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Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network
BACKGROUND: Although leishmaniasis is regarded as a public health problem, no effective vaccine or decisive treatment has been introduced for this disease. Therefore, representing novel therapeutic proteins is essential. Protein-protein Interaction network analysis is a suitable tool to discover nov...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Salvia Medical Sciences Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344062/ https://www.ncbi.nlm.nih.gov/pubmed/34466438 http://dx.doi.org/10.22086/gmj.v0i0.1129 |
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author | Amiri Dashatan, Nasrin Rezaie Tavirani, Mostafa Zali, Hakimeh Koushki, Mehdi Ahmadi, Nayebali |
author_facet | Amiri Dashatan, Nasrin Rezaie Tavirani, Mostafa Zali, Hakimeh Koushki, Mehdi Ahmadi, Nayebali |
author_sort | Amiri Dashatan, Nasrin |
collection | PubMed |
description | BACKGROUND: Although leishmaniasis is regarded as a public health problem, no effective vaccine or decisive treatment has been introduced for this disease. Therefore, representing novel therapeutic proteins is essential. Protein-protein Interaction network analysis is a suitable tool to discover novel drug targets for leishmania major. To this aim, gene and protein expression data is used for instructing protein network and the key proteins are highlighted. MATERIALS AND METHODS: In this computational and bioinformatics study, the protein/gene expression data related to leishmania major were studied, and 252 candidate proteins were extracted. Then, the protein networks of these proteins were explored and visualized by using String database and Cytoscape software. Finally, clustering and gene ontology were performed by MCODE and PANTHER databases, respectively. RESULTS: Based on gene ontology analysis, most of the leishmania major proteins were located in cell compartments and membrane. Catalytic activity and binding were regarded as the relevant molecular functions and metabolic and cellular processes were the significant biological process. In this network analysis, UB-EP52, EF-2, chaperonin, Hsp70.4, Hsp60, tubulin alpha and beta chain, and ENOL and LACK were introduced as hub-bottleneck proteins. Based on clustering analysis, Lmjf.32.3270, ENOL and Lmjf.13.0290 were determined as seed proteins in each cluster. CONCLUSION: The results indicated that hub proteins play a significant role in pathogenesis and life cycle of leishmania major. Further studies of hubs will provide a better understanding of leishmaniasis mechanisms. Finally, these key hub proteins could be a suitable and helpful potential for drug targets and treating leishmaniasis by considering their validation. |
format | Online Article Text |
id | pubmed-8344062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Salvia Medical Sciences Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-83440622021-08-30 Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network Amiri Dashatan, Nasrin Rezaie Tavirani, Mostafa Zali, Hakimeh Koushki, Mehdi Ahmadi, Nayebali Galen Med J Original Article BACKGROUND: Although leishmaniasis is regarded as a public health problem, no effective vaccine or decisive treatment has been introduced for this disease. Therefore, representing novel therapeutic proteins is essential. Protein-protein Interaction network analysis is a suitable tool to discover novel drug targets for leishmania major. To this aim, gene and protein expression data is used for instructing protein network and the key proteins are highlighted. MATERIALS AND METHODS: In this computational and bioinformatics study, the protein/gene expression data related to leishmania major were studied, and 252 candidate proteins were extracted. Then, the protein networks of these proteins were explored and visualized by using String database and Cytoscape software. Finally, clustering and gene ontology were performed by MCODE and PANTHER databases, respectively. RESULTS: Based on gene ontology analysis, most of the leishmania major proteins were located in cell compartments and membrane. Catalytic activity and binding were regarded as the relevant molecular functions and metabolic and cellular processes were the significant biological process. In this network analysis, UB-EP52, EF-2, chaperonin, Hsp70.4, Hsp60, tubulin alpha and beta chain, and ENOL and LACK were introduced as hub-bottleneck proteins. Based on clustering analysis, Lmjf.32.3270, ENOL and Lmjf.13.0290 were determined as seed proteins in each cluster. CONCLUSION: The results indicated that hub proteins play a significant role in pathogenesis and life cycle of leishmania major. Further studies of hubs will provide a better understanding of leishmaniasis mechanisms. Finally, these key hub proteins could be a suitable and helpful potential for drug targets and treating leishmaniasis by considering their validation. Salvia Medical Sciences Ltd 2018-06-12 /pmc/articles/PMC8344062/ /pubmed/34466438 http://dx.doi.org/10.22086/gmj.v0i0.1129 Text en Copyright© 2018, Galen Medical Journal. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ) |
spellingShingle | Original Article Amiri Dashatan, Nasrin Rezaie Tavirani, Mostafa Zali, Hakimeh Koushki, Mehdi Ahmadi, Nayebali Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network |
title |
Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network
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title_full |
Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network
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title_fullStr |
Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network
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title_full_unstemmed |
Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network
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title_short |
Prediction of Leishmania major Key Proteins Via Topological Analysis of Protein-Protein Interaction Network
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title_sort | prediction of leishmania major key proteins via topological analysis of protein-protein interaction network |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344062/ https://www.ncbi.nlm.nih.gov/pubmed/34466438 http://dx.doi.org/10.22086/gmj.v0i0.1129 |
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