Calculation of conformational ensembles from potentials of mena force

Sippl, Manfred J.

doi:10.1016/s0022-2836(05)80269-4

Cited by 1,024 publications

(501 citation statements)

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“…The potentials of mean force (PMFs), 1 a beneficial tool in protein fold recognition, generally use the training data base of known protein structures to extract "pseudo-potentials" for predicting unknown structures (41,42,(45)(46)(47)(48)(49). Many applications have demonstrated their usefulness in studies of protein-ligand binding (50 -55) and protein-protein associations (56,57).…”

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CH···O Hydrogen Bonds at Protein-Protein Interfaces

Jiang

Lai

2002

Journal of Biological Chemistry

218

168

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For the first time, a statistical potential has been developed to quantitatively describe the CH⅐⅐⅐O hydrogen bonding interaction at the protein-protein interface. The calculated energies of the CH⅐⅐⅐O pair interaction show a favorable valley at ϳ3.3 Å, exhibiting a feature typical of an H-bond and similar to the ab initio quantum calculation result (Scheiner, S., Kar, T., and Gu, Y. (2001) J. Biol. Chem. 276, 9832-9837). The potentials have been applied to a set of 469 protein-protein complexes to calculate the contribution of different types of interactions to each protein complex: the average energy contribution of a conventional H-bond is ϳ30%; that of a CH⅐⅐⅐O H-bond is 17%; and that of a hydrophobic interaction is 50%. In some protein-protein complexes, the contribution of the CH⅐⅐⅐O H-bond can reach as high as ϳ40 -50%, indicating the importance of the CH⅐⅐⅐O H-bond at the protein interface. At the interfaces of these complexes, C ␣ H⅐⅐⅐O H-bonds frequently occur between adjacent strands in both parallel and antiparallel orientations, having the obvious structural motif of bifurcated H-bonds. Our study suggests that the weak CH⅐⅐⅐O Hbond makes an important contribution to the association and stability of protein complexes and needs more attention in protein-protein interaction studies.The conventional hydrogen bonds of the type X-H⅐⅐⅐Y (where X and Y ϭ N or O) have been widely found and thoroughly studied in macromolecular structures from both experimental and theoretical perspectives (1, 2, 7-9). On the other hand, close CH⅐⅐⅐O contacts occur often in protein structures and are considered as hydrogen bonds. It is increasingly recognized that weak CH⅐⅐⅐O hydrogen bonds play an important role in the stabilization and function of biological macromolecules (3-6).CH⅐⅐⅐O contacts are now being increasingly widely accepted as genuine hydrogen bonds (10, 11). Much of the evidence for the CH⅐⅐⅐O hydrogen bond comes from the observation that short intermolecular CH⅐⅐⅐O contacts are well established in many small molecule crystals (12, 13). In more recent years, neutron diffraction studies of amino acid crystals (which yield highly accurate positions of hydrogen atoms experimentally) have provided convincing evidence in favor of the ability of the carbon atoms to function directly as hydrogen bond donors in CH⅐⅐⅐O contacts (14). Recently, there have been surveys of high resolution protein structures that reveal the widespread occurrence of weak CH⅐⅐⅐O hydrogen bonds (15-21, 59, 60). Various studies have reported the existence of a weak C ␣ H⅐⅐⅐O hydrogen bond between the parallel ␤-sheets in proteins (17,59,60). At the same time, some mutation studies on protein-ligand interactions have reported that weak CH⅐⅐⅐O bonds stabilize proteinligand complexes (10,22,23). Similar to protein-ligand interfaces, close CH⅐⅐⅐O contacts abound at protein-protein interfaces. Although CH⅐⅐⅐O H-bonds are normally weaker than conventional hydrogen bonds, their number cannot be neglected. The CH⅐⅐⅐O hydrogen bonding interaction is als...

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confidence: 99%

CH···O Hydrogen Bonds at Protein-Protein Interfaces

Jiang

Lai

2002

Journal of Biological Chemistry

218

168

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“…Then, a comparison between expected and observed feature distributions can yield some insight (although statistical significance does not guarantee biochemical importance). This criterion has been successfully applied in the study of atomic interactions (Warme & Morgan, 1978), the study of some protein microenvironments (Reid et al, 1985;Singh & Thornton, 1992;Walshaw & Goodfellow, 1993), and sequence-structure correlations (Klingler & Brutlag, 1993, 1994, and in constructing context-sensitive potential functions (Sippl, 1990;Rooman et al, 1992). There are, however, advantages to choosing background "control" distributions that are not parametric or assumed uniform but are computed from a population of negative examples of the feature of interest.…”

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Characterizing the microenvironment surrounding protein sites

1995

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Sites are microenvironments within a biomolecular structure, distinguished by their structural or functional role. A site can be defined by a three-dimensional location and a local neighborhood around this location in which the structure or function exists. We have developed a computer system to facilitate structural analysis (both qualitative and quantitative) of biomolecular sites. Our system automatically examines the spatial distributions of biophysical and biochemical properties, and reports those regions within a site where the distribution of these properties differs significantly from control nonsites. The properties range from simple atom-based characteristics such as charge to polypeptide-based characteristics such as type of secondary structure. Our analysis of sites uses nonsites as controls, providing a baseline for the quantitative assessment of the significance of the features that are uncovered. In this paper, we use radial distributions of properties to study three well-known sites (the binding sites for calcium, the milieu of disulfide bridges, and the serine protease active site). We demonstrate that the system automatically finds many of the previously described features of these sites and augments these features with some new details. In some cases, we cannot confirm the statistical significance of previously reported features. Our results demonstrate that analysis of protein structure is sensitive to assumptions about background distributions, and that these distributions should be considered explicitly during structural analyses.Keywords: biophysical properties; calcium binding; computational biology; disulfide bridges; microenvironment; protein structure analysis; serine proteases; software Central to molecular biology is the determination of macromolecular structure and the analysis of how structural elements produce an observed function. The principles by which structure relates to function have been elucidated in a piecemeal fashion, from work on single structures or small classes of structures. Computational assistance has come primarily in the form of graphical methods for scientific visualization and from special purpose programs for analyzing individual biophysical properties (such as solvent accessibility or electrostatic fields). Unfortunately, studying structures individually entails a risk of missing important relationships that would be revealed by pooling relevant data. The expected surfeit of protein structures provides an opportunity to develop tools for automatically examining biological structures and producing useful representations of the key biophysical and biochemical features. The utility of a general purpose system for producing these representations would extend from medical/pharmaceutical applications (model-based drug design, comparing pharmacological Reprint requests to: Russ B. Altman, Section on Medical Informatics, Stanford University School of Medicine, MSOB X-215, Stanford, California 94305-5479; e-mail: altman@camis.stanford.edu. activities) to ind...

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“…The quasi-chemical method [5][6][7] is widely used in various forms for obtaining the effective potential between aminoacids and to provide "scores" for candidate protein structures. Briefly, the procedure is as follows: from the databank, one compiles the probability density, f A,B (r), that two specific aminoacids are at a distance r from each other.…”

Section: A the Quasi-chemical Methodsmentioning

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Determination of interaction potentials of amino acids from native protein structures: Tests on simple lattice models

Mourik

Clementi

Maritan

et al. 1999

The Journal of Chemical Physics

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We propose a novel method for the determination of the effective interaction potential between the amino acids of a protein. The strategy is based on the combination of a new optimization procedure and a geometrical argument, which also uncovers the shortcomings of any optimization scheme. The strategy can be applied on any data set of native structures such as those available from the Protein Data Bank (PDB). In this work, however, we explain and test our approach on simple lattice models, where the true interactions are known a priori. Excellent agreement is obtained between the extracted and the true potentials even for modest numbers of protein structures in the PDB. Comparisons with other methods are also discussed.

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Calculation of conformational ensembles from potentials of mena force

Cited by 1,024 publications

References 41 publications

CH···O Hydrogen Bonds at Protein-Protein Interfaces

CH···O Hydrogen Bonds at Protein-Protein Interfaces

Characterizing the microenvironment surrounding protein sites

Determination of interaction potentials of amino acids from native protein structures: Tests on simple lattice models

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