Correlation of protein binding pocket properties with hits’ chemistries used in generation of ultra-large virtual libraries

IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Robert X. Song, Marc C. Nicklaus, Nadya I. Tarasova
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Abstract

Although the size of virtual libraries of synthesizable compounds is growing rapidly, we are still enumerating only tiny fractions of the drug-like chemical universe. Our capability to mine these newly generated libraries also lags their growth. That is why fragment-based approaches that utilize on-demand virtual combinatorial libraries are gaining popularity in drug discovery. These à la carte libraries utilize synthetic blocks found to be effective binders in parts of target protein pockets and a variety of reliable chemistries to connect them. There is, however, no data on the potential impact of the chemistries used for making on-demand libraries on the hit rates during virtual screening. There are also no rules to guide in the selection of these synthetic methods for production of custom libraries. We have used the SAVI (Synthetically Accessible Virtual Inventory) library, constructed using 53 reliable reaction types (transforms), to evaluate the impact of these chemistries on docking hit rates for 40 well-characterized protein pockets. The data shows that the virtual hit rates differ significantly for different chemistries with cross coupling reactions such as Sonogashira, Suzuki–Miyaura, Hiyama and Liebeskind–Srogl coupling producing the highest hit rates. Virtual hit rates appear to depend not only on the property of the formed chemical bond but also on the diversity of available building blocks and the scope of the reaction. The data identifies reactions that deserve wider use through increasing the number of corresponding building blocks and suggests the reactions that are more effective for pockets with certain physical and hydrogen bond-forming properties.

Abstract Image

用于生成超大型虚拟库的蛋白质结合袋特性与命中化学成分的相关性。
尽管可合成化合物虚拟库的规模正在迅速增长,但我们仍然只列举了类药物化学宇宙中的极小部分。我们挖掘这些新生成化合物库的能力也落后于它们的增长。这就是为什么利用按需虚拟组合库的基于片段的方法在药物发现领域越来越受欢迎的原因。这些 "点菜式 "文库利用在目标蛋白质口袋部分有效结合的合成块,并利用各种可靠的化学方法将它们连接起来。然而,目前还没有数据表明,用于制作按需文库的化学物质对虚拟筛选过程中的命中率有潜在影响。在选择这些合成方法来生产定制文库时,也没有任何指导规则。我们使用 53 种可靠的反应类型(转换)构建的 SAVI(可合成虚拟库存)库,评估了这些化学方法对 40 个特征明确的蛋白质口袋的对接命中率的影响。数据显示,不同化学反应的虚拟命中率差别很大,交叉偶联反应(如 Sonogashira、Suzuki-Miyaura、Hiyama 和 Liebeskind-Srogl 偶联)的命中率最高。虚拟命中率似乎不仅取决于所形成化学键的性质,还取决于可用构件的多样性和反应的范围。这些数据确定了值得通过增加相应构筑模块的数量来更广泛使用的反应,并提出了对具有某些物理和氢键形成特性的口袋更有效的反应。
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来源期刊
Journal of Computer-Aided Molecular Design
Journal of Computer-Aided Molecular Design 生物-计算机:跨学科应用
CiteScore
8.00
自引率
8.60%
发文量
56
审稿时长
3 months
期刊介绍: The Journal of Computer-Aided Molecular Design provides a form for disseminating information on both the theory and the application of computer-based methods in the analysis and design of molecules. The scope of the journal encompasses papers which report new and original research and applications in the following areas: - theoretical chemistry; - computational chemistry; - computer and molecular graphics; - molecular modeling; - protein engineering; - drug design; - expert systems; - general structure-property relationships; - molecular dynamics; - chemical database development and usage.
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