Fatmawati Fenti, Sakti Aditya Wibawa, Hildayani Suci Zulaikha, Warganegara Fida Madayanti, Martoprawiro Muhamad Abdulkadir
Doctoral Program of Chemistry, Faculty of Mathematics and Natural Science, Institut Teknologi Bandung, Bandung, Indonesia.
Faculty of Pharmacy, Bhakti Kencana University, Bandung, Indonesia.
J Mol Model. 2025 Jul 12;31(8):206. doi: 10.1007/s00894-025-06408-6.
Nearly 90% of drugs on the market are racemates. A racemate is a mixture of two enantiomers or substances in equal amounts that have an asymmetric molecular structure that is a mirror image of each other. Despite having the same chemical structure, chiral drug isomers can exhibit very different biological behaviors in terms of pharmacology, toxicity, pharmacokinetics, metabolism, etc. Since racemic drugs have only one bioactive enantiomer while its counterpart enantiomers impart undesirable pharmacological properties, it is necessary to separate these racemic compounds to obtain the desired active enantiomer. Chromatography is one of the approaches for the separation of enantiomers. In this study, we observed the chromatographic profile of racemic mandelic acid compound passed through a chiral HPLC column. The chromatogram profile was then observed computationally to study the separation mechanism. The experimental results are in line with the computational analysis that the S chromatogram eluted first compared to the R-enantiomer. It can be predicted that the binding energy of the R-enantiomer (-108.92 kJ/mol) is stronger than the S-enantiomer (- 67 kJ/mol).
The chromatogram profile of mandelic acid racemate was observed experimentally using a chiral OD column, and the prediction of column-ligand binding energy was based on computational studies using the conformer-rotamer ensemble sampling tool (CREST). The chromatogram profile was identified using a 0.46 cm × 25 cm chiral OD column HPLC instrument (Daicel Chemical). The samples used were racemic compounds of mandelic acid and standard (S)-mandelic acid. Computational calculations of column capacity factors and binding energies of each enantiomer were performed with a Windows 11 Pro 64-bit operating system, × 64-based processor, equipped with the MGL-Tools program consisting of the ADT (Autodock Tools) application, Avogadro, AutoDock 4.2, Discovery Studio 2020 Client®, and CREST installed as a driver program for the XTB semiempirical quantum chemistry package. For geometry optimization and sampling of DMPC-ligand complexes, we used CREST at https://github.com/grimme-lab/crest .
市场上近90%的药物是外消旋体。外消旋体是两种对映体或物质的等量混合物,它们具有不对称的分子结构,且互为镜像。尽管手性药物异构体具有相同的化学结构,但在药理学、毒性、药代动力学、代谢等方面可能表现出非常不同的生物学行为。由于外消旋药物只有一种生物活性对映体,而其对应的对映体具有不良的药理性质,因此有必要分离这些外消旋化合物以获得所需的活性对映体。色谱法是分离对映体的方法之一。在本研究中,我们观察了外消旋扁桃酸化合物通过手性高效液相色谱柱后的色谱图。然后通过计算观察色谱图以研究分离机制。实验结果与计算分析一致,即S色谱图比R-对映体先洗脱。可以预测,R-对映体的结合能(-108.92 kJ/mol)比S-对映体(-67 kJ/mol)更强。
使用手性OD柱通过实验观察扁桃酸外消旋体的色谱图,柱-配体结合能的预测基于使用构象异构体-旋转异构体集合采样工具(CREST)的计算研究。使用0.46 cm×25 cm手性OD柱高效液相色谱仪(大赛璐化学公司)鉴定色谱图。所用样品为扁桃酸外消旋化合物和标准(S)-扁桃酸。使用Windows 11 Pro 64位操作系统、基于×64的处理器进行各对映体的柱容量因子和结合能的计算,该处理器配备了由ADT(自动对接工具)应用程序、Avogadro、AutoDock 4.2、Discovery Studio 2020 Client®和作为XTB半经验量子化学软件包驱动程序安装的CREST组成的MGL-Tools程序。为了进行DMPC-配体复合物的几何优化和采样,我们在https://github.com/grimme-lab/crest上使用了CREST。