Kolinski Andrzej
Faculty of Chemistry, Warsaw University, Warszawa, Poland.
Acta Biochim Pol. 2004;51(2):349-71.
Protein modeling could be done on various levels of structural details, from simplified lattice or continuous representations, through high resolution reduced models, employing the united atom representation, to all-atom models of the molecular mechanics. Here I describe a new high resolution reduced model, its force field and applications in the structural proteomics. The model uses a lattice representation with 800 possible orientations of the virtual alpha carbon-alpha carbon bonds. The sampling scheme of the conformational space employs the Replica Exchange Monte Carlo method. Knowledge-based potentials of the force field include: generic protein-like conformational biases, statistical potentials for the short-range conformational propensities, a model of the main chain hydrogen bonds and context-dependent statistical potentials describing the side group interactions. The model is more accurate than the previously designed lattice models and in many applications it is complementary and competitive in respect to the all-atom techniques. The test applications include: the ab initio structure prediction, multitemplate comparative modeling and structure prediction based on sparse experimental data. Especially, the new approach to comparative modeling could be a valuable tool of the structural proteomics. It is shown that the new approach goes beyond the range of applicability of the traditional methods of the protein comparative modeling.
蛋白质建模可以在不同层次的结构细节上进行，从简化的晶格或连续表示，到采用联合原子表示的高分辨率简化模型，再到分子力学的全原子模型。在此，我描述一种新的高分辨率简化模型、其力场以及在结构蛋白质组学中的应用。该模型使用一种晶格表示，其中虚拟的α-碳-碳α键有800种可能的取向。构象空间的采样方案采用复制交换蒙特卡罗方法。基于知识的力场势能包括：类蛋白质的一般构象偏差、短程构象倾向的统计势能、主链氢键模型以及描述侧链基团相互作用的上下文相关统计势能。该模型比先前设计的晶格模型更精确，并且在许多应用中，相对于全原子技术，它具有互补性和竞争力。测试应用包括：从头算结构预测、多模板比较建模以及基于稀疏实验数据的结构预测。特别是，新的比较建模方法可能成为结构蛋白质组学的一个有价值的工具。结果表明，新方法超出了传统蛋白质比较建模方法的适用范围。
