Suppr超能文献

基于植物化学物质的定量构效关系研究及其在更好药物设计中的应用。

QSAR of phytochemicals for the design of better drugs.

机构信息

Jadavpur University, Department of Pharmaceutical Technology, Drug Theoretics and Cheminformatics Laboratory, Kolkata, India.

出版信息

Expert Opin Drug Discov. 2012 Oct;7(10):877-902. doi: 10.1517/17460441.2012.716420. Epub 2012 Aug 16.

Abstract

INTRODUCTION

Phytochemicals have been the single most prolific source of leads for the development of new drug entities from the dawn of the drug discovery. They cover a wide range of therapeutic indications with a great diversity of chemical structures. The research fraternity still believes in exploring the phytochemicals for new drug discovery. Application of molecular biological techniques has increased the availability of novel compounds that can be conveniently isolated from natural sources. Combinatorial chemistry approaches are being applied based on phytochemical scaffolds to create screening libraries that closely resemble drug-like compounds. In silico techniques like quantitative structure-activity relationships (QSAR), pharmacophore and virtual screening are playing crucial and rate accelerating steps for the better drug design in modern era.

AREAS COVERED

QSAR models of different classes of phytochemicals covering different therapeutic areas are thoroughly discussed in the review. Further, the authors have enlisted all the available phytochemical databases for the convenience of researchers working in the area.

EXPERT OPINION

This review justifies the need to develop more QSAR models for the design of better drugs from phytochemicals. Technical drawbacks associated with phytochemical research have been lessened, and there are better opportunities to explore the biological activity of previously inaccessible sources of phytochemicals although there is still the need to reduce the time and cost involvement in such exercise. The future possibilities for the integration of ethnopharmacology with QSAR, place us at an exciting stage that will allow us to explore plant sources worldwide and design better drugs.

摘要

简介

自药物发现时代伊始,植物化学物质一直是开发新药的主要来源,具有广泛的治疗适应症和多样化的化学结构。研究界仍然相信可以从植物化学物质中探索新的药物发现。分子生物学技术的应用增加了新型化合物的可用性,这些化合物可以方便地从天然来源中分离出来。基于植物化学物质支架的组合化学方法正在被应用于创建筛选库,这些筛选库与类似药物的化合物非常相似。在现代,定量构效关系(QSAR)、药效团和虚拟筛选等计算技术在更好的药物设计中起着至关重要和加速的作用。

涵盖领域

该综述深入讨论了不同治疗领域的不同类别的植物化学物质的 QSAR 模型。此外,作者还列出了所有可用的植物化学物质数据库,以便研究人员使用。

专家意见

本综述证明了需要为植物化学物质设计更好的药物开发更多的 QSAR 模型。与植物化学物质研究相关的技术难点已经减少,尽管仍然需要减少此类研究的时间和成本投入,但有更好的机会探索以前无法获得的植物化学物质的生物活性。尽管仍然需要减少此类研究的时间和成本投入,但将民族药理学与 QSAR 相结合的未来可能性使我们处于一个令人兴奋的阶段,使我们能够探索全球的植物来源并设计更好的药物。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验