ArticleInternational journal of molecular sciences2015
Aqueous Molecular Dynamics Simulations of the M. tuberculosis Enoyl-ACP Reductase-NADH System and Its Complex with a Substrate Mimic or Diphenyl Ethers Inhibitors.
Article in International journal of molecular sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 17 citations in OpenAlex.
- Identification of novel inhibitors targeting Mycobacterium abscessus InhA through virtual screening, docking, and molecular dynamic simulations.Scientific reports · 2025Article
- Molecular modelling studies and in vitro enzymatic assays identified A 4-(nitrobenzyl)guanidine derivative as inhibitor of SARS-CoV-2 Mpro.Scientific reports · 2024Article
- Perfluorinated compounds binding to estrogen receptor of different species: a molecular dynamic modeling.Journal of molecular modeling · 2018Article
- Anti-Mycobacterial Evaluation of 7-Chloro-4-Aminoquinolines and Hologram Quantitative Structure-Activity Relationship (HQSAR) Modeling of Amino-Imino Tautomers.Pharmaceuticals (Basel, Switzerland) · 2017Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular dynamics (MD) simulations of 12 aqueous systems of the NADH-dependent enoyl-ACP reductase from Mycobacterium tuberculosis (InhA) were carried out for up to 20-40 ns using the GROMACS 4.5 package. Simulations of the holoenzyme, holoenzyme-substrate, and 10 holoenzyme-inhibitor complexes were conducted in order to gain more insight about the secondary structure motifs of the InhA substrate-binding pocket. We monitored the lifetime of the main intermolecular interactions: hydrogen bonds and hydrophobic contacts. Our MD simulations demonstrate the importance of evaluating the conformational changes that occur close to the active site of the enzyme-cofactor complex before and after binding of the ligand and the influence of the water molecules. Moreover, the protein-inhibitor total steric (ELJ) and electrostatic (EC) interaction energies, related to Gly96 and Tyr158, are able to explain 80% of the biological response variance according to the best linear equation, pKi=7.772-0.1885×Gly96+0.0517×Tyr158 (R²=0.80; n=10), where interactions with Gly96, mainly electrostatic, increase the biological response, while those with Tyr158 decrease. These results will help to understand the structure-activity relationships and to design new and more potent anti-TB drugs.
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