Brylinski Michal
Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.
BMC Res Notes. 2013 Jul 31;6:303. doi: 10.1186/1756-0500-6-303.
Many structural bioinformatics approaches employ sequence profile-based threading techniques. To improve fold recognition rates, homology searching may include artificially evolved amino acid sequences, which were demonstrated to enhance the sensitivity of protein threading in targeting midnight zone templates.
We describe implementation details of eVolver, an optimization algorithm that evolves protein sequences to stabilize the respective structures by a variety of potentials, which are compatible with those commonly used in protein threading. In a case study focusing on LARG PDZ domain, we show that artificially evolved sequences have quite high capabilities to recognize the correct protein structures using standard sequence profile-based fold recognition.
Computationally design protein sequences can be incorporated in existing sequence profile-based threading approaches to increase their sensitivity. They also provide a desired linkage between protein structure and function in in silico experiments that relate to e.g. the completeness of protein structure space, the origin of folds and protein universe. eVolver is freely available as a user-friendly webserver and a well-documented stand-alone software distribution at http://www.brylinski.org/evolver.
许多结构生物信息学方法采用基于序列谱的穿线技术。为提高折叠识别率，同源性搜索可能包括人工进化的氨基酸序列，已证明这些序列可提高蛋白质穿线针对午夜区模板的敏感性。
我们描述了eVolver的实现细节，eVolver是一种优化算法，通过多种势能来进化蛋白质序列以稳定各自的结构，这些势能与蛋白质穿线中常用的势能兼容。在一项针对LARG PDZ结构域的案例研究中，我们表明，使用基于标准序列谱的折叠识别方法，人工进化的序列具有相当高的识别正确蛋白质结构的能力。
通过计算设计的蛋白质序列可纳入现有的基于序列谱的穿线方法中以提高其敏感性。它们还在与例如蛋白质结构空间的完整性、折叠的起源和蛋白质宇宙相关的计算机实验中提供了蛋白质结构与功能之间所需的联系。eVolver可作为用户友好的网络服务器免费获取，并且在http://www.brylinski.org/evolver上有文档完善的独立软件发行版。
