在CAPRI第38 - 45轮中使用GALAXY进行生物组装体的结构预测

Taeyong Park, Hyeonuk Woo, M. Baek, Jinsol Yang, Chaok Seok
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引用次数: 3

摘要

我们作为服务器预测者和人类预测者参加了CARPI第38 - 45轮研究。这些CAPRI轮次为测试三类蛋白质相互作用的预测方法提供了极好的机会,即蛋白质-蛋白质,蛋白质-肽和蛋白质-低聚糖相互作用。基于模板的方法(用于单体蛋白的GalaxyTBM,用于同源寡聚蛋白的GalaxyHomomer,用于蛋白-肽复合物的GalaxyPepDock)和从头算对接方法(用于蛋白寡聚物的GalaxyTongDock和GalaxyPPDock,用于蛋白-肽复合物的GalaxyPepDock‐ab‐initio,用于蛋白-寡糖复合物的GalaxyDock2和Galaxy7TM)已经进行了测试。基于模板的方法在很大程度上依赖于合适模板的可用性和模板-目标的相似性,而模板-目标的差异是导致基于模板的模型不准确的原因。我们的基于物理能量优化(GalaxyRefineComplex和GalaxyLoop)的结构精化和循环建模方法可以改善基于模板的不准确模型。目前的从头算对接方法需要精确的蛋白质结构作为输入。我们的对接方法可以解释输入结构的小构象变化,从而为几个CAPRI目标产生最佳模型之一。然而,预测涉及蛋白质骨架的大构象变化仍然具有挑战性,并且基于物理的方法的全面探索仍然需要到来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structure prediction of biological assemblies using GALAXY in CAPRI rounds 38‐45
We participated in CARPI rounds 38‐45 both as a server predictor and a human predictor. These CAPRI rounds provided excellent opportunities for testing prediction methods for three classes of protein interactions, that is, protein‐protein, protein‐peptide, and protein‐oligosaccharide interactions. Both template‐based methods (GalaxyTBM for monomer protein, GalaxyHomomer for homo‐oligomer protein, GalaxyPepDock for protein‐peptide complex) and ab initio docking methods (GalaxyTongDock and GalaxyPPDock for protein oligomer, GalaxyPepDock‐ab‐initio for protein‐peptide complex, GalaxyDock2 and Galaxy7TM for protein‐oligosaccharide complex) have been tested. Template‐based methods depend heavily on the availability of proper templates and template‐target similarity, and template‐target difference is responsible for inaccuracy of template‐based models. Inaccurate template‐based models could be improved by our structure refinement and loop modeling methods based on physics‐based energy optimization (GalaxyRefineComplex and GalaxyLoop) for several CAPRI targets. Current ab initio docking methods require accurate protein structures as input. Small conformational changes from input structure could be accounted for by our docking methods, producing one of the best models for several CAPRI targets. However, predicting large conformational changes involving protein backbone is still challenging, and full exploration of physics‐based methods for such problems is still to come.
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