Pyrkov T V, Priestle J P, Jacoby E, Efremov R G
MM Shemyakin & Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.
SAR QSAR Environ Res. 2008 Jan-Mar;19(1-2):91-9. doi: 10.1080/10629360701844092.
Molecular docking is a powerful computational method that has been widely used in many biomolecular studies to predict geometry of a protein-ligand complex. However, while its conformational search algorithms are usually able to generate correct conformation of a ligand in the binding site, the scoring methods often fail to discriminate it among many false variants. We propose to treat this problem by applying more precise ligand-specific scoring filters to re-rank docking solutions. In this way specific features of interactions between protein and different types of compounds can be implicitly taken into account. New scoring functions were constructed including hydrogen bonds, hydrophobic and hydrophilic complementarity terms. These scoring functions also discriminate ligands by the size of the molecule, the total hydrophobicity, and the number of peptide bonds for peptide ligands. Weighting coefficients of the scoring functions were adjusted using a training set of 60 protein-ligand complexes. The proposed method was then tested on the results of docking obtained for an additional 70 complexes. In both cases the success rate was 5-8% better compared to the standard functions implemented in popular docking software.
分子对接是一种强大的计算方法，已广泛应用于许多生物分子研究中，以预测蛋白质-配体复合物的几何结构。然而，虽然其构象搜索算法通常能够在结合位点生成配体的正确构象，但评分方法往往无法在众多错误变体中区分出正确的构象。我们建议通过应用更精确的配体特异性评分过滤器对对接解决方案进行重新排序来解决这个问题。通过这种方式，可以隐式地考虑蛋白质与不同类型化合物之间相互作用的特定特征。构建了新的评分函数，包括氢键、疏水和亲水互补项。这些评分函数还根据分子大小、总疏水性以及肽配体的肽键数量来区分配体。使用包含60个蛋白质-配体复合物的训练集调整评分函数的加权系数。然后在所获得的另外70个复合物的对接结果上测试了所提出的方法。在这两种情况下，与流行对接软件中实现的标准函数相比，成功率提高了5-8%。
