Research Information System
PROTEIN JOURNAL, vol.33, no.4, pp.323-336, 2014 (SCI-Expanded)
Thanks to its chemical plasticity, cysteine (Cys) is a very versatile player in proteins. A major determinant of Cys reactivity is pKa: the ability to predict it is deemed critical in redox bioinformatics. I considered different computational methods for pKa predictions and ultimately applied one (propka, ppka1) to various datasets; for all residues I assessed the effect of (1) hydrogen bonding, electrostatics and solvation on predictions and (2) protein mobility on pKa variability. Particularly for Cys, exposure and H-bond contributions heavily dictated propka predictions. The prominence of H-bond contributions was previously reported: this may explain the effectiveness of ppka1 (with Cys, tested in a benchmark). However ppka1 was also very sensitive to protein mobility; I assessed the effects of mobility on particularly large (compared to previous studies) datasets of structural ensembles; I found that exposed Cys presented the highest pKa variability, ascribable to correspondingly high H-bond fluctuations associated with protein flexibility. The benefit of including protein dynamics in pKa predictions was previously proposed, but empirical methods were never tested in this sense; instead, giving their outstanding speed, they could lend particularly well to this purpose. I devised a strategy combining short range molecular dynamics with ppka1; the protocol aimed to mitigate high ppka1 variability by including a "statistical view" of fast conformational changes. Tested in a benchmark, the strategy lead to improved performances. These results provide new insights on Cys bioinformatics (pKa prediction protocols) and Cys biology (effect of mobility on exposed Cys properties).