Influence of correlations on molecular recognition

TL;DR

This study explores how patchiness and correlations in hydrophobic and polar residue distributions at biomolecular interfaces affect recognition ability, using idealized lattice models and numerical methods.

Contribution

It introduces a two-stage approach combining ensemble design and free energy analysis to understand correlation effects on molecular recognition.

Findings

Correlations alter optimal patch lengths for biomolecular design.

Recognition ability depends on the distribution and correlations of interface residues.

Mean field and Monte Carlo methods reveal the impact of patchiness on recognition performance.

Abstract

The influence of the patchiness and correlations in the distribution of hydrophobic and polar residues at the interface between two rigid biomolecules on their recognition ability is investigated in idealised coarse-grained lattice models. A general two-stage approach is utilised where an ensemble of probe molecules is designed first and the recognition ability of the probe ensemble is related to the free energy of association with both the target molecule and a different rival molecule in a second step. The influence of correlation effects are investigated using numerical Monte Carlo techniques and mean field methods. Correlations lead to different optimum characteristic lengths of the hydrophobic and polar patches for the mutual design of the two biomolecules on the one hand and their recognition ability in the presence of other molecules on the other hand.