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<p>In computational biology and bioinformatics, molecular docking and molecular dynamics simulations play pivotal roles in predicting potential ligand targets and comprehending the intricate mechanisms of ligand-protein interactions. This study emphasized the use of in silico techniques to scrutinize the binding affinities and dynamic behaviors of selected ligands derived from GC-MS/MS analysis with specific target proteins, aiming to unravel their potential mechanisms of action. The proteins were modeled using a homology approach and meticulously validated using Ramachandran plots and hydropathy analysis to confidently predict their membrane activity. The docking procedure was performed using AutoDock Vina and visualized using Discovery Studio and Schrödinger Maestro software. Multiple rigorous studies of ligand-protein interactions have been conducted, revealing that all ligands exhibit binding scores above − 5&#xa0;kcal/mol. Notably, 4,22-Stigmastadiene-3-one and Lanosta-8,24-dien-3-one demonstrated significant binding affinities with cytochrome oxidase 6, achieving scores of -10.1&#xa0;kcal/mol and − 10.4&#xa0;kcal/mol, respectively, while gamma-Sitosterol exhibited a score of -9.9&#xa0;kcal/mol. Further analysis of acetylcholinesterase indicated robust binding affinities for gamma-Sitosterol and Lanosta-8,24-dien-3-one with scores of -9.1&#xa0;kcal/mol and − 9.0&#xa0;kcal/mol, respectively. Glutathione S transferase 2 displayed the highest binding energy with gamma-Sitosterol (-10.5&#xa0;kcal/mol), while Glutathione S transferase theta exhibited the lowest binding energy. The study also incorporated Odorant binding proteins and electroantennogram results, which underscored the biological relevance of the identified ligands in insect olfaction, further supporting their potential as insecticides. These interactions were characterized by noncovalent bonds, which ensured stability. The comprehensive docking results offer valuable insights into potential inhibitory mechanisms for both insecticidal and synergistic applications in pest management.</p>

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Metabolite-guided disruption of Spodoptera frugiperda: molecular docking and EAD insights for targeted control

  • 期刊论文

  • 发表日期：

    2026年1月27日

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  • Komala Gudla,
  • Shanthi Mookiah,
  • Murugan Marimuthu,
  • Sujayanand Gopalakrishnan Kesharivarmen,
  • Vellaikumar Sampathrajan,
  • Preetha Gnanadhas,
  • Kavitha Govindasamy,
  • Prakash Kolanchi

摘要

In computational biology and bioinformatics, molecular docking and molecular dynamics simulations play pivotal roles in predicting potential ligand targets and comprehending the intricate mechanisms of ligand-protein interactions. This study emphasized the use of in silico techniques to scrutinize the binding affinities and dynamic behaviors of selected ligands derived from GC-MS/MS analysis with specific target proteins, aiming to unravel their potential mechanisms of action. The proteins were modeled using a homology approach and meticulously validated using Ramachandran plots and hydropathy analysis to confidently predict their membrane activity. The docking procedure was performed using AutoDock Vina and visualized using Discovery Studio and Schrödinger Maestro software. Multiple rigorous studies of ligand-protein interactions have been conducted, revealing that all ligands exhibit binding scores above − 5 kcal/mol. Notably, 4,22-Stigmastadiene-3-one and Lanosta-8,24-dien-3-one demonstrated significant binding affinities with cytochrome oxidase 6, achieving scores of -10.1 kcal/mol and − 10.4 kcal/mol, respectively, while gamma-Sitosterol exhibited a score of -9.9 kcal/mol. Further analysis of acetylcholinesterase indicated robust binding affinities for gamma-Sitosterol and Lanosta-8,24-dien-3-one with scores of -9.1 kcal/mol and − 9.0 kcal/mol, respectively. Glutathione S transferase 2 displayed the highest binding energy with gamma-Sitosterol (-10.5 kcal/mol), while Glutathione S transferase theta exhibited the lowest binding energy. The study also incorporated Odorant binding proteins and electroantennogram results, which underscored the biological relevance of the identified ligands in insect olfaction, further supporting their potential as insecticides. These interactions were characterized by noncovalent bonds, which ensured stability. The comprehensive docking results offer valuable insights into potential inhibitory mechanisms for both insecticidal and synergistic applications in pest management.