Molecular Rationale behind the Differential Substrate Specificity of Bacterial RND Multi-Drug Transporters

Abstract Resistance-Nodulation-cell Division (RND) transporters AcrB and AcrD of Escherichia coli expel a wide range of substrates out of the cell in conjunction with AcrA and TolC, contributing to the onset of bacterial multidrug resistance. Despite sharing an overall sequence identity of ~66% (sim...

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Autores principales: Venkata Krishnan Ramaswamy, Attilio V. Vargiu, Giuliano Malloci, Jürg Dreier, Paolo Ruggerone
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/392930ee1eca422298bd285496cace51
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Sumario:Abstract Resistance-Nodulation-cell Division (RND) transporters AcrB and AcrD of Escherichia coli expel a wide range of substrates out of the cell in conjunction with AcrA and TolC, contributing to the onset of bacterial multidrug resistance. Despite sharing an overall sequence identity of ~66% (similarity ~80%), these RND transporters feature distinct substrate specificity patterns whose underlying basis remains elusive. We performed exhaustive comparative analyses of the putative substrate binding pockets considering crystal structures, homology models and conformations extracted from multi-copy μs-long molecular dynamics simulations of both AcrB and AcrD. The impact of physicochemical and topographical properties (volume, shape, lipophilicity, electrostatic potential, hydration and distribution of multi-functional sites) within the pockets on their substrate specificities was quantitatively assessed. Differences in the lipophilic and electrostatic potentials among the pockets were identified. In particular, the deep pocket of AcrB showed the largest lipophilicity convincingly pointing out its possible role as a lipophilicity-based selectivity filter. Furthermore, we identified dynamic features (not inferable from sequence analysis or static structures) such as different flexibilities of specific protein loops that could potentially influence the substrate recognition and transport profile. Our findings can be valuable for drawing structure (dynamics)-activity relationship to be employed in drug design.