DOI

Transitions between different conformational states are ubiquitous in proteins. A vast class of conformation-changing proteins includes evolutionary switches, which vary their conformation as an effect of few mutations or weak environmental variations. However, modeling those processes is extremely difficult due to the need of efficiently exploring a vast conformational space to look for the actual transition path. In this study, we report a strategy that simplifies this task attacking the complexity on several sides. We first apply a minimalist coarse-grained model to the protein, based on an empirical force field with a partial structural bias toward one or both the reference structures. We then explore the transition paths by means of stochastic molecular dynamics and select representative structures by means of a principal path-based clustering algorithm. We finally compare this trajectory with that produced by independent methods adopting a morphing-oriented approach. Our analysis indicates that the minimalist model returns trajectories capable of exploring intermediate states with physical meaning, retaining a very low computational cost, which can allow systematic and extensive exploration of the multistable proteins transition pathways.

Original languageEnglish
Pages (from-to)189-199
Number of pages11
JournalJournal of Computational Biology
Volume27
Issue number2
Early online date26 Nov 2019
DOIs
StatePublished - 1 Feb 2020

    Scopus subject areas

  • Computational Mathematics
  • Genetics
  • Molecular Biology
  • Computational Theory and Mathematics
  • Modelling and Simulation

    Research areas

  • evolutionary switch, minimalist coarse-grained model, molecular evolution, prompt, transition path, PROTEIN-STRUCTURE, SERVER, DYNAMICS, MINIMALIST MODELS, MOTIONS, INSIGHTS

ID: 53713274