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ModFOLD9:一个用于独立估计 3D 蛋白质模型质量的网络服务器。

ModFOLD9: A Web Server for Independent Estimates of 3D Protein Model Quality.

机构信息

School of Biological Sciences, University of Reading, UK.

School of Biological Sciences, University of Reading, UK.

出版信息

J Mol Biol. 2024 Sep 1;436(17):168531. doi: 10.1016/j.jmb.2024.168531. Epub 2024 Mar 11.

DOI:10.1016/j.jmb.2024.168531
PMID:39237204
Abstract

Accurate models of protein tertiary structures are now available from numerous advanced prediction methods, although the accuracy of each method often varies depending on the specific protein target. Additionally, many models may still contain significant local errors. Therefore, reliable, independent model quality estimates are essential both for identifying errors and selecting the very best models for further biological investigations. ModFOLD9 is a leading independent server for detecting the local errors in models produced by any method, and it can accurately discriminate between high-quality models from multiple alternative approaches. ModFOLD9 incorporates several new scores from deep learning-based approaches, leading to greatly improved prediction accuracy compared with earlier versions of the server. ModFOLD9 is continuously independently benchmarked, and it is shown to be highly competitive with other public servers. ModFOLD9 is freely available at https://www.reading.ac.uk/bioinf/ModFOLD/.

摘要

现在有许多先进的预测方法可以提供准确的蛋白质三级结构模型,尽管每种方法的准确性通常取决于特定的蛋白质靶标。此外,许多模型可能仍然存在显著的局部错误。因此,可靠的、独立的模型质量评估对于识别错误和选择最适合进一步生物学研究的最佳模型至关重要。ModFOLD9 是一个领先的独立服务器,用于检测任何方法生成的模型中的局部错误,并且它可以准确地区分来自多种替代方法的高质量模型。ModFOLD9 结合了几种基于深度学习的新方法的评分,与服务器的早期版本相比,预测准确性有了显著提高。ModFOLD9 不断进行独立基准测试,与其他公共服务器相比具有高度竞争力。ModFOLD9 可免费在 https://www.reading.ac.uk/bioinf/ModFOLD/ 获取。

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