The Role of Conformational Changes in Molecular Recognition

Conformational changes of molecules are crucial elements in many biochemical processes, and also in molecular recognition. Here, we present a novel exact mathematical equation for the binding free energy of a receptor–ligand pair. It shows that the energetic contribution due to conformational changes upon molecular recognition is defined by the so-called Kullback–Leibler (KL) divergence between the probability distributions of the conformational ensemble of the biomolecule in the bound and free states. We show that conformational changes always contribute positively to the change in free energy and therefore disfavor the association process. Using the example of ligands binding to a flexible cavity of T4 lysozyme, we illustrate that, due to enthalpy–entropy compensation, the conformational entropy is a misleading quantity for assessing the conformational contribution to the binding free energy, in contrast to the KL divergence, which is the correct quantity to use in this context

How Molecular Conformational Changes Affect Changes in Free Energy

A simple quantitative relationship between the molecular conformational changes and the corresponding changes in the free energy is presented. The change in free energy is the sum of that part of the enthalpic change that is due to the externally applied work (perturbation) and of that part of the entropic change, termed dissipative entropy, that is related to the conformational changes. The dissipative entropy is equivalent to the relative entropy, a concept from information theory, between the distributions of the conformations in the initial and the final states. The remaining change in entropy (nondissipative) cancels exactly with the remaining enthalpic change. The calculation of the dissipative entropy is demonstrated to pose the main difficulty in free energy computation. The straightforward decomposition of the dissipative entropy into contributions from different parts of the system promises to improve the understanding of the role of conformational changes in biochemical reactions

Consistent Prediction of Mutation Effect on Drug Binding in HIV‑1 Protease Using Alchemical Calculations

Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy Δ<i>G</i>, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease

Computational Identification of Novel Amino-Acid Interactions in HIV Gag via Correlated Evolution

<div><p>Pairs of amino acid positions that evolve in a correlated manner are proposed to play important roles in protein structure or function. Methods to detect them might fare better with families for which sequences of thousands of closely related homologs are available than families with only a few distant relatives. We applied co-evolution analysis to thousands of sequences of HIV Gag, finding that the most significantly co-evolving positions are proximal in the quaternary structures of the viral capsid. A reduction in infectivity caused by mutating one member of a significant pair could be rescued by a compensatory mutation of the other.</p> </div

Consistent Prediction of Mutation Effect on Drug Binding in HIV‑1 Protease Using Alchemical Calculations

Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy Δ<i>G</i>, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease

The location of the positions described in the text on Gag sequence and structure.

<p>The top shows a linear representation of Gag domain structure, with positions numbered according to GAG_HV1B1. The three non-trivial co-evolving clusters are shown beneath the domain structure, as are the appropriate regions of the alignment for a sub-set of the sequences used. Sequences are labeled by their GenBank (gb) or EMBL (emb) accession codes. The structures on the bottom right show where the positions in the figure lie on the known three-dimensional structures of Gag domains. The two most significant pairs are marked in the alignment.</p