Pan Xiaolin, Zhao Fanyu, Zhang Yueqing, Wang Xingyu, Xiao Xudong, Zhang John Z H, Ji Changge
Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.
NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.
J Chem Inf Model. 2023 Apr 10;63(7):1833-1840. doi: 10.1021/acs.jcim.2c01393. Epub 2023 Mar 20.
Fast and proper treatment of the tautomeric states for drug-like molecules is critical in computer-aided drug discovery since the major tautomer of a molecule determines its pharmacophore features and physical properties. We present MolTaut, a tool for the rapid generation of favorable states of drug-like molecules in water. MolTaut works by enumerating possible tautomeric states with tautomeric transformation rules, ranking tautomers with their relative internal energies and solvation energies calculated by AI-based models, and generating preferred ionization states according to predicted microscopic p. Our test shows that the ranking ability of the AI-based tautomer scoring approach is comparable to the DFT method (wB97X/6-31G*//M062X/6-31G*/SMD) from which the AI models try to learn. We find that the substitution effect on tautomeric equilibrium is well predicted by MolTaut, which is helpful in computer-aided ligand design. The source code of MolTaut is freely available to researchers and can be accessed at https://github.com/xundrug/moltaut. To facilitate the usage of MolTaut by medicinal chemists, we made a free web server, which is available at http://moltaut.xundrug.cn. MolTaut is a handy tool for investigating the tautomerization issue in drug discovery.
在计算机辅助药物发现中，快速且恰当地处理类药物分子的互变异构状态至关重要，因为分子的主要互变异构体决定了其药效团特征和物理性质。我们展示了MolTaut，这是一种用于在水中快速生成类药物分子有利状态的工具。MolTaut通过用互变异构转换规则枚举可能的互变异构状态、用基于人工智能的模型计算的相对内能和溶剂化能对互变异构体进行排序，以及根据预测的微观p生成优选的电离状态来工作。我们的测试表明，基于人工智能的互变异构体评分方法的排序能力与人工智能模型试图从中学习的DFT方法（wB97X/6 - 31G*//M062X/6 - 31G*/SMD）相当。我们发现MolTaut能很好地预测取代基对互变异构平衡的影响，这有助于计算机辅助配体设计。MolTaut的源代码可供研究人员免费获取，可在https://github.com/xundrug/moltaut上访问。为便于药物化学家使用MolTaut，我们创建了一个免费的网络服务器，可在http://moltaut.xundrug.cn上使用。MolTaut是研究药物发现中互变异构问题的便捷工具。
