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阐明“混沌地带”:困难蛋白建模的进展。

Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling.

机构信息

Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Laboratory, Medical University of Lublin, Lublin, Poland.

University of Eastern Finland, School of Pharmacy, Kuopio, Finland.

出版信息

Methods Mol Biol. 2023;2627:25-40. doi: 10.1007/978-1-0716-2974-1_2.

Abstract

Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The threshold value was long assumed to be around 20-30%. Below this level, obtained sequence identity was getting dangerously close to values that can be obtained by chance, after aligning any random, unrelated sequences. In these cases, other approaches, including ab initio folding simulations or fragment assembly, were usually employed. The most recent editions of the CASP and CAMEO community-wide modeling methods assessment have brought some surprising outcomes, proving that much more clues can be inferred from protein sequence analyses than previously thought. In this chapter, we focus on recent advances in the field of difficult protein modeling, pushing the threshold deep into the "twilight zone", with particular attention devoted to improvements in applications of machine learning and model evaluation.

摘要

同源建模长期以来被认为是预测蛋白质三级结构的首选方法。然而,过去只有在能够找到与目标具有显著序列同一性的模板时,才能提供具有可接受质量的模型。该阈值长期以来被认为在 20-30%左右。在这个水平以下,获得的序列同一性已经非常接近通过对齐任何随机的、不相关的序列偶然获得的同一性。在这些情况下,通常采用其他方法,包括从头折叠模拟或碎片组装。最近的 CASP 和 CAMEO 社区建模方法评估版本带来了一些令人惊讶的结果,证明从蛋白质序列分析中可以推断出比以前更多的线索。在本章中,我们专注于困难蛋白质建模领域的最新进展,将阈值推向“黄昏地带”,特别关注机器学习和模型评估应用的改进。

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