Yasaman Karami

SIMORGH predicts ligand binding sites from apo proteins by integrating conformational ensembles, outperforming existing methods in ligand-free settings and identifying cryptic pockets.

This study identifies a structural trade-off in type IV pili that balances mechanical resilience and supramolecular adaptability using cryo-EM, simulations, and experimental validation.

This paper identifies a bias in allosteric site prediction benchmarks and introduces AlloDyn, a dynamic-aware framework that improves prediction performance by incorporating conformational dynamics.

The paper elucidates the structural basis of the two-photon photoactivation mechanism of orange carotenoid protein using a combination of structural and biochemical methods.

InterMap accelerates interaction fingerprint detection in large molecular ensembles, achieving significant reductions in runtime and memory usage compared to existing tools.

The paper introduces PROTEUS, a method to assess protein conformational plasticity using a generative model, showing it correlates with molecular dynamics data and identifies functionally plastic proteins.

DynamicGT improves protein binding interface prediction by incorporating dynamic features and conformational changes, outperforming static models on flexible and disordered regions.

DynaRepo provides a repository of macromolecular conformational dynamics with simulations and analyses for over 450 complexes and 270 proteins.

ppIRIS predicts bacterial protein-protein interactions using deep learning, achieving high accuracy and enabling proteome-wide screening, with applications in identifying virulence pathways and host-pathogen interactions.

The paper introduces ComPASS, a computational method to analyze communication networks in protein-nucleic acid complexes, revealing distinct signal transmission mechanisms across various systems.

This paper uses molecular dynamics simulations to analyze changes in the RBD/hACE2 interface across SARS-CoV-2 variants, identifying key residues and interactions that contribute to binding stability and variant persistence.

This paper introduces a novel MS score framework for analyzing polyclonal antibodies, demonstrating its ability to identify antibody subgroups and predict interactions.

The paper uses molecular dynamics simulations to analyze Spike-ACE2 binding across SARS-CoV-2 variants, revealing conformational changes and variant-specific binding differences.

This study investigates how oxidation of histone H3 cysteines affects nucleosome structure using molecular modeling, revealing mechanisms and structural consequences of S-sulfenylation.

The paper introduces a framework for rational head-to-tail peptide cyclization using protein structure data, demonstrating improved conformation prediction and successful application to Nrf2 and urotensin II peptides.

This study determines the structural interactions between Streptococcus pyogenes M1 protein and human IgG using integrative structural biology, revealing conserved mechanisms to inhibit phagocytosis.

This study develops a computational framework to quantify disorder in coiled-coils and design substitutions to modulate their stability and flexibility.

GEMME predicts mutational effects by modeling evolutionary history, outperforming existing methods in speed and accuracy for viral and conserved sequences.

This paper accelerates protein structure prediction using GPU-accelerated particle swarm optimization, achieving 34x speedup over CPU with acceptable precision.