From protein sequence to dynamics and disorder with DynaMine

Abstract

Protein function and dynamics are closely related; however, accurate dynamics information is difficult to obtain. Here based on a carefully assembled data set derived from experimental data for proteins in solution, we quantify backbone dynamics properties on the amino-acid level and develop DynaMine-a fast, high-quality predictor of protein backbone dynamics. DynaMine uses only protein sequence information as input and shows great potential in distinguishing regions of different structural organization, such as folded domains, disordered linkers, molten globules and pre-structured binding motifs of different sizes. It also identifies disordered regions within proteins with an accuracy comparable to the most sophisticated existing predictors, without depending on prior disorder knowledge or three-dimensional structural information. DynaMine provides molecular biologists with an important new method that grasps the dynamical characteristics of any protein of interest, as we show here for human p53 and E1A from human adenovirus 5.

Introducing Protein Intrinsic Disorder

“…Furthermore, an ELM server (http://elm.eu.org/) has been developed in view of investigating short functional sites in modular Eukaryotic proteins. 199 The recently developed dynamics predictor, DynaMine, 208 shows that recognition motifs have characteristic patterns of local dynamics, which could be used for improving the accuracy of motif prediction.…”

Disordered regions in transmembrane proteins

“…For disorder prediction, we used the same in silico programs as Pryor and Wiener [23], plus Dynamine [39,40] and ANCHOR [41,42]. In case of IUPred [21,43] and ANCHOR, in addition to the regular usage, we implemented the following modifications on the input sequences: i, the transmembrane segments (io); ii, the transmembrane segments plus 15 amino acids in both directions (io15); iii, and the transmembrane segments plus 30 amino acids in both directions (io30) were cut out, and the remaining "inside" and "outside" sequence parts of each protein were all linked together to produce an arbitrary "in" and "out" protein, respectively.…”

Back to the Future: Nuclear Magnetic Resonance and Bioinformatics Studies on Intrinsically Disordered Proteins

“…Therefore chemical shifts of IDPs offer a rich dataset to be further explored and used to develop prediction methods. One such method, DynaMine (Cilia et al 2013), is a linear model that predicts chemical shift-based order parameters directly from amino acid sequence and has a disorder prediction performance on par with more complex predictors trained from orderdisorder datasets.…”