About
• Ms. Sudipta Nandi is a dedicated research scholar pursuing Ph.D. program in the Department of Biotechnology at the prestigious Indian Institute of Technology Madras (IIT Madras).
• Her research interests revolve around the intriguing realms of structure-based and ligand-based drug design, molecular modeling, in silico virtual screening, molecular dynamics simulations, and the application of machine learning and Monte Carlo techniques in drug discovery. She is particularly fascinated by virtual screening methodologies to repurpose existing small molecules in the market, contributing to the advancement of pharmaceutical sciences.
• She brings hands-on experience in organic synthesis and the design of small molecules and inhibitors, further enriching my research endeavors. Her academic journey is marked by a commitment to translating research findings into practical applications.
• Beyond her core research, she actively engages in scientific writing, mentorship programs, and developing academic research ideas into viable business models.
• She was awarded prestigious Prime Minister's Research Fellowship by Ministry of Human Resource Development (MHRD), Government of India in 2022.
Employment
Employment history is unavailable.
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (7)
- Rational Design of N-Alkylated Benzazepine Derivatives as Potential CETP Inhibitors Save
- Synthesis of Potential Lipophilic β-D-Thiogalactosides Towards LecA Inhibition Save
- Decoding Structural Fingerprints to Design and Elucidate the Mechanism of Action of Prospective Cholesteryl Ester Transfer Protein Drugs Save
- Convenient synthesis of O-alkylated/N-acylated polyhydroxyazepane based compounds for modulating MD-2-TLR4 complex formation Save
- A critical analysis of urea transporter B inhibitors: molecular fingerprints, pharmacophore features for the development of next-generation diuretics Save
- First molecular modelling report on tri-substituted pyrazolines as phosphodiesterase 5 (PDE5) inhibitors through classical and machine learning based multi-QSAR analysis Save
- Urea transporter and its specific and nonspecific inhibitors: State of the art and pharmacological perspective Save