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A Comparative Study of ModernHomology Modeling Algorithms forRhodopsin Structure Prediction

机译：现代比较研究同源性建模算法视紫红质的结构预测

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摘要

Rhodopsins are seven α-helical membrane proteins that are of great importance in chemistry, biology, and modern biotechnology. Any in silico study on rhodopsin properties and functioning requires a high-quality three-dimensional structure. Due to particular difficulties with obtaining membrane protein structures from the experiment, in silico prediction of the three-dimensional rhodopsin structure based only on its primary sequence is an especially important task. For the last few years, significant progress was made in the field of protein structure prediction, especially for methods based on comparative modeling. However, the majority of this progress was made for soluble proteins and further investigations are needed to achieve similar progress for membrane proteins. In this paper, we evaluate the performance of modern protein structure prediction methodologies (implemented in the Medeller, I-TASSER, and Rosetta packages) for their ability to predict rhodopsin structures. Three widely used methodologies were considered: two general methodologies that are commonly applied tosoluble proteins and a methodology that uses constraints that arespecific for membrane proteins. The test pool consisted of 36 target-templatepairs with different sequence similarities that was constructed onthe basis of 24 experimental rhodopsin structures taken from the RCSBdatabase. As a result, we showed that all three considered methodologiesallow obtaining rhodopsin structures with the quality that is closeto the crystallographic one (root mean square deviation (RMSD) ofthe predicted structure from the corresponding X-ray structure upto 1.5 Å) if the target-template sequence identity is higherthan 40%. Moreover, all considered methodologies provided structuresof average quality (RMSD < 4.0 Å) if the target-template sequenceidentity is higher than 20%. Such structures can be subsequently usedfor further investigation of molecular mechanisms of protein functioningand for the development of modern protein-based biotechnologies.
机译：视紫红质是七个在化学，生物学和现代生物技术中非常重要的α-螺旋膜蛋白。任何关于视紫红质特性和功能的计算机研究都需要高质量的三维结构。由于从实验中获得膜蛋白结构特别困难，因此仅基于其初级序列的三维视紫红质结构的计算机模拟预测是一项特别重要的任务。在过去的几年中，蛋白质结构预测领域取得了重大进展，特别是基于比较模型的方法。然而，这种进展的大部分是针对可溶性蛋白的，需要进一步研究以实现膜蛋白的相似进展。在本文中，我们评估了现代蛋白质结构预测方法（在Medeller，I-TASSER和Rosetta软件包中实现）的性能，以预测其视紫红质的结构。考虑了三种广泛使用的方法：两种通常用于可溶性蛋白质和使用限制条件的方法膜蛋白特异的测试池由36个目标模板组成对具有不同序列相似性的对RCSB提取的24种视紫红质结构的基础数据库。结果，我们证明了所有三种考虑的方法允许获得具有接近质量的视紫红质结构到晶体学的1（均方根偏差（RMSD）从相应的X射线结构向上预测的结构如果目标模板序列同一性更高，则为1.5Å）超过40％。此外，所有考虑的方法都提供了结构目标模板序列的平均质量（RMSD <4.0Å）身份高于20％。这样的结构可以随后使用进一步研究蛋白质功能的分子机制并发展基于蛋白质的现代生物技术。

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