Nandan
Kumar

Nandan Kumar
Kansas State University
Manhattan, Kansas, USA
Computational structural biology AI/ML for proteins Drug discovery Membrane modeling

I am a Postdoctoral Researcher and Lab Manager at Kansas State University, working at the interface of computational structural biology, bioinformatics, peptide science, and AI/ML. My research focuses on developing scalable, data-driven models to understand the structure, dynamics, and function of proteins and bioactive peptides. I integrate large-scale molecular simulations with advanced protein-language models and machine-learning approaches to uncover mechanistic insights into biomolecular interactions and behavior.

I enjoy thinking about how proteins and peptides behave across length and time scales, from quantum-level interactions and molecular dynamics simulations to data-driven models of sequence and structure. My research goal is to design and understand bioactive peptides, biologics, and complex protein assemblies using multiscale simulations, protein language models, and graph neural networks, and to translate these insights into improved therapeutics and practical biomolecular applications.

Recently, I have worked on:

  1. AI-driven peptide prediction and design – developing pLM4CPPs and pLM4G-CPPs that combine protein language models and graph learning for accurate prediction of cell-penetrating and antimicrobial peptides, with interpretable sequence–activity relationships.
  2. Multiscale simulations of proteins, membranes, and complex environments – using all-atom and coarse-grained MD to study gluten proteins, ovalbumin, heterogeneous lipid bilayers, and antifreeze proteins under ethanol, pressure, and processing conditions, linking structural dynamics to functionality and allergenicity.
  3. Open-source platforms for drug discovery and non-covalent interactions – contributing to the Molecular Property Diagnostic Suite (MPDS), A2ID, CAD, and fragment libraries to explore chemical space and quantify key non-covalent interactions in protein–ligand systems.

I did my Ph.D. in Computational Biology at CSIR-Indian Institute of Chemical Technology under the supervision of Prof. G. Narahari Sastry, where I worked on ion–molecule interactions, lipid membrane heterogeneity, and drug repurposing for infectious diseases. Before that, I completed an M.Sc. in Bioinformatics (Gold Medalist) at Central University of Bihar and a B.Sc. in Biotechnology at Magadh University. I have also contributed to the development of drug discovery portals and non-covalent interaction databases at CSIR-NEIST.

Research expertise

  • Computational structural biology & biomolecular dynamics – all-atom and coarse-grained MD of proteins, peptides, and membranes under environmental stresses (pressure, solvent, processing) to link conformational dynamics with function, stability, and allergenicity.
  • Protein & peptide structure–function prediction – multi-scale modeling of protein–protein, protein–ligand, and protein–membrane interactions, including QM/MM and enhanced-sampling approaches for binding and selectivity.
  • AI-driven bioinformatics & peptide design – development of predictive models using protein language models, graph neural networks, and classical ML for cell-penetrating, antimicrobial, and bioactive peptides.
  • Computational drug discovery & cheminformatics – virtual screening, drug repurposing, and fragment-based design; exploration of chemical space using MPDS, RDKit, and related tools for small-molecule optimization.
  • Membrane biophysics & biologics design – modeling lipid heterogeneity, peptide–bilayer interactions, and pore formation to guide the design of targeted biologics and membrane-active agents.
  • Software, databases & open platforms – co-development of web portals and databases (MPDS, A2ID, CAD) for non-covalent interactions and structure-based drug discovery, supporting academic and industrial users.

Recent news

  • 2025 Recipient of the Outstanding Post-Doctoral Research Associate Award at Kansas State University.
  • 2025 Four first-author papers published in J. Chem. Inf. Model., J. Phys. Chem. B, and Food Chemistry.
  • 2024–2025 Invited talks at Cereals & Grains 2024 and the Foods2024 electronic conference.
  • 2024 Released pLM4CPPs, a state-of-the-art protein language model–based predictor for cell-penetrating peptides.
  • 2023–2025 Reviewed 30+ manuscripts for journals including Food Chemistry, Int. J. Biol. Macromol., and various Frontiers series.

Research highlights

Selected publications

Full list of publications: Google Scholar.

Honors & awards

30+
PEER-
REVIEWED
PUBLICATIONS
7
BOOK
CHAPTERS
11
H-INDEX
(SCHOLAR)
375+
CITATIONS

Based on Google Scholar and Scopus metrics (updated 2025). View profile.