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Book ChapterDOI

Hot Spots at the Protein-Protein Interface

TL;DR: This work documents some basic information on hot spots in the context of protein-protein interactions and describes how they help to efficiently distinguish specific from non-specific protein- protein interactions.
Abstract: Protein-protein interaction leads to stable interface for specific biochemical or regulatory function. This is accompanied by binding free energy at the interface between interacting proteins. High energy interface residues are referred as hot spots. They have critical role in protein-protein binding. Hot spots participate in strong and energetically favorable side chain-side chain interactions. They help to efficiently distinguish specific from non-specific protein-protein interactions. We document some basic information on hot spots in the context of protein-protein interactions.
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Journal ArticleDOI
TL;DR: The Alanine Scanning Energetics database (ASEdb) is a searchable database of single alanine mutations in protein-protein, protein-nucleic acid, and protein-small molecule interactions for which binding affinities have been experimentally determined.
Abstract: The Alanine Scanning Energetics database (ASEdb) is a searchable database of single alanine mutations in protein-protein, protein-nucleic acid, and protein-small molecule interactions for which binding affinities have been experimentally determined. In cases where structures are available, it contains surface areas of the mutated side chain and links to the PDB entries. It is useful for studying the contribution of single amino acids to the energetics of protein interactions, and can be updated by researchers as new data are generated.

384 citations

Journal ArticleDOI
TL;DR: An accurate prediction model for hot spot residues, given the structure of a protein complex is developed and several new features based on the protrusion index of amino acid residues are proposed, which have been shown to significantly improve the prediction performance of hot spots.
Abstract: Background: It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying their interactions. Experimental hot spots detection methods such as alanine scanning mutagenesis are not applicable on a large scale since they are time consuming and expensive. Therefore, reliable and efficient computational methods for identifying hot spots are greatly desired and urgently required. Results: In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces. We systematically investigate a wide variety of 62 features from a combination of protein sequence and structure information. Then, to remove redundant and irrelevant features and improve the prediction performance, feature selection is employed using the F-score method. Based on the selected features, nine individualfeature based predictors are developed to identify hot spots using SVMs. Furthermore, a new ensemble classifier, namely APIS (A combined model based on Protrusion Index and Solvent accessibility), is developed to further improve the prediction accuracy. The results on two benchmark datasets, ASEdb and BID, show that this proposed method yields significantly better prediction accuracy than those previously published in the literature. In addition, we also demonstrate the predictive power of our proposed method by modelling two protein complexes: the calmodulin/ myosin light chain kinase complex and the heat shock locus gene products U and V complex, which indicate that our method can identify more hot spots in these two complexes compared with other state-of-the-art methods. Conclusion: We have developed an accurate prediction model for hot spot residues, given the structure of a protein complex. A major contribution of this study is to propose several new features based on the protrusion index of amino acid residues, which has been shown to significantly improve the prediction performance of hot spots. Moreover, we identify a compact and useful feature subset that has an important implication for identifying hot spot residues. Our results indicate that these features are more effective than the conventional evolutionary conservation, pairwise residue potentials and other traditional features considered previously, and that the combination of our and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spot residues. The data and source code are available on web site http://home.ustc.edu.cn/~jfxia/hotspot.html.

183 citations

Journal ArticleDOI
01 May 1996-Proteins
TL;DR: A method is described to dock a ligand into a binding site in a protein on the basis of the complementarity of the inter‐molecular atomic contacts, which can assist in the design of improved ligands by indicating what changes in complementarity may occur as a result of the substitution of an atom in the ligand.
Abstract: A method is described to dock a ligand into a binding site in a protein on the basis of the complementarity of the intermolecular atomic contacts. Docking is performed by maximization of a complementarity function that is dependent on atomic contact surface area and the chemical properties of the contacting atoms. The generality and simplicity of the complementarity function ensure that a wide range of chemical structures can be handled. The ligand and the protein are treated as rigid bodies, but displacement of a small number of residues lining the ligand binding site can be taken into account. The method can assist in the design of improved ligands by indicating what changes in complementarity may occur as a result of the substitution of an atom in the ligand. The capabilities of the method are demonstrated by application to 14 protein-ligand complexes of known crystal structure.

163 citations

Journal ArticleDOI
TL;DR: The Binding Interface Database organizes the vast amount of protein interaction information into tables, graphical contact maps and descriptive functional profiles to make information about protein interactive function easily accessible.
Abstract: Summary: To make information about protein interactive function easily accessible, we are mining the primary scientific literature for detailed data about protein interfaces. The Binding Interface Database (BID) organizes the vast amount of protein interaction information into tables, graphical contact maps and descriptive functional profiles. Currently data on 170 interacting protein pairs are available with over 1300 mutations described. Availability: The BID database is freely available at http: //tsailab.org/BID/. To have your protein of interest entered, contact Tiffany Fischer (tiffbrink@neo.tamu.edu) or Jerry Tsai at the email below

149 citations

Journal ArticleDOI
TL;DR: A new database of computational hot spots in protein interfaces: HotSprint is presented, which provides information for interface residues that are functionally and structurally important as well as the evolutionary history and solvent accessibility of residues in interfaces.
Abstract: We present a new database of computational hot spots in protein interfaces: HotSprint Hot spots are residues comprising only a small fraction of interfaces yet accounting for the majority of the binding energy HotSprint contains data for 35 776 protein interfaces among 49 512 protein interfaces extracted from the multi-chain structures in Protein Data Bank (PDB) as of February 2006 The conserved residues in interfaces with certain buried accessible solvent area (ASA) and complex ASA thresholds are flagged as computational hot spots The predicted hot spots are observed to correlate with the experimental hot spots with an accuracy of 76% Several machine-learning methods (SVM, Decision Trees and Decision Lists) are also applied to predict hot spots, results reveal that our empirical approach performs better than the others A web interface for the HotSprint database allows users to browse and query the hot spots in protein interfaces HotSprint is available at http://prismccbbkuedutr/hotsprint; and it provides information for interface residues that are functionally and structurally important as well as the evolutionary history and solvent accessibility of residues in interfaces

114 citations