Protein multi-scale organization through graph partitioning and robustness analysis: Application to the myosin-myosin light chain interaction

TL;DR

This paper presents a multi-scale graph partitioning method to analyze protein organization across scales, applied to myosin-myosin light chain interaction, revealing biological features and key residues.

Contribution

It introduces a novel multi-scale graph partitioning approach combined with robustness analysis to study protein structure and function across different scales.

Findings

Identified conserved clusters in myosin protein

Analyzed the closing mechanism of the protein

Pinpointed key residues for binding through mutational analysis

Abstract

Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding.