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DrugScore enables you to score protein-ligand complexes of your interest and to visualize the per-atom score contributions. Predicts DNA binding proteins for proteins with known 3D structure.īinding Affinity Prediction and Scoring Functions open in new windowBAPPLĬomputing binding free energy of a non-metallo protein-ligand complex using an all atom energy based empirical scoring functionīinding affinity prediction of protein-ligand complex containing Zinc Given the structure of a protein known to bind DNA, the method predicts residues that contact DNA using neural network method Web server for predicting soft metal binding sites in proteinsĪ knowledge-based method for the prediction of DNA-protein interactions Other Sites (DNA, RNA, Metals) open in new windowCHED Protein binding site prediction with an empirical scoring function Identification of optimal surface patches with the lowest docking desolvation energy values meta-PPISP is built on three individual web servers: cons-PPISP, PINUP, and Promate

Prediction of interaction hotspots from sequenceĪutomated decision-tree approach to predicting protein-protein interaction hot spotsĪ meta server for predicting protein-protein interaction sites. Prediction of protein interfaces using an empirical model Protein-Protein Interaction Sites open in new windowcons-PPISPĪ consensus neural network method for predicting protein-protein interaction sitesĪ server to predict interacting protein pairs and interacting sites by homology modeling of complex structures metaPocket use LIGSITE csc, PASS, Q-SiteFinder and SURFNET Prediction of binding site by pocket identification using the Connolly surface and degree of conservationĪ meta server for ligand-binding site prediction.