MobiDB-lite 4.0：更快地预测蛋白质内在无序性和结构紧凑性

MobiDB-lite 4.0: faster prediction of intrinsic protein disorder and structural compactness.

作者信息

Mehdiabadi Mahta, Blum Matthias, Tesei Giulio, von Bülow Sören, Lindorff-Larsen Kresten, Tosatto Silvio C E, Piovesan Damiano

机构信息

Department of Biomedical Sciences, University of Padova, 35131 Padova, Italy.

European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom.

出版信息

Bioinformatics. 2025 May 6;41(5). doi: 10.1093/bioinformatics/btaf297.

DOI:10.1093/bioinformatics/btaf297

PMID:40347452

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12122076/

Abstract

MOTIVATION

In recent years, many disorder predictors have been developed to identify intrinsically disordered regions (IDRs) in proteins, achieving high accuracy. However, it may be difficult to interpret differences in predictions across methods. Consensus methods offer a simple solution, highlighting reliable predictions while filtering out uncertain positions. Here, we present a new version of MobiDB-lite, a consensus method designed to predict long IDRs and classify them based on compositional biases and conformational properties.

RESULTS

MobiDB-lite 4.0 pipeline was optimized to be ten times faster than the previous version. It now provides compactness annotations based on predicted apparent scaling exponent. The newly added features and disorder subclassifications allow the users to get a comprehensive insight into the protein's function and characteristics. MobiDB-lite 4.0 is integrated into the MobiDB and DisProt databases. A version without the compactness predictor is integrated into InterProScan, propagating MobiDB-lite annotations to UniProtKB.

AVAILABILITY AND IMPLEMENTATION

The MobiDB-lite 4.0 source code and a Docker container are available from the GitHub repository: https://github.com/BioComputingUP/MobiDB-lite.

摘要

动机

近年来，已开发出许多无序预测器来识别蛋白质中的内在无序区域（IDR），并取得了很高的准确率。然而，不同方法之间的预测差异可能难以解释。共识方法提供了一个简单的解决方案，突出可靠的预测，同时过滤掉不确定的位置。在此，我们展示了新版本的MobiDB-lite，这是一种共识方法，旨在预测长IDR，并根据组成偏差和构象特性对其进行分类。

结果

MobiDB-lite 4.0流程经过优化，速度比上一版本快十倍。它现在基于预测的表观标度指数提供紧凑性注释。新添加的功能和无序子分类使用户能够全面了解蛋白质的功能和特性。MobiDB-lite 4.0已集成到MobiDB和DisProt数据库中。一个没有紧凑性预测器的版本已集成到InterProScan中，将MobiDB-lite注释传播到UniProtKB。