Srirupa Chakraborty

Oligomannose Fc Glycans Reprogram the Energetic and Conformational Basis of CD16a Recognition

This study uses molecular dynamics simulations to show how oligomannose Fc glycans alter CD16a binding by changing energetic interactions and conformational dynamics.

Molecular Basis of Core Fucosylation-Dependent Modulation of IgG1-FcCD16a Binding

This study investigates how core fucosylation affects IgG1-FcCD16a binding through molecular dynamics simulations, revealing structural and dynamic changes that reduce ADCC.

Interpretable Antibody-Antigen Structural Interface Prediction via Adaptive Graph Learning and Cyclic Transfer

VASCIF predicts antibody-antigen interfaces using a structure-aware graph model, achieving state-of-the-art performance and revealing biophysically meaningful interaction patterns.

Decoding epitope immunodominance in HIV Env using cryoEM and machine learning

This study uses cryoEM and machine learning to predict and redirect immunodominant epitopes in HIV Env, showing improved vaccine antigen design.

Structural and immunological characterization of the H3 influenza hemagglutinin during antigenic drift

This study examines how glycan evolution in H3 hemagglutinin affects antigenicity and immunogenicity, showing reduced antibody binding and shifted immune response.

Cleaved vs. Uncleaved: How Furin Cleavage Reshapes the Conformational Landscape of SARS-CoV-2 Spike

This study compares cleaved and uncleaved SARS-CoV-2 Spike proteins using MD simulations, showing cleavage alters conformational dynamics and allosteric communication, potentially affecting receptor binding.

Allosteric Control and Glycan Shielding Adaptations in the SARS-CoV-2 Spike from Early to Peak Virulence

This study analyzes structural changes in the SARS-CoV-2 Spike protein between D614G and Delta variants using molecular dynamics simulations to identify allosteric and glycan shielding adaptations affecting virulence and immune evasion.

Unveiling Interaction Signatures Across Viral Pathogens through VASCO: Viral Antigen-Antibody Structural COmplex dataset

VASCO provides a curated dataset of viral antigen-antibody complexes to improve predictive modeling and immunogen design for antiviral therapeutics.

A Graph-Directed Approach for Creation of a Homology Modeling Library: Application to Venom Structure Prediction

The paper introduces a graph-based algorithm to generate a homology modeling library for venom structure prediction, expanding the conotoxin structure library by 300%.