Dr. Devvret Verma is a prolific researcher and academician who has made significant contributions in the fields of biotechnology, bioinformatics, and drug discovery. He has authored and co-authored several research papers in reputable scientific journals and has participated in various conferences and symposiums. His work focuses on utilising computational approaches to explore and understand the complex interactions between microorganisms, plants, and human pathogens.
One of his notable research areas is the study of host-pathogen interactions between Mycobacterium tuberculosis and humans. In his paper, he has presented a comprehensive database focusing on the interactions between hosts and various strains of Mycobacterium tuberculosis (Mtb). This research database, known as Mtb-HID, serves as a valuable resource for studying the complex interactions between the host immune system and Mtb, facilitating a better understanding of tuberculosis pathogenesis. By consolidating information on host-pathogen interactions across different MTB strains, the database provides insights into the mechanisms underlying tuberculosis infection, disease progression, and potential therapeutic targets. The publication of this work in the renowned journal “Current Science” and its inclusion in the SCI index demonstrate its significance in the scientific community. Another significant contribution by Dr. Devvret is in the field of drug discovery and repurposing. He has employed computational techniques to identify potential anti-tubercular compounds present in Indian plants and has conducted in-silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction of phytochemicals. This research, published in the AIP Conference Proceedings, aims to discover new drugs or repurpose existing compounds for the treatment of tuberculosis.
Dr. Devvret has also made contributions to the fight against the COVID-19 pandemic. His paper “Computational-guided approach for drug repurposing against SARS-CoV-2” in Future Virology explores computational methods to identify potential drug candidates for repurposing against the virus. Additionally, his work on molecular docking and simulation studies of natural compounds of Vitex negundo against SARS-CoV-2’s papain-like protease demonstrates his dedication to finding solutions to global health challenges.
Apart from his research, he has co-authored papers that cover diverse topics, such as the relationship between tobacco smoking and liver cancer risk and the development of a unified database of host-pathogen interactions for different strains of Mycobacterium tuberculosis. His expertise extends to in-silico analysis, homology modelling, and the use of neural networks for disease detection.
Overall, his work reflects his passion for applying computational and bioinformatics approaches to advance our understanding of microbial biology, drug discovery, and disease mechanisms. His research contributions have the potential to make a significant impact on various fields, ranging from agriculture to infectious diseases.
