Molecular binding: Under water's influence

Gerhard Hummer is in the Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892-0520, USA. .
Nature Chemistry (Impact Factor: 25.33). 11/2010; 2(11):906-7. DOI: 10.1038/nchem.885
Source: PubMed
Hydration is known to affect molecular-recognition processes, such as those between proteins and ligands. Now, theoretical simulations provide thermodynamic insight into cavity-ligand binding, revealing how it is predominantly driven by the behaviour of the few surrounding water molecules.

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    • "The analysis of the structure and dynamic properties of the solvent around protein active sites, has gathered strong attention among the scientific community, showing that the water molecules that are displaced upon ligand binding are key players for determining the underlying thermodynamics of the process (Michel et al. 2009; Hummer 2010; Setny et al. 2010 ). As a result of the protein–solvent interactions , water molecules are not placed randomly on the protein surface, adopting thus a well-established structure, defined by regions of highly ordered water molecules. "
    [Show abstract] [Hide abstract] ABSTRACT: Understanding protein–ligand interactions is a fundamental question in basic biochemistry, and the role played by the solvent along this process is not yet fully understood. This fact is particularly relevant in lectins, proteins that mediate a large variety of biological processes through the recognition of specific carbohydrates. In the present work, we have thoroughly analyzed a nonredundant and well-curated set of lectin structures looking for a potential relationship between the structural water properties in the apo-structures and the corresponding protein–ligand complex structures. Our results show that solvent structure adjacent to the binding sites mimics the ligand oxygen structural framework in the resulting protein–ligand complex, allowing us to develop a predictive method using a Naive Bayes classifier. We also show how these properties can be used to improve docking predictions of lectin–carbohydrate complex structures in terms of both accuracy and precision, thus developing a solid strategy for the rational design of glycomimetic drugs. Overall our results not only contribute to the understanding of protein–ligand complexes, but also underscore the role of the water solvent in the ligand recognition process. Finally, we discuss our findings in the context of lectin specificity and ligand recognition properties.
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    • "Recent simulations on a model system addressed this question. Through the use of umbrella sampling calculations at multiple temperatures on the simple model system of a spherical ligand binding into a hemispherical cavity, Baron et al. decomposed the entropic and enthalpic contributions to ligand binding or rejection for neutral and charged ligands binding to neutral and charged receptors (Baron et al. 2010; Hummer, 2010; Setny et al. 2010). Results demonstrated that water dominated the binding thermodynamics. "
    [Show abstract] [Hide abstract] ABSTRACT: Molecular recognition plays a central role in biochemical processes. Although well studied, understanding the mechanisms of recognition is inherently difficult due to the range of potential interactions, the molecular rearrangement associated with binding, and the time and length scales involved. Computational methods have the potential for not only complementing experiments that have been performed, but also in guiding future ones through their predictive abilities. In this review, we discuss how molecular dynamics (MD) simulations may be used in advancing our understanding of the thermodynamics that drive biomolecular recognition. We begin with a brief review of the statistical mechanics that form a basis for these methods. This is followed by a description of some of the most commonly used methods: thermodynamic pathways employing alchemical transformations and potential of mean force calculations, along with end-point calculations for free energy differences, and harmonic and quasi-harmonic analysis for entropic calculations. Finally, a few of the fundamental findings that have resulted from these methods are discussed, such as the role of configurational entropy and solvent in intermolecular interactions, along with selected results of the model system T4 lysozyme to illustrate potential and current limitations of these methods.
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    [Show abstract] [Hide abstract] ABSTRACT: The independent trajectory thermodynamic integration (IT-TI) approach (Lawrenz et. al J. Chem. Theory. Comput. 2009, 5:1106-1116(1)) for free energy calculations with distributed computing is employed to study two distinct cases of protein-ligand binding: first, the influenza surface protein N1 neuraminidase bound to the inhibitor oseltamivir, and second, the M. tuberculosis enzyme RmlC complexed with the molecule CID 77074. For both systems, finite molecular dynamics (MD) sampling and varied molecular flexibility give rise to IT-TI free energy distributions that are remarkably centered on the target experimental values, with a spread directly related to protein, ligand, and solvent dynamics. Using over 2 μs of total MD simulation, alternative protocols for the practical, general implementation of IT-TI are investigated, including the optimal use of distributed computing, the total number of alchemical intermediates, and the procedure to perturb electrostatics and van der Waals interactions. A protocol that maximizes predictive power and computational efficiency is proposed. IT-TI outperforms traditional TI predictions and allows a straightforward evaluation of the reliability of free energy estimates. Our study has broad implications for the use of distributed computing in free energy calculations of macromolecular systems.
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