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利用扭转角动力学和预测的约束条件对螺旋蛋白进行折叠预测。

Fold prediction of helical proteins using torsion angle dynamics and predicted restraints.

作者信息

Zhang Chao, Hou Jingtong, Kim Sung-Hou

机构信息

Department of Chemistry and E. O. Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA.

出版信息

Proc Natl Acad Sci U S A. 2002 Mar 19;99(6):3581-5. doi: 10.1073/pnas.052003799.

Abstract

We describe a procedure for predicting the tertiary folds of alpha-helical proteins from their primary sequences. The central component of the procedure is a method for predicting interhelical contacts that is based on a helix-packing model. Instead of predicting the individual contacts, our method attempts to identify the entire patch of contacts that involve residues regularly spaced in the sequences. We use this component to glue together two powerful existing methods: a secondary structure prediction program, whose output serves as the input to the contact prediction algorithm, and the tortion angle dynamics program, which uses the predicted tertiary contacts and secondary structural states to assemble three-dimensional structures. In the final step, the procedure uses the initial set of simulated structures to refine the predicted contacts for a new round of structure calculation. When tested against 24 small to medium-sized proteins representing a wide range of helical folds, the completely automated procedure is able to generate native-like models within a limited number of trials consistently.

摘要

我们描述了一种从α-螺旋蛋白的一级序列预测其三级结构的方法。该方法的核心部分是一种基于螺旋堆积模型预测螺旋间接触的方法。我们的方法不是预测单个接触,而是尝试识别涉及序列中规则间隔残基的整个接触区域。我们使用该组件将两种强大的现有方法结合在一起:一种二级结构预测程序,其输出作为接触预测算法的输入;以及扭转角动力学程序,该程序使用预测的三级接触和二级结构状态来组装三维结构。在最后一步中,该方法使用初始的模拟结构集来优化预测的接触,以进行新一轮的结构计算。当针对代表广泛螺旋折叠的24个中小型蛋白质进行测试时,这个完全自动化的方法能够在有限次数的试验中始终生成类似天然结构的模型。

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