了解结核病药物发现的主要挑战:未来会怎样?

IF 6 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Rima Zein-Eddine, Masoud Ramuz, Guislaine Refrégier, Johannes F Lutzeyer, Alexey Aleksandrov, Hannu Myllykallio
{"title":"了解结核病药物发现的主要挑战:未来会怎样?","authors":"Rima Zein-Eddine, Masoud Ramuz, Guislaine Refrégier, Johannes F Lutzeyer, Alexey Aleksandrov, Hannu Myllykallio","doi":"10.1080/17460441.2025.2531229","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global health concern. It spreads through airborne droplets and has a high mortality rate, particularly without treatment. Drug resistance is rising, with treatments against multidrug-resistant TB (MDR-TB) showing poor treatment success rates. The thick, lipid-rich wall of Mtb and its slow growth reduce antibiotic effectiveness, requiring long treatment courses of 4-6 months. Current therapies often fail against drug-resistant strains, highlighting the urgent need for new, short-course treatment, affordable, and combination-friendly drugs.</p><p><strong>Areas covered: </strong>Within this perspective, the authors review and comment on the following topics regarding Mtb resistance emergence and treatment strategies: i) Existing treatment ii) Resistance evolution in Mtb; iii) Key challenges in drug discovery targeting Mtb; iv) emerging strategies and recent advances in Mtb drug discovery, and v) Next-generation approaches. Literature was identified through a search of PubMed, google scholar, and web of science, from January 2010 to March 2025.</p><p><strong>Expert opinion: </strong>AI is accelerating the discovery of bioavailable and safe preclinical drug candidates for TB, though data limitations and biological complexity remain challenging. Future progress requires multi-modal models, open-access datasets, and interdisciplinary collaboration.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-16"},"PeriodicalIF":6.0000,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding the key challenges in tuberculosis drug discovery: what does the future hold?\",\"authors\":\"Rima Zein-Eddine, Masoud Ramuz, Guislaine Refrégier, Johannes F Lutzeyer, Alexey Aleksandrov, Hannu Myllykallio\",\"doi\":\"10.1080/17460441.2025.2531229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global health concern. It spreads through airborne droplets and has a high mortality rate, particularly without treatment. Drug resistance is rising, with treatments against multidrug-resistant TB (MDR-TB) showing poor treatment success rates. The thick, lipid-rich wall of Mtb and its slow growth reduce antibiotic effectiveness, requiring long treatment courses of 4-6 months. Current therapies often fail against drug-resistant strains, highlighting the urgent need for new, short-course treatment, affordable, and combination-friendly drugs.</p><p><strong>Areas covered: </strong>Within this perspective, the authors review and comment on the following topics regarding Mtb resistance emergence and treatment strategies: i) Existing treatment ii) Resistance evolution in Mtb; iii) Key challenges in drug discovery targeting Mtb; iv) emerging strategies and recent advances in Mtb drug discovery, and v) Next-generation approaches. Literature was identified through a search of PubMed, google scholar, and web of science, from January 2010 to March 2025.</p><p><strong>Expert opinion: </strong>AI is accelerating the discovery of bioavailable and safe preclinical drug candidates for TB, though data limitations and biological complexity remain challenging. Future progress requires multi-modal models, open-access datasets, and interdisciplinary collaboration.</p>\",\"PeriodicalId\":12267,\"journal\":{\"name\":\"Expert Opinion on Drug Discovery\",\"volume\":\" \",\"pages\":\"1-16\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2025-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Opinion on Drug Discovery\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/17460441.2025.2531229\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Opinion on Drug Discovery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/17460441.2025.2531229","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

摘要

由结核分枝杆菌(Mtb)引起的结核病(TB)仍然是一个主要的全球卫生问题。它通过空气中的飞沫传播,死亡率很高,特别是在没有治疗的情况下。耐药性正在上升,针对耐多药结核病(MDR-TB)的治疗成功率很低。结核分枝杆菌厚且富含脂质的壁及其生长缓慢降低了抗生素的有效性,需要4-6个月的长疗程。目前的治疗方法对耐药菌株往往无效,这突出表明迫切需要新的、短期的、负担得起的和联合友好的药物。涵盖的领域:从这个角度来看,作者回顾和评论了以下关于结核分枝杆菌耐药性出现和治疗策略的主题:i)现有治疗ii)结核分枝杆菌耐药性演变;iii)针对结核分枝杆菌的药物发现面临的主要挑战;4)结核分枝杆菌药物发现的新策略和最新进展,5)下一代方法。从2010年1月到2025年3月,通过PubMed、b谷歌scholar和web of science的搜索确定了文献。专家意见:人工智能正在加速发现生物可利用和安全的结核病临床前候选药物,尽管数据限制和生物学复杂性仍然具有挑战性。未来的进展需要多模态模型、开放获取数据集和跨学科合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding the key challenges in tuberculosis drug discovery: what does the future hold?

Introduction: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global health concern. It spreads through airborne droplets and has a high mortality rate, particularly without treatment. Drug resistance is rising, with treatments against multidrug-resistant TB (MDR-TB) showing poor treatment success rates. The thick, lipid-rich wall of Mtb and its slow growth reduce antibiotic effectiveness, requiring long treatment courses of 4-6 months. Current therapies often fail against drug-resistant strains, highlighting the urgent need for new, short-course treatment, affordable, and combination-friendly drugs.

Areas covered: Within this perspective, the authors review and comment on the following topics regarding Mtb resistance emergence and treatment strategies: i) Existing treatment ii) Resistance evolution in Mtb; iii) Key challenges in drug discovery targeting Mtb; iv) emerging strategies and recent advances in Mtb drug discovery, and v) Next-generation approaches. Literature was identified through a search of PubMed, google scholar, and web of science, from January 2010 to March 2025.

Expert opinion: AI is accelerating the discovery of bioavailable and safe preclinical drug candidates for TB, though data limitations and biological complexity remain challenging. Future progress requires multi-modal models, open-access datasets, and interdisciplinary collaboration.

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
CiteScore
10.20
自引率
1.60%
发文量
78
审稿时长
6-12 weeks
期刊介绍: Expert Opinion on Drug Discovery (ISSN 1746-0441 [print], 1746-045X [electronic]) is a MEDLINE-indexed, peer-reviewed, international journal publishing review articles on novel technologies involved in the drug discovery process, leading to new leads and reduced attrition rates. Each article is structured to incorporate the author’s own expert opinion on the scope for future development. The Editors welcome: Reviews covering chemoinformatics; bioinformatics; assay development; novel screening technologies; in vitro/in vivo models; structure-based drug design; systems biology Drug Case Histories examining the steps involved in the preclinical and clinical development of a particular drug The audience consists of scientists and managers in the healthcare and pharmaceutical industry, academic pharmaceutical scientists and other closely related professionals looking to enhance the success of their drug candidates through optimisation at the preclinical level.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信