Ratul Bhowmik, Ilaria D'Agostino, Andrea Angeli, Ashok Aspatwar
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引用次数: 0
Abstract
Introduction: β-Carbonic anhydrases (β-CAs) are zinc-dependent metalloenzymes that catalyze the reversible hydration of carbon dioxide to bicarbonate and protons. They are widely distributed in bacteria, where they support pH regulation, inorganic carbon homeostasis, and central metabolism. Unlike humans, which express only α-class carbonic anhydrases, many bacterial pathogens encode β-CAs, highlighting these enzymes as attractive antibacterial targets with reduced risk of host cross-reactivity.
Areas covered: This review discusses integrated in silico and in vitro strategies for the discovery and validation of small-molecule inhibitors targeting bacterial β-CAs. Computational approaches - including pharmacophore modeling, molecular docking, molecular dynamics simulations, and machine learning - are increasingly used to prioritize and optimize candidate inhibitors. Experimental validation employs enzymatic activity assays, biophysical binding techniques, and whole-cell assays to assess target engagement and antibacterial effects. Current inhibitor classes include sulfonamides, coumarins, dithiocarbamates, phenolic compounds, and natural products, with selected chemotypes demonstrating antibacterial or antivirulence activity in specific models. Relevant literature was identified through searches of PubMed, Web of Science, and Scopus, focusing on studies published between approximately 2000 and 2025.
Expert opinion: β-CAs represent a tractable yet underexploited antibacterial target class. Successful translation will depend on improving bacterial penetration, pharmacokinetics, and target engagement. When strategically positioned as adjunctive or context-dependent therapies, β-CA inhibitors may contribute to the treatment of drug-resistant bacterial infections, including tuberculosis.
简介:β-碳酸酐酶(β-CAs)是锌依赖的金属酶,催化二氧化碳可逆水合成碳酸氢盐和质子。它们广泛分布于细菌中,支持pH调节、无机碳稳态和中枢代谢。与人类只表达α-类碳酸酐酶不同,许多细菌病原体编码β-CAs,突出这些酶作为有吸引力的抗菌靶点,降低了宿主交叉反应的风险。涉及领域:本综述讨论了针对细菌β-CAs的小分子抑制剂的发现和验证的集成硅和体外策略。计算方法——包括药效团建模、分子对接、分子动力学模拟和机器学习——越来越多地用于确定候选抑制剂的优先级和优化。实验验证采用酶活性分析、生物物理结合技术和全细胞分析来评估靶标接合和抗菌效果。目前的抑制剂类别包括磺胺类、香豆素类、二硫代氨基甲酸酯类、酚类化合物和天然产物,在特定模型中具有选定的化学型,显示出抗菌或抗毒活性。相关文献通过PubMed、Web of Science和Scopus检索确定,重点关注2000年至2025年间发表的研究。专家意见:β-CAs是一种易于处理但尚未充分利用的抗菌靶标类。成功的翻译将取决于提高细菌渗透,药代动力学和目标接合。当战略性地定位为辅助疗法或情境依赖疗法时,β-CA抑制剂可能有助于治疗耐药细菌感染,包括结核病。
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.