Quantitative proteome-based guidelines for intrinsic disorder characterization

Abstract

Intrinsically disordered proteins fail to adopt a stable three-dimensional structure under physiological conditions. It is now understood that many disordered proteins are not dysfunctional, but instead engage in numerous cellular processes, including signaling and regulation. Disorder characterization from amino acid sequence relies on computational disorder prediction algorithms. While numerous large-scale investigations of disorder have been performed using these algorithms, and have offered valuable insight regarding the prevalence of protein disorder in many organisms, critical proteome-based descriptive statistical guidelines that would enable the objective assessment of intrinsic disorder in a protein of interest remain to be established. Here we present a quantitative characterization of numerous disorder features using a rigorous non-parametric statistical approach, providing expected values and percentile cutoffs for each feature in ten eukaryotic proteomes. Our estimates utilize multiple ab initio disorder prediction algorithms grounded on physicochemical principles. Furthermore, we present novel threshold values, specific to both the prediction algorithms and the proteomes, defining the longest primary sequence length in which the significance of a continuous disordered region can be evaluated on the basis of length alone. The guidelines presented here are intended to improve the interpretation of disorder content and continuous disorder predictions from the proteomic point of view.

Unfoldomics of prostate cancer: on the abundance and roles of intrinsically disordered proteins in prostate cancer

“…One of such approaches is considering roles of intrinsically disordered proteins, or IDPs, which are proteins that lack a stable secondary and tertiary structure and have been shown to constitute a noticeable part of any proteome of interest 3456789101112131415. At the primary sequence level, IDPs are characterized by noticeable compositional biases, being noticeably depleted in order-promoting amino acids (Cys, Trp, Tyr, Phe, Ile, Leu, Val, and Asn) and being found to be enriched with disorder-promoting residues (Pro, Arg, Gly, Gln, Ser, Glu, Lys, and Ala) 3161718.…”

On the Need to Develop Guidelines for Characterizing and Reporting Intrinsic Disorder in Proteins

“…Similar to the mass balance analogy, these predicted values are virtually meaningless in isolation, without standards for comparison that put the measurand into context. To address this problem, we proposed proteome‐based quantitative guidelines for disorder prediction algorithms . These guidelines enable users to evaluate whether a protein is disordered or not with respect to a reference standard—a central measurement (median, mean) for a specified proteome—for comparative purposes.…”

“…Population statistics directly provide the standing of predicted disorder features in a protein of interest (or intrinsically disordered region) relative to the rest of the proteome. A population‐based solution is provided by our quantitative proteome‐based guidelines for reporting and characterizing intrinsic disorder . These guidelines are implemented in a web‐based toolkit, known as Disorder Atlas, that enables users to objectively interpret disorder predictions with respect to the whole proteome.…”

“…These guidelines are implemented in a web‐based toolkit, known as Disorder Atlas, that enables users to objectively interpret disorder predictions with respect to the whole proteome. Disorder Atlas employs a rich user interface that implements pre‐computed disorder predictions together with our previously published disorder interpretation guidelines . As a result, this software further enables users to conduct population‐level analyses of intrinsic disorder regardless of their computational background.…”

Impact of modifying the primary structure of cytoplasmic and membrane proteins of the placenta on the development of its insufficiency

“…Именно в первичной структуре закодирована программа самоорганизации белковой глобулы. Аминокислотный состав белков используется в настоящее время для определения трехмерной (3D) структуры белка, которая определяет основные свойства белковых молекул как в интактных условиях, так и при функциональных изменениях и при патологии [3].…”