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
{"title":"SLC-转运体的大环抑制剂格局。","authors":"Nejra Granulo, Sergey Sosnin, Daniela Digles, Gerhard F Ecker","doi":"10.1002/minf.202300287","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The macrocycle inhibitor landscape of SLC-transporter.\",\"authors\":\"Nejra Granulo, Sergey Sosnin, Daniela Digles, Gerhard F Ecker\",\"doi\":\"10.1002/minf.202300287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":18853,\"journal\":{\"name\":\"Molecular Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Informatics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/minf.202300287\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Informatics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/minf.202300287","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/5 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
期刊最新文献
Cover Picture: (Mol. Inf. 9/2024) The freedom space - a new set of commercially available molecules for hit discovery. Cover Picture: (Mol. Inf. 8/2024) Chemography-guided analysis of a reaction path network for ethylene hydrogenation with a model Wilkinson's catalyst. Sulfotransferase-mediated phase II drug metabolism prediction of substrates and sites using accessibility and reactivity-based algorithms.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1