Engelhardt Marc U, Zimmermann Markus O, Mier Finn, Boeckler Frank M
Laboratory for Molecular Design & Pharmaceutical Biophysics, Institute of Pharmaceutical Sciences, Department of Pharmacy and Biochemistry, Eberhard Karls Universität Tübingen, 72076 Tübingen, Germany.
Interfaculty Institute for Biomedical Informatics (IBMI), Eberhard Karls Universität Tübingen, 72076 Tübingen, Germany.
J Chem Theory Comput. 2025 Jun 24;21(12):6174-6183. doi: 10.1021/acs.jctc.5c00456. Epub 2025 Jun 9.
Halogen-π interactions play a pivotal role in molecular recognition processes, drug design, and therapeutic strategies, providing unique opportunities for enhancing and fine-tuning the binding affinity and specificity of pharmaceutical agents. The present study systematically benchmarks various combinations of quantum mechanical (QM) methods and basis sets to characterize halogen-π interactions in model systems. We evaluate both density functional theory (DFT) methods and wave function-based post-HF methods in terms of accuracy to reference calculations at the CCSD(T)/CBS level of theory and runtime efficiency. By balancing these crucial aspects, we aim to identify an optimal configuration suitable for high-throughput applications. Our results indicate that MP2 using the reasonably large TZVPP basis set is in excellent agreement with reference calculations, striking a balance between accuracy and computational efficiency. This allows us to generate large, reliable data sets, which will serve as a basis to develop and train machine-learning models capable of accurately capturing the strength of halogen-π interactions, thereby providing a robust data-driven foundation for medicinal chemistry analysis.
卤代-π相互作用在分子识别过程、药物设计和治疗策略中起着关键作用，为增强和微调药物制剂的结合亲和力及特异性提供了独特机遇。本研究系统地对量子力学（QM）方法和基组的各种组合进行基准测试，以表征模型系统中的卤代-π相互作用。我们从理论精度到CCSD(T)/CBS水平的参考计算以及运行时效率方面，评估了密度泛函理论（DFT）方法和基于波函数的后HF方法。通过平衡这些关键因素，我们旨在确定适合高通量应用的最佳配置。我们的结果表明，使用相当大的TZVPP基组的MP2与参考计算结果高度吻合，在准确性和计算效率之间取得了平衡。这使我们能够生成大量可靠的数据集，作为开发和训练能够准确捕捉卤代-π相互作用强度的机器学习模型的基础，从而为药物化学分析提供强大的数据驱动基础。
