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首页> 外文期刊>ACS Omega >Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein–Ligand Complexes in Cognate Docking
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Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein–Ligand Complexes in Cognate Docking

机译:SQM / COSMO评分功能在同源对接中不同蛋白质-配体复合物的自然姿势识别中的出色表现

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General and reliable description of structures and energetics in protein–ligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quantum mechanical (SQM) methods, which correctly describe all types of noncovalent interactions and are fast enough to treat systems of thousands of atoms. Two most accurate SQM methods, PM6-D3H4X and SCC-DFTB3-D3H4X, are coupled with the conductor-like screening model (COSMO) implicit solvation model in so-called “SQM/COSMO” SFs and have shown unique recognition of native ligand poses in cognate docking in four challenging PL systems, including metalloprotein. Here, we apply the two SQM/COSMO SFs to 17 diverse PL complexes and compare their performance with four widely used classical SFs (Glide XP, AutoDock4, AutoDock Vina, and UCSF Dock). We observe superior performance of the SQM/COSMO SFs and identify challenging systems. This method, due to its generality, comparability across the chemical space, and lack of need for any system-specific parameters, gives promise of becoming, after comprehensive large-scale testing in the near future, a useful computational tool in structure-based drug design and serving as a reference method for the development of other SFs.
机译:迄今为止,使用对接/评分方法对蛋白质-配体(PL)结合中的结构和能量学进行了一般性和可靠的描述。我们通过校正半经验量子力学(SQM)方法的系统开发来解决评分功能(SFs)的这一紧迫缺陷,该方法可以正确描述所有类型的非共价相互作用,并且足够快地处理成千上万个原子的系统。两种最准确的SQM方法PM6-D3H4X和SCC-DFTB3-D3H4X,与所谓的“ SQM / COSMO” SF中的类似导体的筛选模型(COSMO)隐含溶剂化模型相结合,并显示出对天然配体姿势的独特识别在包括金属蛋白在内的四个具有挑战性的PL系统中进行同源对接。在这里,我们将两种SQM / COSMO SF应用于17种不同的PL复合物,并将它们与四种广泛使用的经典SF(Glide XP,AutoDock4,AutoDock Vina和UCSF Dock)进行比较。我们观察到SQM / COSMO SF的出色性能,并确定具有挑战性的系统。由于该方法的通用性,整个化学领域的可比性以及无需任何特定于系统的参数,该方法有望在不久的将来经过全面的大规模测试后成为基于结构的药物的有用计算工具设计并作为其他SF开发的参考方法。

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