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SQM/COSMO Scoring Function: Reliable Quantum-Mechanical Tool for Sampling and Ranking in Structure-Based Drug Design.
ChemPlusChem ( IF 3.4 ) Pub Date : 2020-06-02 , DOI: 10.1002/cplu.202000120
Adam Pecina 1 , Saltuk M Eyrilmez 1, 2 , Cemal Köprülüoğlu 1, 2 , Vijay Madhav Miriyala 1 , Martin Lepšík 1 , Jindřich Fanfrlík 1 , Jan Řezáč 1 , Pavel Hobza 1, 2
Affiliation  

Quantum mechanical (QM) methods have been gaining importance in structure‐based drug design where a reliable description of protein‐ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM‐based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM‐based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof‐of‐concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure‐based drug design.

中文翻译:

SQM/COSMO 评分函数:基于结构的药物设计中用于采样和排序的可靠量子力学工具。

量子力学 (QM) 方法在基于结构的药物设计中越来越重要,其中对蛋白质-配体相互作用的可靠描述至关重要。但是,策略 i。e. 必须采用 QM/MM、碎片化或半经验 (SQM) 方法来克服 QM 方法的不利扩展。各种基于 SQM 的方法对先导化合物对接的准确性和改进做出了重大贡献。我们实验室中 SQM 的参数化和隐式溶剂方法有助于获得可靠的基于 SQM 的评分函数。在对与数十个蛋白质靶标结合的配体进行活性排序的应用中获得的经验导致建立了更快的 SQM/COSMO 评分方法,对于具有一万个姿势的两打蛋白质目标,其在自然姿势识别中优于标准评分方法。最近,SQM/COSMO 被有效地应用于虚拟筛选富集的概念验证研究。由于其优越的性能、可行性和化学通用性,我们提出 SQM/COSMO 方法作为基于结构的药物设计的有效工具。
更新日期:2020-06-02
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