Dataset Information

Disorder transitions and conformational diversity cooperatively modulate biological function in proteins.

ABSTRACT: Structural differences between conformers sustain protein biological function. Here, we studied in a large dataset of 745 intrinsically disordered proteins, how ordered-disordered transitions modulate structural differences between conformers as derived from crystallographic data. We found that almost 50% of the proteins studied show no transitions and have low conformational diversity while the rest show transitions and a higher conformational diversity. In this last subset, 60% of the proteins become more ordered after ligand binding, while 40% more disordered. As protein conformational diversity is inherently connected with protein function our analysis suggests differences in structure-function relationships related to order-disorder transitions.

SUBMITTER: Zea DJ

PROVIDER: S-EPMC4941770 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Disorder transitions and conformational diversity cooperatively modulate biological function in proteins.

Zea Diego Javier DJ Monzon Alexander Miguel AM Gonzalez Claudia C Fornasari María Silvina MS Tosatto Silvio C E SC Parisi Gustavo G

Protein science : a publication of the Protein Society 20160418 6

Structural differences between conformers sustain protein biological function. Here, we studied in a large dataset of 745 intrinsically disordered proteins, how ordered-disordered transitions modulate structural differences between conformers as derived from crystallographic data. We found that almost 50% of the proteins studied show no transitions and have low conformational diversity while the rest show transitions and a higher conformational diversity. In this last subset, 60% of the proteins ...[more]

PMID: 27038125

Similar Datasets

Project description:Many proteins contain regions of intrinsic disorder, not folding into unique, stable conformations. Numerous experimental methods have been developed to measure the disorder of all or select residues. In the absence of experimental data, computational methods are often utilized to identify these disordered regions and thus gain a better understanding of both structure and function. Many freely available computational methods have been developed to predict regions of intrinsic disorder from the primary sequence of a protein, including our recently developed Rosetta ResidueDisorder. While these methods are very useful, they are only designed to predict intrinsic disorder from the sequence. However, it would be useful to have a method that could also measure intrinsic disorder directly from structure. Such a method might also be used to identify changes in the structure of systems that can transition from folded to unfolded or vice versa, even systems that are not intrinsically disordered. Here we extended the capabilities of Rosetta ResidueDisorder to measure the intrinsic disorder from the coordinates of a single conformation of a protein. As a proof of principle, we show that ResidueDisorder can measure the intrinsic disorder from the coordinates with a higher accuracy (69.2%) than when predicted from sequence (65.4%) using a benchmark set of 229 proteins, showing that intrinsic disorder can be measured accurately from single structures over a large range of intrinsic disorder (0-100%). Additionally, we used ResidueDisorder to analyze unfolding trajectories of 12 fast-folding, nonintrinsically disordered proteins generated using molecular dynamics (MD), specifically steered MD (SMD), high-temperature MD, and accelerated MD (aMD) as well as long-time scale folding/unfolding trajectories. Using ResidueDisorder, a clear correlation between RMSD with respect to the native structure and measured fraction of denatured residues was observed. Finally, we introduced methods to predict folding/unfolding transitions as well as a native-like structure in the absence of a crystal structure from folding/unfolding MD trajectories. Rosetta ResidueDisorder is available as an application in the Rosetta software suite with the addition of new capabilities for directly identifying denatured regions and predicting events.

Dataset Information

Disorder transitions and conformational diversity cooperatively modulate biological function in proteins.

Publications

Disorder transitions and conformational diversity cooperatively modulate biological function in proteins.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets