Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA.
Department of Chemistry and Biochemistry and Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida 32306, USA.
J Chem Phys. 2020 Sep 21;153(11):114502. doi: 10.1063/5.0019056.
The General AMBER Force Field (GAFF) has been broadly used by researchers all over the world to perform in silico simulations and modelings on diverse scientific topics, especially in the field of computer-aided drug design whose primary task is to accurately predict the affinity and selectivity of receptor-ligand binding. The atomic partial charges in GAFF and the second generation of GAFF (GAFF2) were originally developed with the quantum mechanics derived restrained electrostatic potential charge, but in practice, users usually adopt an efficient charge method, Austin Model 1-bond charge corrections (AM1-BCC), based on which, without expensive ab initio calculations, the atomic charges could be efficiently and conveniently obtained with the ANTECHAMBER module implemented in the AMBER software package. In this work, we developed a new set of BCC parameters specifically for GAFF2 using 442 neutral organic solutes covering diverse functional groups in aqueous solution. Compared to the original BCC parameter set, the new parameter set significantly reduced the mean unsigned error (MUE) of hydration free energies from 1.03 kcal/mol to 0.37 kcal/mol. More excitingly, this new AM1-BCC model also showed excellent performance in the solvation free energy (SFE) calculation on diverse solutes in various organic solvents across a range of different dielectric constants. In this large-scale test with totally 895 neutral organic solvent-solute systems, the new parameter set led to accurate SFE predictions with the MUE and the root-mean-square-error of 0.51 kcal/mol and 0.65 kcal/mol, respectively. This newly developed charge model, ABCG2, paved a promising path for the next generation GAFF development.
通用 AMBER 力场（GAFF）已被全球研究人员广泛用于在不同科学领域进行计算机辅助药物设计等模拟和建模，特别是在计算机辅助药物设计领域，其主要任务是准确预测受体-配体结合的亲和力和选择性。GAFF 和第二代 GAFF（GAFF2）中的原子部分电荷最初是使用量子力学推导的静电势电荷开发的，但在实践中，用户通常采用有效的电荷方法，即基于 Austin 模型 1-键电荷校正（AM1-BCC）的方法。在此基础上，无需进行昂贵的从头计算，就可以使用 AMBER 软件包中的 ANTECHAMBER 模块高效便捷地获得原子电荷。在这项工作中，我们针对 GAFF2 开发了一套新的 BCC 参数，该参数使用了 442 种中性有机溶质，涵盖了水溶液中不同功能团。与原始 BCC 参数集相比，新参数集将水合自由能的平均未对齐误差（MUE）从 1.03 kcal/mol 显著降低到 0.37 kcal/mol。更令人兴奋的是，该新的 AM1-BCC 模型在不同介电常数下各种有机溶剂中不同溶质的溶剂化自由能（SFE）计算中也表现出了优异的性能。在总共 895 个中性有机溶剂-溶质体系的大规模测试中，新参数集导致 SFE 预测具有 0.51 kcal/mol 的 MUE 和 0.65 kcal/mol 的均方根误差。这种新开发的电荷模型 ABCG2 为下一代 GAFF 的发展铺平了道路。
