Eisenmenger F, Argos P, Abagyan R
European Molecular Biology Laboratory, Heidelberg, Germany.
J Mol Biol. 1993 Jun 5;231(3):849-60. doi: 10.1006/jmbi.1993.1331.
Protein homology modelling typically involves the prediction of side-chain conformations in the modelled protein while assuming a main-chain trace taken from a known tertiary structure of a protein with homologous sequence. It is generally believed that the need to examine all possible combinations of side-chain conformations poses the major obstacle to accurate homology modelling. Methods proposed heretofore use only discrete or limited searches of the side-chain torsion angle space to mitigate the combinatorial problem and also rely on simplified energy functions for calculational speed. The configurational constraints are typically based upon use of frequently observed torsion angles, fixed steps in torsion angles, or oligopeptide segments taken from tertiary structural databanks that are similar in sequence and conformation with the target structure. In the present work, a more fundamental approach is explored for several protein structures and it is demonstrated that the combinatorial barrier in side-chain placement hardly exists. Each side-group can be configured individually in the environment of only the backbone atoms using a systematic search procedure combined with extensive local energy minimization. Tests, using the main-chain or both the main-chain and remaining side-chain atoms to calculate low energy geometries for each residue, established the dominance of the main-chain contribution. The final structure is achieved by combining the individually placed side-chains followed by a full energy refinement of the structure. The prediction accuracy of the present homology modelling technique was assessed relative to other automated procedures and was found to yield improved predictions relative to the known side-chain conformations determined by X-ray crystallography.
蛋白质同源建模通常涉及在假定主链轨迹取自具有同源序列的蛋白质已知三级结构的情况下,预测建模蛋白质中的侧链构象。人们普遍认为,检查侧链构象的所有可能组合的必要性构成了精确同源建模的主要障碍。迄今为止提出的方法仅对侧链扭转角空间进行离散或有限搜索以减轻组合问题,并且还依赖于简化的能量函数以提高计算速度。构型约束通常基于使用频繁观察到的扭转角、扭转角的固定步长或取自三级结构数据库的寡肽片段,这些片段在序列和构象上与目标结构相似。在本工作中,针对几种蛋白质结构探索了一种更基本的方法,结果表明在侧链放置中几乎不存在组合障碍。每个侧基可以在仅主链原子的环境中使用系统搜索程序并结合广泛的局部能量最小化来单独配置。使用主链或主链和其余侧链原子来计算每个残基的低能几何结构的测试,确定了主链贡献的主导地位。通过组合单独放置的侧链,然后对结构进行全能量优化来获得最终结构。相对于其他自动化程序评估了本同源建模技术的预测准确性,发现相对于通过X射线晶体学确定的已知侧链构象,该技术产生了改进的预测。