Member Listing – Gaurav Bhardwaj

Computational peptide design for targeted therapeutics

Peptides offer attractive opportunities for drug design as they combine the stability of traditional small-molecule therapeutics with the specificity and potency of larger antibody-based drugs. However, peptide drug discovery so far has mostly relied on a limited number of natural peptide scaffolds or screening of random combinatorial peptide libraries. Our lab focuses on developing computational and experimental methods for precisely designing peptides for targeting therapeutic proteins. Areas of focus in the lab include the design of new antibiotics, antivirals, and anti-cancer peptides. In parallel, we have also focused on developing design principles for peptides with enhanced cellular permeability, oral bioavailability, and blood-brain barrier traversal. More recently, we have focused on developing machine learning-based methods for generating peptides with diverse structures and functions.

Peptide design, Machine Learning, Drug Discovery

2014