Monte Carlo sampling of flexible protein structures: an application to the SARS-CoV-2 omicron variant
Samuel W.K. Wong

TL;DR
This paper introduces a sequential Monte Carlo method to sample the full conformational space of flexible proteins, applied to the SARS-CoV-2 Omicron variant, revealing mutation impacts on structural flexibility relevant to binding.
Contribution
The paper presents a novel Monte Carlo sampling approach that explores the entire conformational space of proteins, unlike previous methods focusing only on lowest-energy structures.
Findings
Identified key mutation region 495-508 in Omicron affecting conformational flexibility.
Method successfully sampled diverse protein conformations consistent with known mutation effects.
Application demonstrated relevance to understanding variant-specific binding properties.
Abstract
Proteins can exhibit dynamic structural flexibility as they carry out their functions, especially in binding regions that interact with other molecules. For the key SARS-CoV-2 spike protein that facilitates COVID-19 infection, studies have previously identified several such highly flexible regions with therapeutic importance. However, protein structures available from the Protein Data Bank are presented as static snapshots that may not adequately depict this flexibility, and furthermore these cannot keep pace with new mutations and variants. In this paper we present a sequential Monte Carlo method for broadly sampling the 3-D conformational space of protein structure, according to the Boltzmann distribution of a given energy function. Our approach is distinct from previous sampling methods that focus on finding the lowest-energy conformation for predicting a single stable structure. We…
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Taxonomy
TopicsProtein Structure and Dynamics · RNA and protein synthesis mechanisms · thermodynamics and calorimetric analyses
