Your browser doesn't support javascript.
loading
Computational modelling of efflux pumps and their inhibitors.
Ramaswamy, Venkata Krishnan; Cacciotto, Pierpaolo; Malloci, Giuliano; Vargiu, Attilio V; Ruggerone, Paolo.
Afiliación
  • Ramaswamy VK; Department of Physics, University of Cagliari, Monserrato, Cagliari, Italy.
  • Cacciotto P; Department of Physics, University of Cagliari, Monserrato, Cagliari, Italy.
  • Malloci G; Department of Physics, University of Cagliari, Monserrato, Cagliari, Italy.
  • Vargiu AV; Department of Physics, University of Cagliari, Monserrato, Cagliari, Italy.
  • Ruggerone P; Department of Physics, University of Cagliari, Monserrato, Cagliari, Italy paolo.ruggerone@dsf.unica.it.
Essays Biochem ; 61(1): 141-156, 2017 02 28.
Article en En | MEDLINE | ID: mdl-28258237
ABSTRACT
Antimicrobial resistance is based on the multifarious strategies that bacteria adopt to face antibiotic therapies, making it a key public health concern of our era. Among these strategies, efflux pumps (EPs) contribute significantly to increase the levels and profiles of resistance by expelling a broad range of unrelated compounds - buying time for the organisms to develop specific resistance. In Gram-negative bacteria, many of these chromosomally encoded transporters form multicomponent 'pumps' that span both inner and outer membranes and are driven energetically by a primary or secondary transporter component.One of the strategies to reinvigorate the efficacy of antimicrobials is by joint administration with EP inhibitors (EPI), which either block the substrate binding and/or hinder any of the transport-dependent steps of the pump. In this review, we provide an overview of multidrug-resistance EPs, their inhibition strategies and the relevant findings from the various computational simulation studies reported to date with respect to deciphering the mechanism of action of inhibitors with the purpose of improving their rational design.
Asunto(s)
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteínas Bacterianas / Simulación por Computador Tipo de estudio: Prognostic_studies Idioma: En Revista: Essays Biochem Año: 2017 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteínas Bacterianas / Simulación por Computador Tipo de estudio: Prognostic_studies Idioma: En Revista: Essays Biochem Año: 2017 Tipo del documento: Article País de afiliación: Italia