Targeting the cell wall of Mycobacterium tuberculosis: a molecular modeling investigation of the interaction of imipenem and meropenem with L,D-transpeptidase 2.

J Biomol Struct Dyn

a Laboratório de Planejamento e Desenvolvimento de Fármacos, Instituto de Ciências Exatas e Naturais , Universidade Federal do Pará , CP 11101, Belém , PA 66075-110 , Brazil.

Published: October 2016

AI Article Synopsis

  • A single crystal X-ray structure of the enzyme L,D-transpeptidase (ex-LdtMt2) revealed that imipenem and meropenem inhibit its activity, with imipenem being more effective.
  • Through molecular modeling, the binding interactions of nine commercially available inhibitors were analyzed, confirming that calculated binding energies matched experimental data for imipenem and meropenem.
  • The study also highlighted the solvation interaction energy (SIE) method as an accurate and cost-effective way to predict carbapenem affinities, while providing a theoretical explanation for the entropy penalty observed with meropenem.

Article Abstract

The single crystal X-ray structure of the extracellular portion of the L,D-transpeptidase (ex-LdtMt2 - residues 120-408) enzyme was recently reported. It was observed that imipenem and meropenem inhibit activity of this enzyme, responsible for generating L,D-transpeptide linkages in the peptidoglycan layer of Mycobacterium tuberculosis. Imipenem is more active and isothermal titration calorimetry experiments revealed that meropenem is subjected to an entropy penalty upon binding to the enzyme. Herein, we report a molecular modeling approach to obtain a molecular view of the inhibitor/enzyme interactions. The average binding free energies for nine commercially available inhibitors were calculated using MM/GBSA and Solvation Interaction Energy (SIE) approaches and the calculated energies corresponded well with the available experimentally observed results. The method reproduces the same order of binding energies as experimentally observed for imipenem and meropenem. We have also demonstrated that SIE is a reasonably accurate and cost-effective free energy method, which can be used to predict carbapenem affinities for this enzyme. A theoretical explanation was offered for the experimental entropy penalty observed for meropenem, creating optimism that this computational model can serve as a potential computational model for other researchers in the field.

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Source
http://dx.doi.org/10.1080/07391102.2015.1029000DOI Listing

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