Sinko William, Mertz Blake, Shimizu Takafumi, Takahashi Taisuke, Terada Yoh, Kimura S Roy
Alivexis Inc., 1 Broadway, 14th Floor, Cambridge, Massachusetts 02142, United States.
Alivexis Inc., Daiichi Hibiya Building 7F, Shimbashi 1-18-21, Minato-ku, Tokyo 105-0004, Japan.
J Chem Inf Model. 2025 Jan 13;65(1):265-274. doi: 10.1021/acs.jcim.4c01805. Epub 2024 Dec 16.
In rational drug discovery, both free energy of binding and the binding half-life () are important factors in determining the efficacy of drugs. Numerous computational methods have been developed to predict these important properties, many of which rely on molecular dynamics (MD) simulations. While binding free-energy methods (thermodynamic equilibrium predictions) have been well validated and have demonstrated the ability to drive daily synthesis decisions in a commercial drug discovery setting, the prediction of (kinetics predictions) has had limited validation, and predictive methods have largely not been deployed in drug discovery settings. We developed ModBind, a novel method for MD simulation-based predictions. ModBind demonstrated similar accuracy to current state-of-the-art free-energy prediction methods. Additionally, ModBind performs ∼100 times faster than most available MD simulation-based free-energy or methods, allowing for widespread use by the molecular modeling community. While most free-energy methods rely on relative free-energy changes and are primarily useful for optimization of a congeneric series, our method requires no structural similarity between ligands, making ModBind an absolute predictor of . ModBind is thus a tool that can be used in virtual screening of diverse ligands, making it distinct from relative free-energy methods. We also discuss conditions that enable approximate prediction of ligand efficacy using ModBind and the limitations of this approach.
在合理的药物研发中,结合自由能和结合半衰期()都是决定药物疗效的重要因素。人们已经开发了许多计算方法来预测这些重要性质,其中许多方法依赖于分子动力学(MD)模拟。虽然结合自由能方法(热力学平衡预测)已经得到了充分验证,并已证明有能力在商业药物研发环境中推动日常合成决策,但对(动力学预测)的预测验证有限,且预测方法在很大程度上尚未应用于药物研发环境。我们开发了ModBind,一种基于MD模拟进行预测的新方法。ModBind表现出与当前最先进的自由能预测方法相似的准确性。此外,ModBind的运行速度比大多数基于MD模拟的自由能或方法快约100倍,使得分子建模社区能够广泛使用。虽然大多数自由能方法依赖于相对自由能变化,主要用于同类系列的优化,但我们的方法不需要配体之间的结构相似性,这使得ModBind成为的绝对预测器。因此,ModBind是一种可用于虚拟筛选各种配体的工具,这使其有别于相对自由能方法。我们还讨论了使用ModBind进行配体疗效近似预测的条件以及这种方法的局限性。