Computational Biophysics and Bioinformatics

Pitambar Poudel has received the BPS Travel Award 2026 to present his research at the Annual Meeting in San Francisco, CA

The Medical Biophysics graduate program got support from NSF to enable AI-assisted education. News

The lab was awarded NSF Collaborative Research grant 2025-2028, $174,976. News

Congratulations to Shamrat Paul on receining Maste

Congratulations to Shamrat Paul on his Master's graduation!

Dr. Shailesh Pandey was promoted to senior Researc

Dr. Shailesh K. Panday was promoted to Senior Research Scientist

Dr. Alexov was elected to the American Institute for Medical and Biological Engineering (AIMBE)

The lab was awarded R35GM151964 (MIRA) 2024-2029 of $1.9M.

Dr. Alexov was awarded University Research, Scholarship and Artistic Achievement Award (URSAAA)

Congratulations to Mahesh and Mihiri for graduating in 2022

Dr. Emil Alexov was named Wallace R. Roy Distinguished Professor. News.

Atomic-style Clemson Robot

Robot holding barnase-barstar complex.

Created by Brandon Campbell, ProNOI package developed by Nick Smith. Potential distribution calculated with parallelized DelPhi developed by Chuan Li. Movie created by Lin Li.

About the Lab

The research in the lab focuses on computational modeling of biological macromolecules and their assemblages as well as predicting biophysical quantities associated with them. One of the primary roles of the lab is to develop and maintain the popular software package DelPhi, which calculates electrostatic potentials and energies of systems comprised of biological macromolecules. We are also interested in modeling disease-causing missense mutations, pKa's of amino acids and nucleic groups, and pH-dependence of stability and binding.

Software & Servers See repositories at

DelPhi Webserver

Delphi webserver is an online interface for the popular Poisson-Boltzmann solver (Delphi) for calculating electrostatic energies and potential in biological macromolecules.

Delphi pKa

Delphi-PKA is a DelPhi-based C++ program which allows to predict pKa's for ionizable groups at given pH in proteins, RNA and DNA.

SAAMBE-3D

A structure–based methods for predicting protein–protein Binding Free Energy change due to Single Amino Acid Mutation (SAAMBE-3D).

SAAMBE-SEQ

A sequence–based methods for predicting protein–protein Binding Free Energy change due to Single Amino Acid Mutation (SAAMBE-SEQ).

SAAMBE-MEM

Predicting protein-protein binding free energy change due to single amino acid change in membrane proteins.

SAAFEC-SEQ

An online application for calculating folding free energy changes in proteins caused by missense mutations for provided protein sequence.

BION-2

BION-2 predicts the positions of non-specifically surface-bound ions utilizing the Gaussian-based treatment of ions within the framework of the modified Poisson–Boltzmann equation.

SAMPDI-3Dv2

SAMPDI-3Dv2 uses a machine learning algorithm with features as physico-chemical properties, structure of mutation site and protein-DNA interactions to predict the change of binding free energy.

PKAD - 2

PKAD - 2 contains experimentally measured pKa values for >1500 ionizable residues in wild type as well as mutant proteins.

PKAD-R

The PKAD-R database is carefully curated, redesigned and expanded (including 214 new (128 non-redundant) pKa entries from the literature) upon PKAD and PKAD-2.

People

Head of Lab