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首页> 外文会议>Evolutionary Computation (CEC), 2012 IEEE Congress on >Protein structure prediction based on optimal hydrophobic core formation
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Protein structure prediction based on optimal hydrophobic core formation

机译：基于最佳疏水核形成的蛋白质结构预测

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摘要

The prediction of a minimum energy protein structure from its amino acid sequence represents an important and challenging problem in computational biology. In this paper, we propose a novel heuristic approach for protein structure prediction (PSP) based on the concept of optimal hydrophobic core formation. Using 2D HP model, a well-known set of sub-structures analogous to the secondary structures are obtained. Some sub-conformations are appropriately classified and then incorporated as prior knowledge. Unlike most of the popular PSP approaches which are stochastic in nature, the proposed method is deterministic. The effectiveness of the proposed algorithm is evaluated by well-known benchmark as well as non-benchmark sequences commonly used with 2D HP model. Maintaining similar accuracy as other core based and population based algorithms our method is significantly faster and reduces the computation time as it avoids blind search within the hydrophobic core (H-Core).
机译：从其氨基酸序列预测最小能量蛋白质结构代表了计算生物学中一个重要且具有挑战性的问题。在本文中，我们基于最佳疏水性核心形成的概念，提出了一种用于蛋白质结构预测（PSP）的新颖启发式方法。使用2D HP模型，可以获得类似于二级结构的一组著名的子结构。一些子构象被适当地分类，然后被合并为先验知识。与自然界中大多数流行的PSP方法不同，该方法具有确定性。该算法的有效性通过众所周知的基准以及二维HP模型常用的非基准序列进行评估。保持与其他基于核和基于种群的算法相似的准确性，我们的方法明显更快，并减少了计算时间，因为它避免了在疏水核（H-Core）中进行盲目搜索。

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