SLC-转运体的大环抑制剂格局。

IF 2.8 4区 医学 Q3 CHEMISTRY, MEDICINAL
Molecular Informatics Pub Date : 2024-05-01 Epub Date: 2024-03-05 DOI:10.1002/minf.202300287
Nejra Granulo, Sergey Sosnin, Daniela Digles, Gerhard F Ecker
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引用次数: 0

摘要

在过去几年里,由于溶质载体转运体(SLC)具有作为药物靶点的潜力,人们对它们的兴趣与日俱增。与此同时,大环作为治疗剂也表现出了良好的活性。然而,大环化合物/溶质载体转运体之间的整体相互作用尚未完全揭示。在本研究中,我们对具有针对 SLC 转运体活性的大环化合物进行了统计分析。利用基于 KNIME 的数据挖掘管道,共检索到 825 个与 SLC 转运体相互作用的大环化合物的生物活性数据点。为了进一步分析 SLC 抑制剂概况,我们开发了一个交互式 KNIME 工作流程,并利用参数 t-SNE 模型绘制了化学空间覆盖交互式地图。参数 t-SNE 模型在几个相应的 SLC 亚家族靶标之间提供了良好的区分能力。KNIME 工作流、数据集和可视化工具可免费向社区提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The macrocycle inhibitor landscape of SLC-transporter.

In the past years the interest in Solute Carrier Transporters (SLC) has increased due to their potential as drug targets. At the same time, macrocycles demonstrated promising activities as therapeutic agents. However, the overall macrocycle/SLC-transporter interaction landscape has not been fully revealed yet. In this study, we present a statistical analysis of macrocycles with measured activity against SLC-transporter. Using a data mining pipeline based on KNIME retrieved in total 825 bioactivity data points of macrocycles interacting with SLC-transporter. For further analysis of the SLC inhibitor profiles we developed an interactive KNIME workflow as well as an interactive map of the chemical space coverage utilizing parametric t-SNE models. The parametric t-SNE models provide a good discrimination ability among several corresponding SLC subfamilies' targets. The KNIME workflow, the dataset, and the visualization tool are freely available to the community.

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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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