In silico construction of a focused fragment library facilitating exploration of chemical space.

IF 2.8 4区 医学 Q3 CHEMISTRY, MEDICINAL Molecular Informatics Pub Date : 2024-03-01 Epub Date: 2024-01-23 DOI:10.1002/minf.202300256
Weijie Han, Xiaohe Xu, Qing Fan, Yingchao Yan, YanMin Zhang, Yadong Chen, Haichun Liu
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Abstract

Fragment-based drug design (FBDD) has emerged as a captivating subject in the realm of computer-aided drug design, enabling the generation of novel molecules through the rearrangement of ring systems within known compounds. The construction of focused fragment library plays a pivotal role in FBDD, necessitating the compilation of all potential bioactive ring systems capable of interacting with a specific target. In our study, we propose a workflow for the development of a focused fragment library and combinatorial compound library. The fragment library comprises seed fragments and collected fragments. The extraction of seed fragments is guided by receptor information, serving as a prerequisite for establishing a focused libraries. Conversely, collected fragments are obtained using the feature graph method, which offers a simplified representation of fragments and strikes a balance between diversity and similarity when categorizing different fragments. The utilization of feature graph facilitates the rational partitioning of chemical space at fragment level, enabling the exploration of desired chemical space and enhancing the efficiency of screening compound library. Analysis demonstrates that our workflow enables the enumeration of a greater number of entirely new potential compounds, thereby aiding in the rational design of drugs.

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硅构建聚焦片段库,促进化学空间探索。
基于片段的药物设计(FBDD)已成为计算机辅助药物设计领域一个令人着迷的课题,它通过对已知化合物中的环系统进行重排,生成新的分子。集中片段库的构建在 FBDD 中起着关键作用,它要求汇集所有能与特定靶点相互作用的潜在生物活性环系统。在我们的研究中,我们提出了一个开发聚焦片段库和组合化合物库的工作流程。片段库包括种子片段和收集片段。种子片段的提取以受体信息为指导,是建立重点片段库的先决条件。相反,收集的片段是通过特征图法获得的,这种方法简化了片段的表示,并在对不同片段进行分类时兼顾了多样性和相似性。特征图的使用有助于在片段层面合理划分化学空间,从而探索所需的化学空间,提高化合物库筛选的效率。分析表明,我们的工作流程能够枚举出更多全新的潜在化合物,从而有助于药物的合理设计。
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来源期刊
Molecular Informatics
Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.30
自引率
2.80%
发文量
70
审稿时长
3 months
期刊介绍: Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.
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