Ovchinnikov Sergey, Park Hahnbeom, Kim David E, DiMaio Frank, Baker David
Department of Biochemistry, University of Washington, Seattle, Washington.
Institute for Protein Design, University of Washington, Seattle, Washington.
Proteins. 2018 Mar;86 Suppl 1(Suppl 1):113-121. doi: 10.1002/prot.25390. Epub 2017 Oct 8.
We describe several notable aspects of our structure predictions using Rosetta in CASP12 in the free modeling (FM) and refinement (TR) categories. First, we had previously generated (and published) models for most large protein families lacking experimentally determined structures using Rosetta guided by co-evolution based contact predictions, and for several targets these models proved better starting points for comparative modeling than any known crystal structure-our model database thus starts to fulfill one of the goals of the original protein structure initiative. Second, while our "human" group simply submitted ROBETTA models for most targets, for six targets expert intervention improved predictions considerably; the largest improvement was for T0886 where we correctly parsed two discontinuous domains guided by predicted contact maps to accurately identify a structural homolog of the same fold. Third, Rosetta all atom refinement followed by MD simulations led to consistent but small improvements when starting models were close to the native structure, and larger but less consistent improvements when starting models were further away.
我们描述了在第12届蛋白质结构预测关键评估(CASP12)中,我们使用Rosetta在自由建模(FM)和精修(TR)类别下进行结构预测的几个显著方面。首先,我们之前已经使用基于协同进化的接触预测指导下的Rosetta,为大多数缺乏实验确定结构的大型蛋白质家族生成(并发表)了模型,对于几个目标,这些模型被证明是比任何已知晶体结构更好的比较建模起点——我们的模型数据库因此开始实现原始蛋白质结构计划的目标之一。其次,虽然我们的“人类”团队为大多数目标简单提交了ROBETTA模型,但对于六个目标,专家干预显著改善了预测;最大的改进是针对T0886,在那里我们通过预测的接触图正确解析了两个不连续的结构域,以准确识别相同折叠的结构同源物。第三,当起始模型接近天然结构时,Rosetta全原子精修后进行分子动力学模拟导致了一致但较小的改进,而当起始模型距离较远时,改进较大但不太一致。