前和后alphafold时代的生物分子相互作用预测:第八次CAPRI评价。

IF 2.8 4区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Marc F Lensink, Nessim Raouraoua, Guillaume Brysbaert, Sameer Velankar, Shoshana J Wodak, Alexandre M J J Bonvin
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引用次数: 0

摘要

我们报告了第8次CAPRI评估期,记录了CAPRI第47轮至第55轮(不包括CASP和与covid相关的轮)的评估,这些轮见证了向人工智能驱动的预测工具(如AlphaFold和相关替代方案)的过渡。由于各种因素,包括目标的性质、待预测界面的复杂性和构象变化,本评估中的预测轮具有很高的难度。共评估了11个目标,包括21个界面,其中大部分属于难以预测的类别。虽然回顾性分析显示AlphaFold在这些目标上表现出色,但人类预测在困难的目标上仍然优于人工智能,特别是那些涉及抗体和核酸的目标。在其诞生近25年后,CAPRI仍然是一个充满活力和协作的倡议,大约有50个预测器和评分组以及10个服务器积极参与。为盲实验提供目标的实验人员的持续贡献,以及人工智能、采样策略和评分方法的进一步进步,将是克服复杂生物分子系统中剩余的结构预测挑战的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biomolecular Interaction Prediction in the Pre- and Post-AlphaFold Era: The 8th CAPRI Evaluation.

We report on the 8th CAPRI Evaluation period, capturing the assessment of CAPRI Rounds 47 to 55 (excluding the CASP and COVID-related Rounds), which have witnessed the transition to AI-driven prediction tools such as AlphaFold and related alternatives. The prediction Rounds in this evaluation are characterized by a high level of difficulty due to various factors, including the nature of the targets, the intricacy of the interfaces to be predicted, and conformational changes. A total of 11 targets encompassing 21 interfaces, mostly in the difficult prediction category, were evaluated. While a retrospective analysis reveals a strong performance of AlphaFold on those targets, human predictors still outperform AI on difficult targets, particularly those involving antibodies and nucleic acids. Almost 25 years after its birth, CAPRI remains a vibrant and collaborative initiative with active participation from approximately 50 predictor and scorer groups and 10 servers. Continued contributions from experimentalists providing targets to such blind experiments, and further advances in AI, sampling strategies, and improvement in scoring methods will be key to overcoming remaining structural prediction challenges in complex biomolecular systems.

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来源期刊
Proteins-Structure Function and Bioinformatics
Proteins-Structure Function and Bioinformatics 生物-生化与分子生物学
CiteScore
5.90
自引率
3.40%
发文量
172
审稿时长
3 months
期刊介绍: PROTEINS : Structure, Function, and Bioinformatics publishes original reports of significant experimental and analytic research in all areas of protein research: structure, function, computation, genetics, and design. The journal encourages reports that present new experimental or computational approaches for interpreting and understanding data from biophysical chemistry, structural studies of proteins and macromolecular assemblies, alterations of protein structure and function engineered through techniques of molecular biology and genetics, functional analyses under physiologic conditions, as well as the interactions of proteins with receptors, nucleic acids, or other specific ligands or substrates. Research in protein and peptide biochemistry directed toward synthesizing or characterizing molecules that simulate aspects of the activity of proteins, or that act as inhibitors of protein function, is also within the scope of PROTEINS. In addition to full-length reports, short communications (usually not more than 4 printed pages) and prediction reports are welcome. Reviews are typically by invitation; authors are encouraged to submit proposed topics for consideration.
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