Unnati Kushavah

Dr. Unnati Kushavah is an Assistant Professor in the Department of Biotechnology at Invertis University, Bareilly, with 5 years of research experience. She earned her Ph.D. from CSIR-Central Drug Research Institute (CSIR-CDRI), India, specialising in computational drug discovery, bioinformatics, and molecular modelling. Her doctoral research focused on computational and machine-learning approaches for identifying and designing therapeutic candidates targeting proteins associated with metabolic disorders, particularly type 2 diabetes.

Her research expertise includes molecular docking, molecular dynamics simulations, virtual screening, pharmacophore modelling, QSAR and 3D-QSAR, structure- and ligand-based drug design, de novo drug design, and computational biophysics. She has worked with platforms and software including Schrödinger Suite, SYBYL, Discovery Studio, AutoDock, MODELLER, VLife, Cresset, WEKA, and GROMACS, along with programming and data-analysis tools such as Python, R, Biopython, PERL, SQL, and RNA-seq data analysis.

Dr. Kushavah has teaching experience in microbiology, biotechnology, bioprocess engineering, molecular biology, plant physiology, and related life-science subjects. Her research interests include computer-aided drug discovery, artificial intelligence and machine learning in drug development, molecular simulation, protein–ligand interactions, metabolic diseases, and translational computational biology.

Her research has contributed to the identification and optimisation of potential therapeutic molecules against metabolically relevant targets, supported by experimental validation. She has authored and co-authored research publications and participated in multidisciplinary research projects involving metabolic proteins and therapeutic target discovery. She also contributes to academic content development, student mentoring, teaching, and interdisciplinary research.