Protein binding site prediction using an empirical scoring function

Abstract

Most biological processes are mediated by interactions between proteins and their interacting partners including proteins, nucleic acids and small molecules. This work establishes a method called PINUP for binding site prediction of monomeric proteins. With only two weight parameters to optimize, PINUP produces not only 42.2% coverage of actual interfaces (percentage of correctly predicted interface residues in actual interface residues) but also 44.5% accuracy in predicted interfaces (percentage of correctly predicted interface residues in the predicted interface residues) in a cross validation using a 57-protein dataset. By comparison, the expected accuracy via random prediction (percentage of actual interface residues in surface residues) is only 15%. The binding sites of the 57-protein set are found to be easier to predict than that of an independent test set of 68 proteins. The average coverage and accuracy for this independent test set are 30.5 and 29.4%, respectively. The significant gain of PINUP over expected random prediction is attributed to (i) effective residue-energy score and accessible-surface-area-dependent interface-propensity, (ii) isolation of functional constraints contained in the conservation score from the structural constraints through the combination of residue-energy score (for structural constraints) and conservation score and (iii) a consensus region built on top-ranked initial patches.

MET-activating Residues in the B-repeat of the Listeria monocytogenes Invasion Protein InlB

“…InlB to Stimulate Cell Motility-Two servers predicting potentialprotein-proteininteractionsitesbasedonstructuresofmonomeric proteins (30,31) identified a likely binding hot spot in the B-repeat formed by the loop N-terminal of strand ␤4 (PINUP and ProMate) and the N terminus of strand ␤1 (PINUP only). In addition, we identified a potential interaction site in strand ␤2 of the B-repeat, because its sequence is least conserved among all secondary structure elements in Flg_new domains (17).…”

Structural modeling and analysis of dengue-mediated inhibition of interferon signaling pathway

“…The approach of the HADDOCK web server is based on the biochemical and/or biophysical interaction data (Liang et al, 2006) along with ab initio PPIs. HADDOCK uses the docking protocol, which supports solvated docking, flexibility of protein regions and modified amino acids.…”

“…PINuP (Liang et al, 2006), PIER (Kufareva et al, 2007), WHISCY (De Vries et al, 2006), ProMate (Neuvirth et al, 2004), SPPIDER (Porollo and Meller, 2007) and cons-PPISP (Chen and Zhou, 2005) are six interface residues prediction algorithms, which are cumulatively included in CPORT and provide reliable prediction of the interface residues, which can be integrated into the HADDOCK web server as active and passive site residues.…”

Computational Tools and Databases for the Study and Characterization of Protein Interactions

“…The combination of ProMate's predictions and a parametric scoring function based of sequence conservation and structural features resulted in an improvement of the accuracy of the predictions (de Vries et al 2006). Other implementations of prediction methods include an empirical scoring function composed of side chain energy score, residue conservation and interface propensity (Liang et al 2006), the search of structural interaction templates extracted from protein complexes (Chang et al 2006) and a clustering algorithm that identifies residues with a high propensity of being located in interfaces (Negi et al 2007). …”