Hetényi Csaba, Maran Uko, Karelson Mati
Department of Chemistry, Tartu University, 2 Jakobi Street, 51014 Tartu, Estonia.
J Chem Inf Comput Sci. 2003 Sep-Oct;43(5):1576-83. doi: 10.1021/ci034052u.
Generally, computer-aided drug design is focused on screening of ligand molecules for a single protein target. The screening of several proteins for a ligand is a relatively new application of molecular docking. In the present study, complexes from the Brookhaven Protein Databank were used to investigate a docking approach of protein screening. Automated molecular docking calculations were applied to reproduce 44 protein-aromatic ligand complexes (31 different proteins and 39 different ligand molecules) of the databank. All ligands were docked to all different protein targets in altogether 12090 docking runs. Based on the results of the extensive docking simulations, two relative measures, the molecular interaction fingerprint (MIF) and the molecular affinity fingerprint (MAF), were introduced to describe the selectivity of aromatic ligands to different proteins. MIF and MAF patterns are in agreement with fragment and similarity considerations. Limitations and future extension of our approach are discussed.
一般来说,计算机辅助药物设计专注于针对单一蛋白质靶点筛选配体分子。针对一种配体筛选多种蛋白质是分子对接的一种相对较新的应用。在本研究中,使用来自布鲁克海文蛋白质数据库的复合物来研究蛋白质筛选的对接方法。应用自动分子对接计算来重现该数据库中的44种蛋白质 - 芳香族配体复合物(31种不同蛋白质和39种不同配体分子)。所有配体总共进行了12090次对接运行,与所有不同的蛋白质靶点进行对接。基于广泛对接模拟的结果,引入了两种相对度量,即分子相互作用指纹(MIF)和分子亲和指纹(MAF),以描述芳香族配体对不同蛋白质的选择性。MIF和MAF模式与片段和相似性考虑因素一致。讨论了我们方法的局限性和未来扩展。