Journal of Computer-Aided Molecular Design ( IF 3.0 ) Pub Date : 2020-08-17 , DOI: 10.1007/s10822-020-00337-7 Anikó Udvarhelyi 1 , Stephane Rodde 2 , Rainer Wilcken 2
|
Abstract
Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known. We further show that including ReSCoSS conformers significantly improves COSMO-RS based predictions of physicochemical properties over single-conformation approaches. ReSCoSS has found broad adoption in the in-house drug discovery and development work streams and has contributed to establishing quantum-chemistry methods as a strategic pillar in ligand discovery.
Graphic abstract
中文翻译：
ReSCoSS：一种灵活的量子化学工作流程，可识别类药物分子的相关溶液构象异构体。
摘要
构象平衡是药物设计的核心，但它们的能量描述往往受到低成本方法准确性不足的阻碍。在这里，我们提出了一种基于量子化学 ReSCoSS 的灵活半自动工作流程，旨在识别相关构象异构体并预测它们在真实溶剂类导体筛选模型 (COSMO-RS) 框架中不同溶剂环境中的平衡。我们通过对已知相关构象的文献中的几种药物样分子的构象案例研究，证明了工作流程的实用性和准确性。我们进一步表明，与单一构象方法相比，包括 ReSCoSS 构象异构体显着改善了基于 COSMO-RS 的理化性质预测。
京公网安备 11010802027423号