Elucidating fungicide complex formation mechanisms with Phytophthora infestans target proteins: In silico insights

The development of new pesticides as well as new approaches in their application are important challenges for food security. Currently, bioinformatics methods are useful for searching and designing models of molecular target structures, including antiviral, fungicidal, bactericidal, insecticidal, herbicidal drugs and plant growth regulators, which have been recently used in agrochemical research. In this article, we present the findings of a study investigating the molecular mechanisms underlying the binding of fungicides (fluopicolide, propamocarb) to target proteins (cytochrome P450, glutathione-S-transferases) of Phytophthora infestans . Virtual three-dimensional complexes of pesticides and their targets have been created using bioinformatics methods. A new approach for identifying the cavity parameters of binding sites using machine learning technology has been proposed. Rigid docking of pesticides with targets has been carried out and the binding energy calculation showed a high degree of stability of ligand-protein complexes. Our proposed in silico approach may be useful for studying the molecular mechanisms of fungicides action on Phytophthora proteins.

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Publication Details

Journal
BIORISK – Biodiversity and Ecosystem Risk Assessment
Published
2025-10-03
DOI
https://doi.org/10.3897/biorisk.23.139718
Primary Topic
Plant Pathogens and Resistance
Type
article
Field-Weighted Citation Impact
0.00

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article

Elucidating fungicide complex formation mechanisms with Phytophthora infestans target proteins: In silico insights

Kirill Sergeevich Golokhvast, Mengcen Wang, P. D. Timkin, Yusufjon Gafforov et al.
BIORISK – Biodiversity and Ecosystem Risk Assessment
Plant Pathogens and Resistance
article

Elucidating fungicide complex formation mechanisms with Phytophthora infestans target proteins: In silico insights

Kirill Sergeevich Golokhvast, Mengcen Wang, P. D. Timkin, Yusufjon Gafforov, Kun Qiao, I. E. Pamirsky, Alisher Baxtibaevich Ajiev
article en

Abstract

The development of new pesticides as well as new approaches in their application are important challenges for food security. Currently, bioinformatics methods are useful for searching and designing models of molecular target structures, including antiviral, fungicidal, bactericidal, insecticidal, herbicidal drugs and plant growth regulators, which have been recently used in agrochemical research. In this article, we present the findings of a study investigating the molecular mechanisms underlying the binding of fungicides (fluopicolide, propamocarb) to target proteins (cytochrome P450, glutathione-S-transferases) of Phytophthora infestans . Virtual three-dimensional complexes of pesticides and their targets have been created using bioinformatics methods. A new approach for identifying the cavity parameters of binding sites using machine learning technology has been proposed. Rigid docking of pesticides with targets has been carried out and the binding energy calculation showed a high degree of stability of ligand-protein complexes. Our proposed in silico approach may be useful for studying the molecular mechanisms of fungicides action on Phytophthora proteins.

BIORISK – Biodiversity and Ecosystem Risk AssessmentVol. 23
City University of Hong Kong (HK), National Research Tomsk State University (RU), Tashkent State Technical University named after Islam Karimov (UZ), Krasnoyarsk Scientific Center (RU), All-Russian Scientific Research Institute of Soybean (RU), Ferghana Polytechnical Institute (UZ), Nukus State Pedagogical Institute named after Ajiniyaz (UZ), City University of Hong Kong, Shenzhen Research Institute (CN), Siberian Research Institute of Agriculture and Peat (RU), New Uzbekistan University (UZ), National University of Uzbekistan (UZ), Zhejiang University (CN)
National Natural Science Foundation of China, Tomsk State University, Fundamental Research Funds for the Central Universities, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 80%
Plant Pathogens and Resistance
DOIOpen Access PDFOpenAlex
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