DJ

Dr. Kalyanashis Jana

Research areas: Chemistry · Physical and Theoretical Chemistry · Crystallography and molecular interactions · Crystal structures of chemical compounds · Crystal Structures and Properties

ORCID iD 0000-0001-9792-8195
Follow

About

As a classically trained chemist turned computational biologist, I bridge the molecular world of biophysics with cutting-edge tools in data science and machine learning. With a Ph.D. in Computational Chemistry and several years of postdoctoral experience, I specialize in simulating biomolecular systems, designing novel proteins, and applying AI for drug discovery and protein engineering. My research has spanned ion channel conductance, transmembrane protein stability, active site reactivity, and ligand binding, employing molecular dynamics (MD), density functional theory (DFT), and hybrid QM/MM approaches. My combined expertise in chemistry and biology helps translate machine learning results into actionable insights for innovation, healthcare, and broader societal benefit.

Key Strengths:

MD simulations (GROMACS, NAMD, OpenMM) and small molecules force field development

AI/ML-driven pipeline creation for ligand design (scikit-learn, PyTorch)

Coding skills in Python, Bash, and Fortran (basis)

Interdisciplinary collaboration with experimental biologists and software engineers

Experienced in Rosetta, AlphaFold2, AutoDock, RDKit, and MODELLER.

Proficient in QM calculations, having hands-on experience with GAUSSIAN, ORCA, and GAMESS.

I’m passionate about using computation to answer biologically meaningful questions—especially in protein engineering, drug designing, and systems biology. I’m always eager to collaborate, innovate, and push boundaries in molecular science.

Employment

Employment history is unavailable.

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications

Publications are unavailable.