Cy‐preds: An algorithm and a web service for the analysis and prediction of cysteine reactivity

摘要: Cysteine (Cys) is a critically important amino acid, serving variety of functions within proteins including structural roles, catalysis, and regulation function through post-translational modifications. Predicting which Cys residues are likely to be reactive very sought after feature. Few methods currently available for the task, either based on evaluation physicochemical features (e.g., pKa exposure) or similarity with known instances. In this study, we developed an algorithm (named HAL-Cy) blends previous work novel implementations identify from nonreactive. HAL-Cy present two major components: (i) energy part, rooted H-bond network contributions (ii) knowledge composed different profiling approaches (including newly weighting matrix sequence profiling). our evaluations, provided significantly improved performances, as tested in comparisons existing approaches. We implemented web service (Cy-preds), ultimate product work; it additional features, tools, options: Cy-preds capable performing fully automated calculations thorough analysis reactivity proteins, ranging predictions functional characterization. believe represents original, effective, useful addition current array tools scientists involved redox biology, biochemistry, bioinformatics.