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使用PconsC4和PconsFold2预测蛋白质结构。

Using PconsC4 and PconsFold2 to Predict Protein Structure.

作者信息

Bassot Claudio, Menendez Hurtado David, Elofsson Arne

机构信息

Department of Biochemistry and Biophysics, Stockholm University and Science for Life Laboratory, Solna, Sweden.

出版信息

Curr Protoc Bioinformatics. 2019 Jun;66(1):e75. doi: 10.1002/cpbi.75. Epub 2019 May 7.

Abstract

In spite of the fact that there has been a significant increase in the number of solved protein structures, structural information is missing for many proteins. Although structural information is codified in the amino acid sequence, computational prediction using only this information is still an unsolved problem. However, one successful method to model a protein's structure starting from the primary sequence is to use contact prediction derived from multiple sequence alignment (MSA). Here we use our contact predictor PconsC4 to generate a list of probable contacts between residues in the primary sequences. These contacts are then used together with the secondary structure prediction as constraints for the CONFOLD folding method. In this way, a 3D protein model can be built starting directly from the primary sequence. © 2019 by John Wiley & Sons, Inc.

摘要

尽管已解析的蛋白质结构数量显著增加,但许多蛋白质仍缺少结构信息。虽然结构信息编码在氨基酸序列中,但仅使用此信息进行计算预测仍是一个未解决的问题。然而,一种从一级序列开始构建蛋白质结构模型的成功方法是使用从多序列比对(MSA)得出的接触预测。在这里,我们使用我们的接触预测器PconsC4来生成一级序列中残基之间可能的接触列表。然后,这些接触与二级结构预测一起用作CONFOLD折叠方法的约束条件。通过这种方式,可以直接从一级序列构建三维蛋白质模型。© 2019约翰威立父子公司版权所有。

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