation:
Using genomics and network pharmacology approaches to identify and validate potential drug targets associated with specific diseases.
Applying molecular docking, virtual screening, and pharmacophore modeling to identify promising compounds from large chemical libraries.
Refining lead compounds through iterative computational modeling and structure-activity relationship studies to improve potency and selectivity.
Confirming computational predictions through laboratory testing, including cell culture experiments and biochemical assays to assess biological activity.
This integrated approach allows for more efficient drug discovery by focusing experimental resources on the most promising candidates identified through computational methods, accelerating the path from concept to potential therapeutic agent.
Named among Stanford University's Top 2% Scientists globally for consecutive 3 years (2023 ,2024 and 2025), recognizing his significant impact on the field of computational and medicinal chemistry.
Author of more than 75 peer-reviewed scientific publications in prestigious international journals, with a cumulative impact factor exceeding 230 and an h-index of 23.
Achieved an impressive h-index of 23, reflecting both the productivity and citation impact of his research contributions to the scientific community.
These recognitions highlight Dr. Mujwar's standing as a leading researcher in computational and medicinal chemistry, with significant contributions to advancing the field through innovative methodologies and impactful research outcomes.
Dr. Mujwar welcomes inquiries from potential collaborators, students, and industry partners interested in computational and medicinal chemistry research.
Email: [email protected]
Location: Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India
Phone: +91 9827813303
Connect with Dr. Mujwar on LinkedIn, ResearchGate, Google Scholar, and ORCID for the latest updates on his research and publications.
Dr. Somdutt Mujwar: Computational & Medicinal Chemistry Expert