Ranjita Das Computational Chemist

About Ranjita Das Computational Chemist

Computational Chemist | Process R & DWith 15+ years of expertise in computational chemistry, I apply advanced modeling techniques to solve critical challenges in fundamental and industrial sciences. My experience spans pharma, food, personal care, and home care industries, with a current focus on Process R&D in pharmaceuticals.Core Competencies Catalyst & Ligand Optimization – Enhancing catalyst efficiency and selectivity using DFT to improve yields and reduce unwanted byproducts. Reaction Mechanism Studies – Gaining molecular-level insights into catalytic pathways to optimize reaction conditions and guide efficient catalyst design. Enzyme Engineering & Biocatalysis – Applying hybrid computational chemistry to refine enzyme activity, stability, and substrate specificity, driving sustainable drug discovery and production.Technical Expertise Computational Modeling – First-principles modeling, QM, DFT. Process & Formulation R&D – Integrating computational chemistry with experimental data to optimize reactions, improve yields, and scale processes. Software & Tools• Computational Chemistry – Orca, Gaussian, Terachem, DFTB+, XTB, Quantum Espresso, Gamess, ADF, NCIPLOT, Multiwfn, Autodock, Gromacs.• Molecular Modeling & Simulations – Chemcraft, GaussView, Avogadro, Chimera, VMD, ChemDraw, Modeller, MGLtools, Discovery Studio.• Cheminformatics & Data Analytics – RDKit, OpenBabel, Plotly, KNIME, scikit-learn. AI/ML-Assisted Descriptor Design – Supporting predictive modeling for enzyme function and catalytic efficiency by integrating ML-driven insights with computational chemistry.Industry Impact & CollaborationI bridge the gap between computational chemistry and industrial R&D, helping companies accelerate drug development, optimize enzyme-driven bioprocesses, and enhance API synthesis. I collaborate with cross-functional teams to integrate computational insights into decision-making, reducing costs and increasing efficiency.Future Directions & Research Interests AI/ML & Physics-Based Models – Expanding predictive capabilities for biocatalysis and process R&D.🧬 Advancing Biocatalysis – Developing sustainable solutions for drug synthesis. In Silico Formulation Design – Predicting key formulation properties computationally. Quantum Computing in Chemistry – Exploring next-gen computational approaches for complex molecular systems.I\'m open to discussing how computational chemistry can drive innovation in pharma and beyond. Let’s connect!#ComputationalChemistry #Biocatalysis #EnzymeEngineering #Pharma #ProcessR & D

Experience

1. Senior Scientist 1

   Aganitha

   Mar 2026 — Present

Education

• Indian Institute of Technology, Kharagpur

  Doctor of Philosophy - PhD, Computational Chemistry, Density Functional Theory

  2009 — 2014