Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
J Comput Chem. 2010 Jul 15;31(9):1911-8. doi: 10.1002/jcc.21478.
We present a Lamarckian genetic algorithm (LGA) variant for flexible ligand-receptor docking which allows to handle a large number of degrees of freedom. Our hybrid method combines a multi-deme LGA with a recently published gradient-based method for local optimization of molecular complexes. We compared the performance of our new hybrid method to two non gradient-based search heuristics on the Astex diverse set for flexible ligand-receptor docking. Our results show that the novel approach is clearly superior to other LGAs employing a stochastic optimization method. The new algorithm features a shorter run time and gives substantially better results, especially with increasing complexity of the ligands. Thus, it may be used to dock ligands with many rotatable bonds with high efficiency.
我们提出了一种拉马克遗传算法(LGA)变体,用于灵活的配体-受体对接,该变体可以处理大量自由度。我们的混合方法将多群体 LGA 与最近发表的基于梯度的方法相结合,用于分子复合物的局部优化。我们将新混合方法的性能与两种非基于梯度的搜索启发式方法在 Astex 多样的柔性配体-受体对接数据集上进行了比较。结果表明,该新方法明显优于其他采用随机优化方法的 LGAs。该新算法具有更短的运行时间,并能获得更好的结果,特别是在配体的复杂性增加时更是如此。因此,它可以用于高效地对接具有许多可旋转键的配体。