In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani
Fusarium solani is worrisome because it severely threatens the agricultural productivity of certain crops such as tomatoes and peas, causing the general decline, wilting, and root necrosis. It has also been implicated in the infection of the human eye cornea. It is believed that early detection of t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Bioinformatics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2022.972529/full |
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| author | Olalekan Olanrewaju Bakare Olalekan Olanrewaju Bakare Arun Gokul Muhali Olaide Jimoh Ashwil Klein Marshall Keyster |
| author_facet | Olalekan Olanrewaju Bakare Olalekan Olanrewaju Bakare Arun Gokul Muhali Olaide Jimoh Ashwil Klein Marshall Keyster |
| author_sort | Olalekan Olanrewaju Bakare |
| collection | DOAJ |
| description | Fusarium solani is worrisome because it severely threatens the agricultural productivity of certain crops such as tomatoes and peas, causing the general decline, wilting, and root necrosis. It has also been implicated in the infection of the human eye cornea. It is believed that early detection of the fungus could save these crops from the destructive activities of the fungus through early biocontrol measures. Therefore, the present work aimed to build a sensitive model of novel anti-Fusarium solani antimicrobial peptides (AMPs) against the fungal cutinase 1 (CUT1) protein for early, sensitive and accurate detection. Fusarium solani CUT1 receptor protein 2D secondary structure, model validation, and functional motifs were predicted. Subsequently, anti-Fusarium solani AMPs were retrieved, and the HMMER in silico algorithm was used to construct a model of the AMPs. After their structure predictions, the interaction analysis was analyzed for the Fusarium solani CUT1 protein and the generated AMPs. The putative anti-Fusarium solani AMPs bound the CUT1 protein very tightly, with OOB4 having the highest binding energy potential for HDock. The pyDockWeb generated high electrostatic, desolvation, and low van der Waals energies for all the AMPs against CUT1 protein, with OOB1 having the most significant interaction. The results suggested the utilization of AMPs for the timely intervention, control, and management of these crops, as mentioned earlier, to improve their agricultural productivity and reduce their economic loss and the use of HMMER for constructing models for disease detection. |
| first_indexed | 2024-04-12T16:56:49Z |
| format | Article |
| id | doaj.art-7c79a83e58ae4245ad0c75df83c27fd5 |
| institution | Directory Open Access Journal |
| issn | 2673-7647 |
| language | English |
| last_indexed | 2024-04-12T16:56:49Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj.art-7c79a83e58ae4245ad0c75df83c27fd52022-12-22T03:24:13ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472022-09-01210.3389/fbinf.2022.972529972529In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solaniOlalekan Olanrewaju Bakare0Olalekan Olanrewaju Bakare1Arun Gokul2Muhali Olaide Jimoh3Ashwil Klein4Marshall Keyster5Environmental Biotechnology Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South AfricaDepartment of Biochemistry, Faculty of Basic Medical Sciences, Olabisi Onabanjo University, Sagamu, Ogun State, NigeriaDepartment of Plant Sciences, Qwaqwa Campus, University of the Free State, Phuthadithjaba, South AfricaDepartment of Plant Science, Faculty of Sciences, Olabisi Onabanjo University, Ago-Iwoye, NigeriaPlant Omics Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South AfricaEnvironmental Biotechnology Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South AfricaFusarium solani is worrisome because it severely threatens the agricultural productivity of certain crops such as tomatoes and peas, causing the general decline, wilting, and root necrosis. It has also been implicated in the infection of the human eye cornea. It is believed that early detection of the fungus could save these crops from the destructive activities of the fungus through early biocontrol measures. Therefore, the present work aimed to build a sensitive model of novel anti-Fusarium solani antimicrobial peptides (AMPs) against the fungal cutinase 1 (CUT1) protein for early, sensitive and accurate detection. Fusarium solani CUT1 receptor protein 2D secondary structure, model validation, and functional motifs were predicted. Subsequently, anti-Fusarium solani AMPs were retrieved, and the HMMER in silico algorithm was used to construct a model of the AMPs. After their structure predictions, the interaction analysis was analyzed for the Fusarium solani CUT1 protein and the generated AMPs. The putative anti-Fusarium solani AMPs bound the CUT1 protein very tightly, with OOB4 having the highest binding energy potential for HDock. The pyDockWeb generated high electrostatic, desolvation, and low van der Waals energies for all the AMPs against CUT1 protein, with OOB1 having the most significant interaction. The results suggested the utilization of AMPs for the timely intervention, control, and management of these crops, as mentioned earlier, to improve their agricultural productivity and reduce their economic loss and the use of HMMER for constructing models for disease detection.https://www.frontiersin.org/articles/10.3389/fbinf.2022.972529/fullFusarium solaniproteinin silicoenergiesfungus |
| spellingShingle | Olalekan Olanrewaju Bakare Olalekan Olanrewaju Bakare Arun Gokul Muhali Olaide Jimoh Ashwil Klein Marshall Keyster In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani Frontiers in Bioinformatics Fusarium solani protein in silico energies fungus |
| title | In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani |
| title_full | In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani |
| title_fullStr | In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani |
| title_full_unstemmed | In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani |
| title_short | In silico discovery of biomarkers for the accurate and sensitive detection of Fusarium solani |
| title_sort | in silico discovery of biomarkers for the accurate and sensitive detection of fusarium solani |
| topic | Fusarium solani protein in silico energies fungus |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2022.972529/full |
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