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药物发现中的计算策略:利用减法基因组分析进行靶点识别。

Computational Strategies in Drug Discovery: Leveraging Subtractive Genomic Analysis for Target Identification.

作者信息

Patil Vivek, Desai Sharav, Patel Vipul, Somase Vrushali

机构信息

Department of Pharmaceutics, Sanjivani College of Pharmaceutical Education and Research, Savitribai Phule Pune University, At-Sahajanandnagar, Post- Shinganapur, Tal.-Kopargaon, Ahmednagar, Maharashtra, 423603, India.

出版信息

Curr Pharm Biotechnol. 2025;26(9):1271-1286. doi: 10.2174/0113892010295441240515074348.


DOI:10.2174/0113892010295441240515074348
PMID:38808712
Abstract

The utilization of subtractive genomic analysis has emerged as an important and essential method in modern drug discovery and development since it significantly improves the process of identifying and validating potential targets for discovering novel therapeutic compounds to treat severe infections caused by Antimicrobial-resistant (AMR) - pathogenic species. This review provides a complete overview of the methodology, advantages, disadvantages, and prospects, associated with subtractive genomic research in the context of drug discovery and development. The initial phase of analysis encompasses the retrieval of data, which serves as a foundation for the subsequent data mining process in Phase 1. After data mining, Phase 2 utilizes subtractive channels for the target's non-homology and essentiality analysis. Phase 3 of the study aims to provide a comprehensive understanding of prospective targets by their qualitative characterization. Further, Phase 4 of the study emphasizes on conducting structure-based analyses, which involves the determination, refinement, evaluation, and validation of three-dimensional structures of the target proteins, along with their active site prediction and selection of the novel therapeutic compounds against that active site on the obtained targets through virtual screening and docking studies by utilizing various databases and servers. The therapeutic compounds obtained can be then validated by and testing, thereby establishing a connection between the computational predictions and real applications.

摘要

消减基因组分析的应用已成为现代药物发现与开发中一种重要且必不可少的方法,因为它显著改善了识别和验证潜在靶点的过程,这些靶点用于发现新型治疗化合物,以治疗由耐药性(AMR)致病物种引起的严重感染。本综述全面概述了与药物发现和开发背景下的消减基因组研究相关的方法、优点、缺点和前景。分析的初始阶段包括数据检索,这为第1阶段后续的数据挖掘过程奠定了基础。数据挖掘后,第2阶段利用消减通道进行靶点的非同源性和必要性分析。该研究的第3阶段旨在通过对潜在靶点的定性表征来全面了解它们。此外,该研究的第4阶段强调进行基于结构的分析,这涉及确定、优化、评估和验证目标蛋白的三维结构,以及预测其活性位点,并通过利用各种数据库和服务器进行虚拟筛选和对接研究,针对所得靶点上的该活性位点选择新型治疗化合物。然后可以通过 和 测试对获得的治疗化合物进行验证,从而在计算预测和实际应用之间建立联系。

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本文引用的文献

[1]
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Nucleic Acids Res. 2024-1-5

[2]
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[3]
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[4]
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BMC Microbiol. 2023-1-21

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[9]
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Bioengineering (Basel). 2022-9-7

[10]
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PLoS One. 2022

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