Jan Brezovský

The paper improves the binding efficiency and interaction stability of thermophilic cohesin-dockerin pairs on bacterial cell surfaces using computational and experimental methods.

The paper introduces geometry-based descriptors to predict enzyme-substrate interactions with high accuracy and interpretability, outperforming existing machine learning methods with minimal training data.

This paper identifies two distinct MUS81 inhibitors that enhance chemotherapy efficacy by impairing DNA repair in cancer cells.

This study investigates how different water models affect water molecule migration through enzyme tunnels, finding that TIP3P allows faster and greater transport compared to OPC and TIP4P-Ew.

The paper investigates how different water models affect the structure and dynamics of enzyme tunnels using molecular dynamics simulations of three haloalkane dehalogenase variants.

This study benchmarks coarse-grained simulation methods for analyzing enzyme transport tunnels, finding they efficiently capture tunnel geometry but vary in replicating all-atom dynamics.

This study uses Gaussian accelerated MD simulations to improve tunnel sampling in enzymes, revealing new transient tunnels and their functional relevance.

The paper integrates prior knowledge into initial seeds for adaptive sampling simulations to better model ligand transport in enzymes with buried active sites, improving consistency and predictive accuracy.

This study investigates water transport through narrow tunnels in three β-hydrolases using molecular dynamics simulations, revealing that sub-angstrom bottlenecks can facilitate transport with increased hydrogen bonding.

TransportTools enables efficient analysis of ligand transport pathways through voids in biomolecules using high-throughput molecular dynamics data.