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.

Integrated in silico and in vitro screening approaches for the discovery of small-molecule inhibitors of β-carbonic anhydrases / Bhowmik R., D'Agostino I., Angeli A., Aspatwar A.. - In: EXPERT OPINION ON DRUG DISCOVERY. - ISSN 1746-0441. - ELETTRONICO. - 21:(2026), pp. 319-337. [10.1080/17460441.2026.2636772]

Integrated in silico and in vitro screening approaches for the discovery of small-molecule inhibitors of β-carbonic anhydrases

Angeli A.;
2026

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.
2026
21
319
337
Bhowmik R.; D'Agostino I.; Angeli A.; Aspatwar A.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1467578
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