Design of elastic networks with evolutionary optimised long-range communication as mechanical models of allosteric proteins

TL;DR

This paper presents an in silico method for designing elastic network structures that mimic allosteric proteins by encoding long-range dynamical coupling, using evolutionary optimization to enhance communication and robustness.

Contribution

The study introduces a novel evolutionary design approach for elastic networks that model allosteric communication, revealing dynamical properties similar to real proteins.

Findings

Designed structures exhibit long-range strain propagation.

Evolutionary optimization improves allosteric coupling.

Structures show robustness to mutations.

Abstract

Allosteric effects are often underlying the activity of proteins and elucidating generic design aspects and functional principles which are unique to allosteric phenomena represents a major challenge. Here an approach which consists in the in silico design of synthetic structures which, as the principal element of allostery, encode dynamical long-range coupling among two sites is presented. The structures are represented by elastic networks, similar to coarse-grained models of real proteins. A strategy of evolutionary optimization was implemented to iteratively improve allosteric coupling. In the designed structures allosteric interactions were analyzed in terms of strain propagation and simple pathways which emerged during evolution were identified as signatures through which long-range communication was established. Moreover, robustness of allosteric performance with respect to mutations was demonstrated. As it turned out, the designed prototype structures reveal dynamical properties resembling those found in real allosteric proteins. Hence, they may serve as toy models of complex allosteric systems, such as proteins.