Technical Research and Development, Novartis Pharma AG, 4002, Basel, Switzerland.
Global Discovery Chemistry, Novartis Institutes for BioMedical Research, 4002, Basel, Switzerland.
J Comput Aided Mol Des. 2021 Apr;35(4):399-415. doi: 10.1007/s10822-020-00337-7. Epub 2020 Aug 17.
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.
构象平衡是药物设计的核心，但由于低成本方法的准确性不足，其能量描述常常受到阻碍。在这里，我们提出了一种基于量子化学的灵活半自动工作流程 ReSCoSS，旨在识别相关构象，并在用于实际溶剂的导体屏蔽模型（COSMO-RS）框架中预测它们在不同溶剂环境中的平衡。我们通过对文献中几种药物样分子的构象案例研究，展示了该工作流程的实用性和准确性，其中已知相关构象。我们还表明，与单构象方法相比，包含 ReSCoSS 构象可显著提高基于 COSMO-RS 的物理化学性质预测的准确性。ReSCoSS 在内部药物发现和开发工作流程中得到了广泛采用，并有助于将量子化学方法确立为配体发现的战略支柱。
