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Role of Carbonic Anhydrases and Inhibitors in Acid–Base Physiology: Insights from Mathematical Modeling

Carbonic anhydrases (CAs) catalyze a reaction fundamental for life: the bidirectional conversion of carbon dioxide (CO(2)) and water (H(2)O) into bicarbonate (HCO(3)(−)) and protons (H(+)). These enzymes impact numerous physiological processes that occur within and across the many compartments in th...

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Detalles Bibliográficos
Autores principales: Occhipinti, Rossana, Boron, Walter F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695913/
https://www.ncbi.nlm.nih.gov/pubmed/31390837
http://dx.doi.org/10.3390/ijms20153841
Descripción
Sumario:Carbonic anhydrases (CAs) catalyze a reaction fundamental for life: the bidirectional conversion of carbon dioxide (CO(2)) and water (H(2)O) into bicarbonate (HCO(3)(−)) and protons (H(+)). These enzymes impact numerous physiological processes that occur within and across the many compartments in the body. Within compartments, CAs promote rapid H(+) buffering and thus the stability of pH-sensitive processes. Between compartments, CAs promote movements of H(+), CO(2), HCO(3)(−), and related species. This traffic is central to respiration, digestion, and whole-body/cellular pH regulation. Here, we focus on the role of mathematical modeling in understanding how CA enhances buffering as well as gradients that drive fluxes of CO(2) and other solutes (facilitated diffusion). We also examine urinary acid secretion and the carriage of CO(2) by the respiratory system. We propose that the broad physiological impact of CAs stem from three fundamental actions: promoting H(+) buffering, enhancing H(+) exchange between buffer systems, and facilitating diffusion. Mathematical modeling can be a powerful tool for: (1) clarifying the complex interdependencies among reaction, diffusion, and protein-mediated components of physiological processes; (2) formulating hypotheses and making predictions to be tested in wet-lab experiments; and (3) inferring data that are impossible to measure.