Dataset Information

A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins.

ABSTRACT: Intrinsically disordered proteins/regions (IDPs/IDRs) are prevalent in allosteric regulation. It was previously thought that intrinsic disorder is favorable for maximizing the allosteric coupling. Here, we propose a comprehensive ensemble model to compare the roles of both order-order transition and disorder-order transition in allosteric effect. It is revealed that the MWC pathway (order-order transition) has a higher probability than the EAM pathway (disorder-order transition) in allostery, suggesting a complicated role of IDPs/IDRs in regulatory proteins. In addition, an analytic formula for the maximal allosteric coupling response is obtained, which shows that too stable or too unstable state is unfavorable to endow allostery, and is thus helpful for rational design of allosteric drugs.

SUBMITTER: Zhang L

PROVIDER: S-EPMC6292653 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins.

Zhang Luhao L Li Maodong M Liu Zhirong Z

PLoS computational biology 20181203 12

Intrinsically disordered proteins/regions (IDPs/IDRs) are prevalent in allosteric regulation. It was previously thought that intrinsic disorder is favorable for maximizing the allosteric coupling. Here, we propose a comprehensive ensemble model to compare the roles of both order-order transition and disorder-order transition in allosteric effect. It is revealed that the MWC pathway (order-order transition) has a higher probability than the EAM pathway (disorder-order transition) in allostery, su ...[more]

PMID: 30507941

Similar Datasets

Project description:Most models of protein evolution are based upon proteins that form relatively rigid 3D structures. A significant fraction of proteins, the so-called disordered proteins, do not form rigid 3D structures and sample a broad conformational ensemble. Disordered proteins do not typically maintain long-range interactions, so the constraints on their evolution should be different than ordered proteins. To test this hypothesis, we developed and compared models of evolution for disordered and ordered proteins. Substitution matrices were constructed using the sequences of putative homologs for sets of experimentally characterized disordered and ordered proteins. Separate matrices, at three levels of sequence similarity (>85%, 85-60%, and 60-40%), were inferred for each type of protein structure. The substitution matrices for disordered and ordered proteins differed significantly at each level of sequence similarity. The disordered matrices reflected a greater likelihood of evolutionary changes, relative to the ordered matrices, and these changes involved nonconservative substitutions. Glutamic acid and asparagine were interesting exceptions to this result. Important differences between the substitutions that are accepted in disordered proteins relative to ordered proteins were also identified. In general, disordered proteins have fewer evolutionary constraints than ordered proteins. However, some residues like tryptophan and tyrosine are highly conserved in disordered proteins. This is due to their important role in forming protein-protein interfaces. Finally, the amino acid frequencies for disordered proteins, computed during the development of the matrices, were compared with amino acid frequencies for different categories of secondary structure in ordered proteins. The highest correlations were observed between the amino acid frequencies in disordered proteins and the solvent-exposed loops and turns of ordered proteins, supporting an emerging structural model for disordered proteins.

Dataset Information

A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins.

Publications

A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets