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用于多药理学预测的基于网络的工具。

Web-Based Tools for Polypharmacology Prediction.

作者信息

Awale Mahendra, Reymond Jean-Louis

机构信息

Department of Chemistry and Biochemistry, National Center of Competence in Research NCCR TransCure, University of Berne, Berne, Switzerland.

出版信息

Methods Mol Biol. 2019;1888:255-272. doi: 10.1007/978-1-4939-8891-4_15.

DOI:10.1007/978-1-4939-8891-4_15
PMID:30519952
Abstract

Drug promiscuity or polypharmacology is the ability of small molecules to interact with multiple protein targets simultaneously. In drug discovery, understanding the polypharmacology of potential drug molecules is crucial to improve their efficacy and safety, and to discover the new therapeutic potentials of existing drugs. Over the past decade, several computational methods have been developed to study the polypharmacology of small molecules, many of which are available as Web services. In this chapter, we review some of these Web tools focusing on ligand based approaches. We highlight in particular our recently developed polypharmacology browser (PPB) and its application for finding the side targets of a new inhibitor of the TRPV6 calcium channel.

摘要

药物混杂性或多药理学是指小分子同时与多个蛋白质靶点相互作用的能力。在药物研发中,了解潜在药物分子的多药理学对于提高其疗效和安全性以及发现现有药物的新治疗潜力至关重要。在过去十年中,已经开发了几种计算方法来研究小分子的多药理学,其中许多方法可作为网络服务使用。在本章中,我们将回顾一些基于配体方法的网络工具。我们特别强调我们最近开发的多药理学浏览器(PPB)及其在寻找TRPV6钙通道新抑制剂的次要靶点方面的应用。

相似文献

1
Web-Based Tools for Polypharmacology Prediction.用于多药理学预测的基于网络的工具。
Methods Mol Biol. 2019;1888:255-272. doi: 10.1007/978-1-4939-8891-4_15.
2
In Silico Target Prediction for Small Molecules.小分子的计算机辅助靶点预测
Methods Mol Biol. 2019;1888:273-309. doi: 10.1007/978-1-4939-8891-4_16.
3
Polypharmacology Browser PPB2: Target Prediction Combining Nearest Neighbors with Machine Learning.多药理学浏览器 PPB2:基于近邻与机器学习的靶标预测。
J Chem Inf Model. 2019 Jan 28;59(1):10-17. doi: 10.1021/acs.jcim.8b00524. Epub 2018 Dec 31.
4
The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data.多药理学浏览器:一种使用ChEMBL生物活性数据的基于网络的多指纹靶点预测工具。
J Cheminform. 2017 Feb 21;9:11. doi: 10.1186/s13321-017-0199-x. eCollection 2017.
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Advances and Challenges in Computational Target Prediction.计算靶点预测的进展与挑战。
J Chem Inf Model. 2019 May 28;59(5):1728-1742. doi: 10.1021/acs.jcim.8b00832. Epub 2019 Feb 28.
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Predicting targeted polypharmacology for drug repositioning and multi- target drug discovery.预测药物重定位和多靶标药物发现的靶向多药理学。
Curr Med Chem. 2013;20(13):1646-61. doi: 10.2174/0929867311320130005.
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Computational polypharmacology: a new paradigm for drug discovery.计算多药理学:药物发现的新范式。
Expert Opin Drug Discov. 2017 Mar;12(3):279-291. doi: 10.1080/17460441.2017.1280024. Epub 2017 Jan 23.
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Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery.提高多靶点药物发现中多药联用的疗效-安全性平衡。
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Comparison of ultra-fast 2D and 3D ligand and target descriptors for side effect prediction and network analysis in polypharmacology.用于多药理学中副作用预测和网络分析的超快速二维和三维配体及靶点描述符的比较
Br J Pharmacol. 2013 Oct;170(3):557-67. doi: 10.1111/bph.12294.
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Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery.多药理学预测:全面预测小分子选择性以降低药物发现风险的漫漫征途。
Expert Opin Drug Discov. 2024 Sep;19(9):1043-1069. doi: 10.1080/17460441.2024.2376643. Epub 2024 Jul 14.

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