Virtual screening of natural products against 5-enolpyruvylshikimate-3-phosphate synthase using the Anagreen herbicide-like natural compound library

Maycon V. de Oliveira, Gilson Mateus Bittencourt Fernandes, Kauê S. da Costa*, Serhii Vakal*, Anderson H. Lima*

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    6 Citations (Scopus)
    26 Downloads (Pure)

    Abstract

    The shikimate pathway enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) catalyzes a reaction involved in the production of amino acids essential for plant growth and survival. EPSPS is the main target of glyphosate, a broad-spectrum herbicide that acts as a competitive inhibitor concerning phosphoenolpyruvate (PEP), which is the natural substrate of EPSPS. In the present study, we introduce a natural compound library, named Anagreen, which is a compendium of herbicide-like compounds obtained from different natural product databases. Herein, we combined the structure- and ligand-based virtual screening strategies to explore Anagreen against EPSPS using the structure of glyphosate complexed with a T102I/P106S mutant of EPSPS from Eleusine indica (EiEPSPS) as a starting point. First, ligand-based pharmacophore screening was performed to select compounds with a similar pharmacophore to glyphosate. Then, structure-based pharmacophore modeling was applied to build a model which represents the molecular features of glyphosate. Then, consensus docking was performed to rank the best poses of the natural compounds against the PEP binding site, and then molecular dynamics simulations were performed to analyze the stability of EPSPS complexed with the selected ligands. Finally, we have investigated the binding affinity of the complexes using free energy calculations. The selected hit compound, namely AG332841, showed a stable conformation and binding affinity to the EPSPS structure and showed no structural similarity to the already known weed EPSPS inhibitors. Our computational study aims to clarify the inhibition of the mutant EiEPSPS, which is resistant to glyphosate, and identify new potential herbicides from natural products.
    Original languageEnglish
    Pages (from-to)18834-18847
    Number of pages14
    JournalRSC Advances
    Volume12
    Issue number29
    DOIs
    Publication statusPublished - 29 Jun 2022
    MoE publication typeA1 Journal article-refereed

    Keywords

    • herbicide
    • molecular modeling
    • in silico
    • glyphosate
    • virtual screening

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