Ekins Sean, Litterman Nadia K, Lipinski Christopher A, Bunin Barry A
Collaborative Drug Discovery, Inc., 1633 Bayshore Highway Suite 342, Burlingame, California, 94010, USA.
Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay Varina, North Carolina, 27526, USA.
Pharm Res. 2016 Jan;33(1):194-205. doi: 10.1007/s11095-015-1779-y. Epub 2015 Aug 27.
We propose a framework with simple proxies to dissect the relative energy contributions responsible for standard drug discovery binding activity.
We explore a rule of thumb using hydrogen-bond donors, hydrogen-bond acceptors and rotatable bonds as relative proxies for the thermodynamic terms. We apply this methodology to several datasets (e.g., multiple small molecules profiled against kinases, Mycobacterium tuberculosis (Mtb) high throughput screening (HTS) and structure based drug design (SBDD) derived compounds, and FDA approved drugs).
We found that Mtb active compounds developed through SBDD methods had statistically significantly larger PEnthalpy values than HTS derived compounds, suggesting these compounds had relatively more hydrogen bond donor and hydrogen bond acceptors compared to rotatable bonds. In recent FDA approved medicines we found that compounds identified via target-based approaches had a more balanced enthalpic relationship between these descriptors compared to compounds identified via phenotypic screens
As it is common to experimentally optimize directly for total binding energy, these computational methods provide alternative calculations and approaches useful for compound optimization alongside other common metrics in available software and databases.
我们提出了一个带有简单代理变量的框架，以剖析对标准药物发现结合活性起作用的相对能量贡献。
我们探索了一种经验法则，使用氢键供体、氢键受体和可旋转键作为热力学项的相对代理变量。我们将此方法应用于多个数据集（例如，针对激酶进行分析的多个小分子、结核分枝杆菌（Mtb）高通量筛选（HTS）和基于结构的药物设计（SBDD）衍生的化合物，以及美国食品药品监督管理局（FDA）批准的药物）。
我们发现，通过SBDD方法开发的Mtb活性化合物的PEnthalpy值在统计学上显著高于HTS衍生的化合物，这表明与可旋转键相比，这些化合物具有相对更多的氢键供体和氢键受体。在最近FDA批准的药物中，我们发现与通过表型筛选鉴定的化合物相比，通过基于靶点的方法鉴定的化合物在这些描述符之间具有更平衡的焓关系。
由于直接针对总结合能进行实验优化很常见，这些计算方法提供了替代计算和方法，可与现有软件和数据库中的其他常见指标一起用于化合物优化。
