Literature DB >> 32198636

Allosteric communication in molecular machines via information exchange: what can be learned from dynamical modeling.

Dimitri Loutchko1, Holger Flechsig2.   

Abstract

Allosteric regulation is crucial for the operation of protein machines and molecular motors. A major challenge is to characterize and quantify the information exchange underlying allosteric communication between remote functional sites in a protein, and to identify the involved relevant pathways. We review applications of two topical approaches of dynamical protein modeling, a kinetic-based single-molecule stochastic model, which employs information thermodynamics to quantify allosteric interactions, and structure-based coarse-grained modeling to characterize intra-molecular couplings in terms of conformational motions and propagating mechanical strain. Both descriptions resolve the directionality of allosteric responses within a protein, emphasizing the concept of causality as the principal hallmark of protein allostery. We discuss the application of techniques from information thermodynamics to dynamic protein elastic networks and evolutionary designed model structures, and the ramifications for protein allostery.

Keywords:  Allosteric regulation; Elastic networks; Information theory; Markov networks; Molecular machines; Stochastic thermodynamics

Year:  2020        PMID: 32198636      PMCID: PMC7242553          DOI: 10.1007/s12551-020-00667-8

Source DB:  PubMed          Journal:  Biophys Rev        ISSN: 1867-2450


  49 in total

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4.  Stochastic thermodynamics of a chemical nanomachine: The channeling enzyme tryptophan synthase.

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8.  Symmetry, Rigidity, and Allosteric Signaling: From Monomeric Proteins to Molecular Machines.

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5.  Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations.

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  5 in total

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