Meng E C, Gschwend D A, Blaney J M, Kuntz I D
Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco 94143-0446.
Proteins. 1993 Nov;17(3):266-78. doi: 10.1002/prot.340170305.
The biological activities of proteins depend on specific molecular recognition and binding. Computational methods for predicting binding modes can facilitate the discovery and design of ligands and yield information on the factors governing complementarity. The DOCK suite of programs has been applied to several systems; here, the degree of orientational sampling required to reproduce and identify known binding modes, with and without rigid-body energy minimization, is investigated for four complexes. There is a tradeoff between sampling and minimization. The known binding modes can be identified with intensive sampling alone (10,000 to 20,000 orientations generated per system) or with moderate sampling combined with minimization. Optimization improves energies significantly, particularly when steric clashes are present, and brings many orientations closer to the experimentally observed position. Whether or not minimization is performed, however, sampling must be sufficient to find at least one structure in the vicinity of the presumed true binding mode. Hybrid approaches combining docking and minimization are promising and will become more viable with the use of faster algorithms and the judicious selection of fewer orientations for minimization.
蛋白质的生物活性取决于特定的分子识别和结合。预测结合模式的计算方法有助于配体的发现与设计，并提供有关互补性控制因素的信息。DOCK程序套件已应用于多个系统；在此，针对四种复合物研究了在有无刚体能量最小化的情况下，重现和识别已知结合模式所需的取向采样程度。在采样和最小化之间存在权衡。已知的结合模式可以仅通过密集采样（每个系统生成10,000至20,000个取向）或通过适度采样与最小化相结合来识别。优化可显著提高能量，尤其是在存在空间冲突的情况下，并使许多取向更接近实验观察到的位置。然而，无论是否进行最小化，采样都必须足够，以便在假定的真实结合模式附近找到至少一种结构。结合对接和最小化的混合方法很有前景，并且随着更快算法的使用以及为最小化明智地选择更少的取向，将变得更加可行。
