Geng Cunliang, Narasimhan Siddarth, Rodrigues João P G L M, Bonvin Alexandre M J J
Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Padualaan 8, 3584 CH, Utrecht, The Netherlands.
Department of Structural Biology, Stanford University School of Medicine, 299 Campus Drive, Stanford, CA, 94305, USA.
Methods Mol Biol. 2017;1561:109-138. doi: 10.1007/978-1-4939-6798-8_8.
Modeling protein-peptide interactions remains a significant challenge for docking programs due to the inherent highly flexible nature of peptides, which often adopt different conformations whether in their free or bound forms. We present here a protocol consisting of a hybrid approach, combining the most frequently found peptide conformations in complexes with representative conformations taken from molecular dynamics simulations of the free peptide. This approach intends to broaden the range of conformations sampled during docking. The resulting ensemble of conformations is used as a starting point for information-driven flexible docking with HADDOCK. We demonstrate the performance of this protocol on six cases of increasing difficulty, taken from a protein-peptide benchmark set. In each case, we use knowledge of the binding site on the receptor to drive the docking process. In the majority of cases where MD conformations are added to the starting ensemble for docking, we observe an improvement in the quality of the resulting models.
由于肽固有的高度灵活性，无论是游离形式还是结合形式，肽通常会采用不同的构象，因此对对接程序来说，模拟蛋白质 - 肽相互作用仍然是一项重大挑战。我们在此提出一种由混合方法组成的方案，该方法将复合物中最常见的肽构象与从游离肽的分子动力学模拟中获取的代表性构象相结合。这种方法旨在拓宽对接过程中采样的构象范围。所得的构象集合被用作使用HADDOCK进行信息驱动的灵活对接的起点。我们从蛋白质 - 肽基准集中选取了六个难度逐渐增加的案例来展示该方案的性能。在每个案例中，我们利用受体上结合位点的知识来驱动对接过程。在大多数将MD构象添加到起始集合以进行对接的案例中，我们观察到所得模型的质量有所提高。
