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.

7 Reads
  • Source
    • "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.
    Glycobiology 09/2014; 25(2). DOI:10.1093/glycob/cwu102 · 3.15 Impact Factor
  • Source
    [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.
    Journal of Chemical Theory and Computation 06/2011; 7(7):2224-2232. DOI:10.1021/ct200230v · 5.50 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: "Hot spots" are residues accounting for the majority of the protein-protein binding free energy (BFE) despite that they comprise only a small fraction of the protein-protein interface. A hot spot can be found experimentally by measuring the BFE change upon mutating it to alanine: the mutation gives rise to a significantly large increase in the BFE. Theoretical prediction of hot spots is an enthusiastic subject in biophysics, biochemistry, and bioinformatics. For the development of a reliable prediction method, it is essential to understand the physical origin of hot spots. To this end, we calculate the water-entropy gains upon binding both for a wild-type complex and for its mutant complex using a hybrid method of the angle-dependent integral equation theory applied to a molecular model for water and the morphometric approach. We note that this type of calculation has never been employed in the previously reported methods. The BFE change due to alanine mutation is evaluated only from the change in the water-entropy gain with no parameters fitted to the experimental data. It is shown that the overall performance of predicting hot spots in our method is higher than that in Robetta, a standard free-energy-based method using fitting parameters, when the most widely used criterion for defining an actual hot spot is adopted. This result strongly suggests that the water-entropy effect we calculate is the key factor governing basic physics of hot spots.
    Physical Chemistry Chemical Physics 08/2011; 13(36):16236-46. DOI:10.1039/c1cp21597c · 4.49 Impact Factor
Show more

Preview (2 Sources)

7 Reads
Available from