Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland.
International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland.
Int J Mol Sci. 2020 Apr 14;21(8):2713. doi: 10.3390/ijms21082713.
Computational prediction has become an indispensable aid in the processes of engineering and designing proteins for various biotechnological applications. With the tremendous progress in more powerful computer hardware and more efficient algorithms, some of in silico tools and methods have started to apply the more realistic description of proteins as their conformational ensembles, making protein dynamics an integral part of their prediction workflows. To help protein engineers to harness benefits of considering dynamics in their designs, we surveyed new tools developed for analyses of conformational ensembles in order to select engineering hotspots and design mutations. Next, we discussed the collective evolution towards more flexible protein design methods, including ensemble-based approaches, knowledge-assisted methods, and provable algorithms. Finally, we highlighted apparent challenges that current approaches are facing and provided our perspectives on their further development.
计算预测已成为工程和设计各种生物技术应用的蛋白质过程中不可或缺的辅助手段。随着更强大的计算机硬件和更高效算法的巨大进步，一些计算机模拟工具和方法已经开始将蛋白质的更真实描述应用于它们的构象集合，使蛋白质动力学成为其预测工作流程的一个组成部分。为了帮助蛋白质工程师在设计中利用考虑动力学的优势，我们调查了为分析构象集合而开发的新工具，以选择工程热点和设计突变。接下来，我们讨论了朝着更灵活的蛋白质设计方法的集体演变，包括基于集合的方法、知识辅助方法和可证明的算法。最后，我们强调了当前方法所面临的明显挑战，并对它们的进一步发展提出了我们的看法。
