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DeepConPred2:一种预测蛋白质残基接触的改进方法。

DeepConPred2: An Improved Method for the Prediction of Protein Residue Contacts.

作者信息

Ding Wenze, Mao Wenzhi, Shao Di, Zhang Wenxuan, Gong Haipeng

机构信息

MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China.

Beijing Innovation Center of Structural Biology, Tsinghua University, Beijing 100084, China.

出版信息

Comput Struct Biotechnol J. 2018 Nov 10;16:503-510. doi: 10.1016/j.csbj.2018.10.009. eCollection 2018.

Abstract

Information of residue-residue contacts is essential for understanding the mechanism of protein folding, and has been successfully applied as special topological restraints to simplify the conformational sampling in de novo protein structure prediction. Prediction of protein residue contacts has experienced amazingly rapid progresses recently, with prediction accuracy approaching impressively high levels in the past two years. In this work, we introduce a second version of our residue contact predictor, DeepConPred2, which exhibits substantially improved performance and sufficiently reduced running time after model re-optimization and feature updates. When testing on the CASP12 free modeling targets, our program reaches at least the same level of prediction accuracy as the best contact predictors so far and provides information complementary to other state-of-the-art methods in contact-assisted folding.

摘要

残基-残基接触信息对于理解蛋白质折叠机制至关重要,并且已成功用作特殊的拓扑约束,以简化从头蛋白质结构预测中的构象采样。蛋白质残基接触预测最近取得了惊人的快速进展,在过去两年中预测准确率达到了令人印象深刻的高水平。在这项工作中,我们推出了残基接触预测器的第二个版本DeepConPred2,经过模型重新优化和特征更新后,其性能有了显著提高,运行时间也大幅缩短。在对CASP12自由建模目标进行测试时,我们的程序达到了至少与目前最佳接触预测器相同的预测准确率水平,并在接触辅助折叠方面提供了与其他现有方法互补的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72d9/6247404/becf099d3725/gr1.jpg

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