Hemant Nagar
Exploring Biology 🧬 Through Computation 💻 & AI 🧠
PhD candidate with 5+ years' experience performing fully atomistic molecular dynamics simulations to study molecular modelling, protein-protein and protein-ligand interactions. Strong background in protein design, LLMs, computational chemistry and biophysics. Proficient in Python programming, training AI models using PyTorch and data mining.
Computational Biophysicist & AI Researcher
Bridging the gap between computational methods and biological discovery through innovative AI-driven approaches.
Research Focus
Drug Design
Molecular Simulations
Computational Biophysics
Rare Event Simulations
Small Molecule Design
Generative AI
Experience
Development of an Antibody Design Pipeline for Humanness and Humanization
Jan-June 2024
Project Details
Education
PhD in Chemical and Biomolecular Engineering
Ohio University • 2021-Current
BS-MS in Chemical Engineering
IIT Kanpur • 2015-2020
Technical Skills
Research Projects
Selected projects from my research work
Investigating the adsorption behavior of microcystin-LR on various surfaces using molecular dynamics simulations and experimental validation for water treatment applications.
Using deep learning to design novel therapeutic antibodies.
Identifying druggable hotspots on IRF3 protein surface using MixMD cosolvent simulations with drug-like fragments for targeted therapeutic development.
Designing human growth hormone variants to modulate receptor interactions through computational alanine scanning and molecular docking studies for therapeutic applications.
Open Source Contributions
Advancing computational biology through open-source machine learning models and tools
Comprehensive benchmarking framework for evaluating generative AI models in computational antibody discovery and design.
Advanced language model for antibody humanization, transforming non-human antibodies into human-compatible sequences.
Advanced fill-mask model trained on antibody sequences for predicting missing residues and sequence completion.
Specialized RoBERTa model trained on human antibody heavy chain sequences for fill-mask tasks and sequence analysis.
Specialized RoBERTa model trained on human antibody light chain sequences for fill-mask tasks and sequence analysis.
Interactive web application for restoring missing residues in antibody heavy and light chain sequences using the Ablang2 model.
Research Publications
Selected peer-reviewed publications from my research work.
Authors: C. Chambers, H. Nagar, S. Sharma, M. Reza
Comprehensive study combining experimental and molecular simulation approaches to understand microcystin-LR adsorption mechanisms on pyrolyzed hydrochars.
Authors: H. Nagar, S. Sharma
Investigation of how surface functional groups influence microcystin-LR adsorption behavior on graphene surfaces through computational analysis.
Let's Collaborate
Interested in collaboration or have questions about my research? Feel free to reach out.
Contact Information
hn533621@ohio.edu