Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
Molecules. 2022 Mar 18;27(6):1985. doi: 10.3390/molecules27061985.
The notion of a contribution of a specific group in an organic molecule's property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the throughput and availability of the FBDD methods by judiciously using an in silico means of assessing the contribution to ligand-receptor binding energy of fragments of a molecule under question using a previously developed in silico Reverse Fragment Based Drug Discovery (R-FBDD) approach. It has been shown that the proposed structure-based drug discovery (SBDD) type of approach fills in the vacant niche among the existing in silico approaches, which mainly stem from the ligand-based drug discovery (LBDD) counterparts. In order to illustrate the applicability of the approach, our work retrospectively repeats the findings of the use case of an FBDD hit-to-lead project devoted to the experimentally based determination of additive group efficiency (GE)-an analog of ligand efficiency (LE) for a group in the molecule-using the Free-Wilson (FW) decomposition. It is shown that in using our in silico approach to evaluate fragment contributions of a ligand and to estimate GE one can arrive at similar decisions as those made using the experimentally determined activity-based FW decomposition. It is also shown that the approach is rather robust to the choice of the scoring function, provided the latter demonstrates a decent scoring power. We argue that the proposed approach of in silico assessment of GE has a wider applicability domain and expect that it will be widely applicable to enhance the net throughput of drug discovery based on the FBDD paradigm.
特定基团对有机分子性质和/或活性的贡献这一概念在我们的思维中既常见又不严格正确，这是由于自由能对于构成分子的分子片段不具有加和性。基于片段的药物发现（FBDD）方法已被证明在解决上述概念方面是富有成效的。然而，FBDD 的主要困难在于它依赖于确定片段大小分子结合的低通量和昂贵的实验手段。在本文中，我们提出了一种通过明智地使用计算手段来增强 FBDD 方法的通量和可用性的方法，即使用先前开发的计算反向基于片段的药物发现（R-FBDD）方法来评估问题分子片段对配体-受体结合能的贡献。已经表明，所提出的基于结构的药物发现（SBDD）类型的方法填补了现有计算方法中的空缺，这些方法主要源自配体基于药物发现（LBDD）的对应方法。为了说明该方法的适用性，我们的工作回顾性地重复了使用基于实验的基于片段的药物发现（FBDD）方法的案例研究结果，该案例研究用于确定加和基团效率（GE）-分子中基团的配体效率（LE）的类似物-使用自由威尔逊（FW）分解。结果表明，使用我们的计算方法来评估配体的片段贡献并估计 GE，可以得出与使用实验确定的基于活性的 FW 分解得出的相似决策。还表明，该方法对评分函数的选择相当稳健，只要后者具有良好的评分能力。我们认为，所提出的计算评估 GE 的方法具有更广泛的适用性域，并期望它将广泛适用于增强基于 FBDD 范式的药物发现的净通量。
