In silico drug design strategies for discovering novel tuberculosis therapeutics.

IF 6 2区 医学 Q1 PHARMACOLOGY & PHARMACY Expert Opinion on Drug Discovery Pub Date : 2024-04-01 Epub Date: 2024-02-19 DOI:10.1080/17460441.2024.2319042
Christian S Carnero Canales, Aline Renata Pavan, Jean Leandro Dos Santos, Fernando Rogério Pavan
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Abstract

Introduction: Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments.

Areas covered: In this review, the authors explore recent advancements in tuberculosis drug discovery enabled by in silico tools. The main objectives of this review article are to highlight emerging drug candidates identified through in silico methods and to provide an update on the therapeutic targets associated with Mycobacterium tuberculosis.

Expert opinion: These in silico methods have not only streamlined the drug discovery process but also opened up new horizons for finding novel drug candidates and repositioning existing ones. The continued advancements in these fields hold great promise for more efficient, ethical, and successful drug development in the future.

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发现新型结核病疗法的硅学药物设计策略。
导言:由于其复杂的生物学特性和产生抗生素耐药性的倾向,结核病仍然是全球公共卫生领域的一个重大问题。发现新药是一项旷日持久、耗资巨大的工作,通常需要十多年的时间,花费数十亿美元。然而,计算机辅助药物设计(CADD)作为一种更灵活、更具成本效益的替代方法已经浮出水面。计算机辅助药物设计(CADD)工具使我们能够破译治疗靶点与新型药物之间的相互作用,使其在寻找新的结核病治疗方法的过程中成为无价之宝:在这篇综述中,作者探讨了利用硅学工具发现结核病药物的最新进展。这篇综述文章的主要目的是重点介绍通过硅学方法发现的新候选药物,并提供与结核分枝杆菌相关的治疗靶点的最新情况:这些硅学方法不仅简化了药物发现过程,还为寻找新型候选药物和重新定位现有候选药物开辟了新天地。这些领域的持续进步为未来更高效、更道德和更成功的药物开发带来了巨大希望。
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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.
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