Markov State Models of protein-protein encounters

TL;DR

This paper reviews how combining molecular dynamics, experimental data, and Markov state models can elucidate the mechanisms of protein-protein interactions, including how they associate and dissociate.

Contribution

It introduces a comprehensive approach integrating simulations and experimental data through Markov state models to study protein-protein encounters.

Findings

Enhanced understanding of protein association mechanisms

Improved modeling of dissociation pathways

Framework for integrating diverse data sources

Abstract

This chapter reviews how molecular dynamics simulations, experimental data, and Markov state models can synergize to map-out the mechanism of protein-protein association and dissociation.