Abstract
Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods.
Highlights
PDZ (PSD95/Disc-large/ZO-1) domains [1] are structural modules, consisting of about a hundred amino acids, common to many signaling proteins
Unravelling how information is processed and transferred within a protein structure requires the study of the dynamical effects of, for instance, binding events, which may be captured experimentally by NMR relaxation experiments
We examine here the accuracy of these predictors in the context of a well-studied domain, i.e. the second PSD95/Disc-large/ZO-1 domain of PTP1e, and compare it to our approach that combines Monte-Carlo sampling of the conformational space of the side-chains and an information theoretical analysis
Summary
PDZ (PSD95/Disc-large/ZO-1) domains [1] are structural modules, consisting of about a hundred amino acids, common to many signaling proteins They have been shown to serve as scaffolds for other proteins and to possess particular dynamical properties [2], which are either induced by the direct interaction with a peptide [3,4,5] or indirectly by the interaction with neighboring domains [6,7]. Whereas the first provides a mechanistic explanation, the latter does not require sequential mechanisms for the propagation of information and production of allosteric effects Both these classical models assumed large structural differences between the different macroscopic states of the protein, like for instance their bound and unbound forms. It has been argued that long-range intra-protein communication may originate from the changes in internal dynamics, without altering the average macroscopic conformation, providing as such information exchange only through entropic effects [11,12,13,14,15,16]
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