Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families

Abstract Insecticides are toxic substances used to control a wide variety of agricultural insect pests. Most of these are chemicals in nature, and their increasing residues in soil, water, and fruits contribute to environmental pollution, chronic human illnesses, and the emergence of insecticide res...

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Main Authors: Peter F. Farag, Aya A. Elsisi, Esraa W. Elabd, Jana J. Sadek, Nada H. Mousa, Rawan M. Zaky, Sara M. Ahmed
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-02618-3
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author Peter F. Farag
Aya A. Elsisi
Esraa W. Elabd
Jana J. Sadek
Nada H. Mousa
Rawan M. Zaky
Sara M. Ahmed
author_facet Peter F. Farag
Aya A. Elsisi
Esraa W. Elabd
Jana J. Sadek
Nada H. Mousa
Rawan M. Zaky
Sara M. Ahmed
author_sort Peter F. Farag
collection DOAJ
description Abstract Insecticides are toxic substances used to control a wide variety of agricultural insect pests. Most of these are chemicals in nature, and their increasing residues in soil, water, and fruits contribute to environmental pollution, chronic human illnesses, and the emergence of insecticide resistance phenomenon. In the context of a green environment, bioinsecticide metabolites, including proteins, are a safe alternative that mostly has selective toxicity to insects. Thus, this study aimed to predict and identify new toxin-like families through uncharacterized secreted proteins from one of the most potent entomopathogenic fungi, Beauveria bassiana ARSEF 2860, which was selected as a model. In this work, a total of 2483 amino acid sequences of uncharacterized proteins (Ups) were retrieved from the RefSeq database. Among these, 365 UPs were identified as secreted proteins using the SignalP web server. We implemented the integration of well-designed bioinformatic tools to characterize and anticipate their homologous similarities at the sequence (InterPro) and structural (AlphaFold2) levels. The structural function annotation of these proteins was predicted using DeepFRI. With 269 successfully predicted folds, we identified new putative families with pathogenesis functions related to toxins like Janus-faced atracotoxins (insecticidal spider toxin), Cry toxins (commercial insecticide from Bacillus thuringiensis), ARTs-like toxins, and other insecticidal toxins. Furthermore, some proteins that are not homologous to any known experimental data were functionally predicted as cation metal ion binding (Zn, Na, and Co) with potential toxicity. Collectively, computational structural genomics can be used to study host–pathogen interactions and predict novel families.
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spelling doaj-art-b22e5723ee0146faa497e21ea8fd27762025-08-20T03:08:40ZengNature PortfolioScientific Reports2045-23222025-05-0115111210.1038/s41598-025-02618-3Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like familiesPeter F. Farag0Aya A. Elsisi1Esraa W. Elabd2Jana J. Sadek3Nada H. Mousa4Rawan M. Zaky5Sara M. Ahmed6Department of Microbiology, Faculty of Science, Ain Shams UniversityDepartment of Microbiology, Faculty of Science, Ain Shams UniversityDepartment of Microbiology, Faculty of Science, Ain Shams UniversityDepartment of Microbiology, Faculty of Science, Ain Shams UniversityDepartment of Microbiology, Faculty of Science, Ain Shams UniversityDepartment of Microbiology, Faculty of Science, Ain Shams UniversityDepartment of Microbiology, Faculty of Science, Ain Shams UniversityAbstract Insecticides are toxic substances used to control a wide variety of agricultural insect pests. Most of these are chemicals in nature, and their increasing residues in soil, water, and fruits contribute to environmental pollution, chronic human illnesses, and the emergence of insecticide resistance phenomenon. In the context of a green environment, bioinsecticide metabolites, including proteins, are a safe alternative that mostly has selective toxicity to insects. Thus, this study aimed to predict and identify new toxin-like families through uncharacterized secreted proteins from one of the most potent entomopathogenic fungi, Beauveria bassiana ARSEF 2860, which was selected as a model. In this work, a total of 2483 amino acid sequences of uncharacterized proteins (Ups) were retrieved from the RefSeq database. Among these, 365 UPs were identified as secreted proteins using the SignalP web server. We implemented the integration of well-designed bioinformatic tools to characterize and anticipate their homologous similarities at the sequence (InterPro) and structural (AlphaFold2) levels. The structural function annotation of these proteins was predicted using DeepFRI. With 269 successfully predicted folds, we identified new putative families with pathogenesis functions related to toxins like Janus-faced atracotoxins (insecticidal spider toxin), Cry toxins (commercial insecticide from Bacillus thuringiensis), ARTs-like toxins, and other insecticidal toxins. Furthermore, some proteins that are not homologous to any known experimental data were functionally predicted as cation metal ion binding (Zn, Na, and Co) with potential toxicity. Collectively, computational structural genomics can be used to study host–pathogen interactions and predict novel families.https://doi.org/10.1038/s41598-025-02618-3AlphaFold2Beauveria bassianaInsecticidal proteinsNew familiesStructural annotations
spellingShingle Peter F. Farag
Aya A. Elsisi
Esraa W. Elabd
Jana J. Sadek
Nada H. Mousa
Rawan M. Zaky
Sara M. Ahmed
Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families
Scientific Reports
AlphaFold2
Beauveria bassiana
Insecticidal proteins
New families
Structural annotations
title Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families
title_full Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families
title_fullStr Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families
title_full_unstemmed Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families
title_short Prediction of secreted uncharacterized protein structures from Beauveria bassiana ARSEF 2860 unravels novel toxins-like families
title_sort prediction of secreted uncharacterized protein structures from beauveria bassiana arsef 2860 unravels novel toxins like families
topic AlphaFold2
Beauveria bassiana
Insecticidal proteins
New families
Structural annotations
url https://doi.org/10.1038/s41598-025-02618-3
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