A Comparative Study of Modern Homology Modeling Algorithms for Rhodopsin Structure Prediction

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 to soluble proteins and a methodology that uses constraints that are specific for membrane proteins. The test pool consisted of 36 target-template pairs with different sequence similarities that was constructed on the basis of 24 experimental rhodopsin structures taken from the RCSB database. As a result, we showed that all three considered methodologies allow obtaining rhodopsin structures with the quality that is close to the crystallographic one (root mean square deviation (RMSD) of the predicted structure from the corresponding X-ray structure up to 1.5 Å) if the target-template sequence identity is higher than 40%. Moreover, all considered methodologies provided structures of average quality (RMSD < 4.0 Å) if the target-template sequence identity is higher than 20%. Such structures can be subsequently used for further investigation of molecular mechanisms of protein functioning and for the development of modern protein-based biotechnologies.视紫红质（Rhodopsins）是一类七次跨膜α螺旋膜蛋白，在化学、生物学与现代生物技术领域均具有重要研究与应用价值。任何针对视紫红质特性与功能的计算机模拟（in silico）研究，均需依托高质量的三维结构。由于通过实验手段获取膜蛋白结构存在特殊难点，仅基于蛋白质一级序列对其三维结构进行计算机模拟预测，便成为一项尤为关键的研究任务。过去数年来，蛋白质结构预测领域取得了显著进展，尤以基于比较建模（comparative modeling）的相关方法为甚。然而，这类进展大多集中于可溶性蛋白质，针对膜蛋白实现同等水平的突破仍有待进一步探索。本文针对集成于Modeller、I-TASSER及Rosetta软件包中的现代蛋白质结构预测方法，开展了其预测视紫红质结构能力的性能评估。本次研究共考量三种常用方法：两种普遍应用于可溶性蛋白质的通用预测方法，以及一种采用膜蛋白特异性约束条件的专用方法。本次测试的数据集由36个靶标-模板对组成，涵盖不同的序列相似性水平，该数据集基于从RCSB数据库中获取的24个实验解析的视紫红质结构构建而成。研究结果表明，当靶标-模板序列同一性高于40%时，上述三种方法均可获得与晶体结构质量相近的视紫红质预测结构——预测结构与对应X射线晶体结构的均方根偏差（root mean square deviation, RMSD）不超过1.5 Å。此外，当靶标-模板序列同一性高于20%时，所有受试方法均可获得中等质量的预测结构（RMSD < 4.0 Å）。这类结构后续可用于进一步解析蛋白质功能的分子机制，以及开发基于蛋白质的现代生物技术。