6 research outputs found
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