当前位置: X-MOL 学术J. Cheminfom. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Cheminformatics-based enumeration and analysis of large libraries of macrolide scaffolds.
Journal of Cheminformatics ( IF 8.6 ) Pub Date : 2018-11-12 , DOI: 10.1186/s13321-018-0307-6
Phyo Phyo Kyaw Zin 1, 2 , Gavin Williams 1, 3 , Denis Fourches 1, 2, 3
Affiliation  

We report on the development of a cheminformatics enumeration technology and the analysis of a resulting large dataset of virtual macrolide scaffolds. Although macrolides have been shown to have valuable biological properties, there is no ready-to-screen virtual library of diverse macrolides in the public domain. Conducting molecular modeling (especially virtual screening) of these complex molecules is highly relevant as the organic synthesis of these compounds, when feasible, typically requires many synthetic steps, and thus dramatically slows the discovery of new bioactive macrolides. Herein, we introduce a cheminformatics approach and associated software that allows for designing and generating libraries of virtual macrocycle/macrolide scaffolds with user-defined constitutional and structural constraints (e.g., types and numbers of structural motifs to be included in the macrocycle, ring size, maximum number of compounds generated). To study the chemical diversity of such generated molecules, we enumerated V1M (Virtual 1 million Macrolide scaffolds) library, each containing twelve common structural motifs. For each macrolide scaffold, we calculated several key properties, such as molecular weight, hydrogen bond donors/acceptors, topological polar surface area. In this study, we discuss (1) the initial concept and current features of our PKS (polyketides) Enumerator software, (2) the chemical diversity and distribution of structural motifs in V1M library, and (3) the unique opportunities for future virtual screening of such enumerated ensembles of macrolides. Importantly, V1M is provided in the Supplementary Material of this paper allowing other researchers to conduct any type of molecular modeling and virtual screening studies. Therefore, this technology for enumerating extremely large libraries of macrolide scaffolds could hold a unique potential in the field of computational chemistry and drug discovery for rational designing of new antibiotics and anti-cancer agents.

中文翻译:

基于化学信息学的大环内酯支架大型库的枚举和分析。

我们报告了化学信息学计数技术的发展以及对虚拟大环内酯支架的大型数据集的分析。尽管大环内酯类已被证明具有有价值的生物学特性,但公共领域还没有现成的各种大环内酯类虚拟库。对这些复杂分子进行分子建模(尤其是虚拟筛选)具有高度相关性,因为这些化合物的有机合成在可行时通常需要许多合成步骤,从而大大减缓了新生物活性大环内酯的发现。在此,我们介绍了一种化学信息学方法和相关软件,允许设计和生成具有用户定义的组成和结构约束的虚拟大环/大环内酯支架库(例如,大环中包含的结构基序的类型和数量、环大小、生成的化合物的最大数量)。为了研究此类生成分子的化学多样性,我们列举了 V1M(虚拟 100 万个大环内酯支架)库,每个库包含 12 个常见的结构基序。对于每个大环内酯支架,我们计算了几个关键特性,例如分子量、氢键供体/受体、拓扑极性表面积。在本研究中,我们讨论 (1) 我们的 PKS(聚酮化合物)枚举器软件的初始概念和当前功能,(2) V1M 文库中结构基序的化学多样性和分布,以及 (3) 未来虚拟筛选的独特机会此类列举的大环内酯类集合。重要的是,本文的补充材料中提供了 V1M,允许其他研究人员进行任何类型的分子建模和虚拟筛选研究。因此,这种用于枚举极大的大环内酯支架库的技术可以在计算化学和药物发现领域具有独特的潜力,以合理设计新的抗生素和抗癌药物。
更新日期:2018-11-12
down
wechat
bug