Augmented DMTA Engineering, R&D IT, AstraZeneca, Eastbrook House, Shaftesbury Road, Cambridge, CB2 8DU, UK.
Augmented DMTA Engineering, R&D IT, AstraZeneca, Pepparedsleden 1, 43183, Mölndal, Sweden.
Sci Rep. 2023 Mar 13;13(1):4143. doi: 10.1038/s41598-023-30089-x.
Hydrogen bonding is an interaction of great importance in drug discovery and development as it may significantly affect chemical and biological processes including the interaction of small molecules with other molecules, proteins, and membranes. In particular, hydrogen bonding can impact drug-like properties such as target affinity and oral availability which are critical to developing effective pharmaceuticals, and therefore, numerous methods for the calculation of properties such as hydrogen-bond strengths, free energy of hydration, or water solubility have been proposed over time. However, the accessibility to efficient methods for the predictions of such properties is still limited. Here, we present the development of Jazzy, an open-source tool for the prediction of hydrogen-bond strengths and free energies of hydration of small molecules. Jazzy also allows the visualisation of hydrogen-bond strengths with atomistic resolution to support the design of compounds with desired properties and the interpretation of existing data. The tool is described in its implementation, parameter fitting, and validation against two data sets of experimental hydration free energies. Jazzy is also applied against two chemical series of bioactive compounds to show that hydrogen-bond strengths can be used to understand their structure-activity relationships. Results from the validations highlight the strengths and limitations of Jazzy, and suggest its suitability for interactive design, screening, and machine-learning featurisation.
氢键在药物发现和开发中具有重要的作用，因为它可能显著影响化学和生物过程，包括小分子与其他分子、蛋白质和膜的相互作用。特别是，氢键可以影响药物样性质，如靶标亲和力和口服生物利用度，这对于开发有效的药物至关重要，因此，随着时间的推移，已经提出了许多用于计算氢键强度、水合自由能或水溶性等性质的方法。然而，对这些性质进行预测的有效方法的可及性仍然有限。在这里，我们介绍了 Jazzy 的开发，这是一种用于预测小分子氢键强度和水合自由能的开源工具。Jazzy 还允许以原子分辨率可视化氢键强度，以支持设计具有所需性质的化合物，并解释现有数据。该工具在其实现、参数拟合和针对两个实验水合自由能数据集的验证方面进行了描述。Jazzy 还应用于两个生物活性化合物的化学系列，以表明氢键强度可用于理解它们的结构-活性关系。验证结果突出了 Jazzy 的优势和局限性，并表明它适合于交互式设计、筛选和机器学习特征化。
