The omnipresence and diversity of allosteric regulation in proteins and protein associations complemented by the potential for the design of allosterically acting biologics and drugs call for the development of a new generation of computational models for the analysis of allostery and rational engineering/design of desired signaling and effector molecules determining it. One of the most important challenges is the consideration of the role of amino acid sequence in forming the protein’s allosteric communication, including the mode and strength of the allosteric signal that is communicated to the regulated functional site. Here, we present the network-based model with a sequence dependence added in consideration of allosteric communication by combining the structure-based statistical mechanical model of allostery with the Miyazawa-Jernigan residue–residue potential. Applying the model in the analysis of five classical allosteric proteins, we found that it is necessary to consider the following two major determinants: (i) the free energy exerted by the allosteric site on the regulated one and (ii) the background (average) change in dynamics of the overall structure. We show that working together these two components determine the allosteric modulation, calling one to study their dependence on structures, oligomerization states, and sequence divergence in different proteins.
Sequence-dependent model of allosteric communication
Current address: Computational Drug Discovery, EMD Serono Research and Development Institute, Merck KGaA, 45A Middlesex Tpke, Billerica, MA 01821, USA.
Note: This paper is part of the JCP Special Topic on New Views of Allostery.
Enrico Guarnera, Igor N. Berezovsky; Sequence-dependent model of allosteric communication. J. Chem. Phys. 7 April 2023; 158 (13): 135101. https://doi.org/10.1063/5.0139848
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