Surya Sekaran
Ms. Sekaran is a PhD Scholar in the Department of Biotechnology. Her research is focused on the discovery and validation of novel therapeutic agents for breast cancer. She is currently working on the identification and evaluation of potential inhibitors for the 17-beta-hydroxysteroid dehydrogenase (17β-HSD) enzyme, a critical target in cancer treatment. Her work integrates both computational (in silico) and experimental (in vitro) methods, combining computational screening and inhibitor design with laboratory-based assays for validation. She is particularly interested in applying modern programming languages and high-performance computing to accelerate the drug discovery pipeline.
Session
Virtual Screening of phytocompounds in drug discovery has surged over the years. We present juDock, a ML-Driven dockerized Linux application built in Julia. juDock automates the pipeline from the preparation of ligands to the prediction of potential compounds for a specific protein integrating AutoDock Vina, RDKit and Scikit-Learn via PythonCall.jl and Genie.jl. Furthermore, juDock is an open source project attracting researchers to contribute using the established ML pipeline for various proteins.