Departament de Química, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.
J Comput Chem. 2014 Jan 30;35(3):192-8. doi: 10.1002/jcc.23472. Epub 2013 Oct 28.
Organometallic compounds are increasingly used as molecular scaffolds in drug development projects; their structural and electronic properties offering novel opportunities in protein-ligand complementarities. Interestingly, while protein-ligand dockings have long become a spearhead in computer assisted drug design, no benchmarking nor optimization have been done for their use with organometallic compounds. Pursuing our efforts to model metal mediated recognition processes, we herein present a systematic study of the capabilities of the program GOLD to predict the interactions of protein with organometallic compounds. The study focuses on inert systems for which no alteration of the first coordination sphere of the metal occurs upon binding. Several scaffolds are used as test systems with different docking schemes and scoring functions. We conclude that ChemScore is the most robust scoring function with ASP and ChemPLP providing with good results too and GoldScore slightly underperforming. This study shows that current state-of-the-art protein-ligand docking techniques are reliable for the docking of inert organometallic compounds binding to protein.
有机金属化合物在药物开发项目中越来越多地被用作分子支架;它们的结构和电子性质为蛋白质-配体互补性提供了新的机会。有趣的是,虽然蛋白质-配体对接技术长期以来一直是计算机辅助药物设计的先锋,但对于它们与有机金属化合物的使用,还没有进行基准测试或优化。在努力对金属介导的识别过程进行建模的过程中,我们在此系统地研究了程序 GOLD 预测蛋白质与有机金属化合物相互作用的能力。该研究侧重于惰性系统,即在结合时金属的第一配体球不会发生变化。使用不同的对接方案和评分函数作为测试系统使用了几种支架。我们得出结论,ChemScore 是最稳健的评分函数,ASP 和 ChemPLP 也提供了良好的结果,而 GoldScore 的表现略逊一筹。这项研究表明,当前最先进的蛋白质-配体对接技术可可靠地对接与蛋白质结合的惰性有机金属化合物。