| Autor | Rezende, Antônio Mauro de | |
| Autor | Folador, Edson Luiz | |
| Autor | Resende, Daniela de Melo | |
| Autor | Ruiz, Jerônimo Conceição | |
| Data de acesso | 2014-06-26T12:02:30Z | |
| Data de disponibilização | 2014-06-26T12:02:30Z | |
| Data do publicação | 2012 | |
| Citação | REZENDE, Antonio Mauro e al. Computational prediction of protein-protein interactions in Leishmania predicted proteomes. Plos One. 2012, vol.7, pp. e51304 | pt_BR |
| ISSN | 1932-6203 | |
| URI | https://www.arca.fiocruz.br/handle/icict/7839 | |
| Idioma | eng | pt_BR |
| Editor | Public Library of Science | pt_BR |
| Direito Autoral | open access | pt_BR |
| Título | Computational prediction of protein-protein interactions in Leishmania predicted proteomes | pt_BR |
| Tipo do documento | Article | pt_BR |
| Resumo em Inglês | The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI) study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping) and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks received some degree of functional annotation which represents an important contribution since approximately 60% of Leishmania predicted proteomes has no predicted function. | pt_BR |
| Afiliação | Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Laboratório de Parasitologia Celular e Molecular. Belo Horizonte, MG, Brazil/Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Belo Horizonte, MG, Brazil | pt_BR |
| Afiliação | Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Laboratório de Parasitologia Celular e Molecular. Belo Horizonte, MG, Brazil/Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brazil | pt_BR |
| Afiliação | Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Laboratório de Parasitologia Celular e Molecular. Belo Horizonte, MG, Brazil/Universidade Federal de Ouro Preto. Laboratório de Pesquisas Clínicas. Ouro Preto, MG, Brazil | pt_BR |
| Afiliação | Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Laboratório de Parasitologia Celular e Molecular | pt_BR |
| Palavras-chave em inglês | Drug interactions | pt_BR |
| Palavras-chave em inglês | Leishmania major | pt_BR |
| Palavras-chave em inglês | Network analysis | pt_BR |
| Palavras-chave em inglês | Protein interaction networks | pt_BR |
| Palavras-chave em inglês | Proteomes | pt_BR |
| Palavras-chave em inglês | Sequence databases | pt_BR |
