Journal of Chemical Theory and ComputationBioinformaticsPeer-reviewed journal article
Effects of phosphorylation on protein backbone dynamics and conformational preferences
Abstract
Phosphorylations are the most common and extensively studied post-translational modification (PTM) of proteins in eukaryotes. They constitute a major regulatory mechanism, modulating protein function, protein-protein interactions, as well as subcellular localization. Phosphorylation sites are preferably located in intrinsically disordered regions and have been shown to trigger structural rearrangements and order-to-disorder transitions. They can therefore have a significant effect on protein backbone dynamics or conformation, but only sparse experimental data are available. To obtain a more general description of how and when phosphorylations have a significant effect on protein behavior, molecular dynamics (MD) currently provides the only suitable framework to study these effects at a large scale in atomistic detail. This study develops a systematic MD simulation framework to explore the influence of phosphorylations on the local backbone dynamics and conformational propensities of proteins. Through a series of glycine-backbone peptides, we studied the effects of amino acid residues including the three most common phosphorylations (Ser, Thr, and Tyr), on local backbone dynamics and conformational propensities. We further extended our study to investigate the interactions of all such residues between position i to positions i+1, i+2, i+3, and i+4 in such peptides. The final dataset is comprised of structural ensembles for 3,393 sequences with more than 1 {micro}s of sampling for each ensemble. To validate the relevance of the results, the structural and conformational properties extracted from the MD simulations are compared to NMR data from the Biological Magnetic Resonance Data Bank. The systematic nature of this study enables the projection of the gained knowledge onto any phosphorylation-site in the proteome and provides a general framework for the study of further PTMs. The full dataset is publicly available, as a training and reference set.
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