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从头算蛋白质结构预测的原理、挑战与进展

Principles, challenges and advances in ab initio protein structure prediction.

作者信息

Jothi Arunachalam

机构信息

Department of Bioinformatics, SCBT, SASTRA University, Thanjavur, India.

出版信息

Protein Pept Lett. 2012 Nov;19(11):1194-204. doi: 10.2174/092986612803217015.

Abstract

The gap between known protein sequences and structures is increasing rapidly and experimental methods alone will not be able to fill in this gap. Therefore it is necessary to use computational methods to predict protein structures. Template based modeling methods could be used for sequences, which have detectable relationship with sequences of one or more experimentally determined protein structures. For predicting the structure of proteins, which does not share a detectable sequence relationship with experimental structures, ab initio protein structure prediction techniques must be used. The methods under ab initio protein structure prediction category aim to predict the structure of a protein from the sequence information alone, without any explicit use of previously known structures. These methods use thermodynamic principles and try to identify the native structure of a protein as the global minimum of a potential energy landscape. However, such methods are computationally complex and are extraordinarily challenging. There has been significant progress in the development of ab inito protein structure prediction methods over the past few years. This review describes the basic principles, the complexity, challenges and recent progresses of ab initio protein structure prediction.

摘要

已知蛋白质序列与结构之间的差距正在迅速扩大,仅靠实验方法无法填补这一差距。因此,有必要使用计算方法来预测蛋白质结构。基于模板的建模方法可用于与一个或多个实验确定的蛋白质结构序列具有可检测关系的序列。对于预测与实验结构不具有可检测序列关系的蛋白质结构,必须使用从头算蛋白质结构预测技术。从头算蛋白质结构预测类别下的方法旨在仅根据序列信息预测蛋白质的结构,而不明确使用先前已知的结构。这些方法利用热力学原理,试图将蛋白质的天然结构识别为势能景观的全局最小值。然而,此类方法计算复杂,极具挑战性。在过去几年中,从头算蛋白质结构预测方法取得了重大进展。本综述描述了从头算蛋白质结构预测的基本原理、复杂性、挑战和最新进展。

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