Mulliken Center for Theoretical Chemistry, Institute of Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115, Bonn, Germany.
Novartis Institutes for Biomedical Research, 4002, Basel, Switzerland.
J Comput Aided Mol Des. 2018 Oct;32(10):1139-1149. doi: 10.1007/s10822-018-0145-7. Epub 2018 Aug 23.
Recent advances in the development of low-cost quantum chemical methods have made the prediction of conformational preferences and physicochemical properties of medium-sized drug-like molecules routinely feasible, with significant potential to advance drug discovery. In the context of the SAMPL6 challenge, macroscopic pKa values were blindly predicted for a set of 24 of such molecules. In this paper we present two similar quantum chemical based approaches based on the high accuracy calculation of standard reaction free energies and the subsequent determination of those pKa values via a linear free energy relationship. Both approaches use extensive conformational sampling and apply hybrid and double-hybrid density functional theory with continuum solvation to calculate free energies. The blindly calculated macroscopic pKa values were in excellent agreement with the experiment.
近年来，低成本量子化学方法的发展取得了进展，使得预测中等大小类似药物分子的构象偏好和物理化学性质变得常规可行，这为药物发现带来了重大的潜在进展。在 SAMPL6 挑战赛的背景下，我们对一组 24 个此类分子的宏观 pk 值进行了盲目预测。在本文中，我们提出了两种类似的基于量子化学的方法，这两种方法都是基于标准反应自由能的高精度计算，并通过线性自由能关系来确定那些 pk 值。这两种方法都使用了广泛的构象采样，并应用混合和双杂交密度泛函理论与连续溶剂化来计算自由能。盲目计算出的宏观 pk 值与实验结果非常吻合。
