Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models.
BACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secre...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2011-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3184965?pdf=render |
| _version_ | 1818126789405310976 |
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| author | Daniel Restrepo-Montoya David Becerra Juan G Carvajal-Patiño Alvaro Mongui Luis F Niño Manuel E Patarroyo Manuel A Patarroyo |
| author_facet | Daniel Restrepo-Montoya David Becerra Juan G Carvajal-Patiño Alvaro Mongui Luis F Niño Manuel E Patarroyo Manuel A Patarroyo |
| author_sort | Daniel Restrepo-Montoya |
| collection | DOAJ |
| description | BACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. RESULTS: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. CONCLUSIONS: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria. |
| first_indexed | 2024-12-11T07:07:03Z |
| format | Article |
| id | doaj.art-891a81913d024c289efe9b78675e708d |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-11T07:07:03Z |
| publishDate | 2011-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-891a81913d024c289efe9b78675e708d2022-12-22T01:16:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-01610e2518910.1371/journal.pone.0025189Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models.Daniel Restrepo-MontoyaDavid BecerraJuan G Carvajal-PatiñoAlvaro MonguiLuis F NiñoManuel E PatarroyoManuel A PatarroyoBACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. RESULTS: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. CONCLUSIONS: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria.http://europepmc.org/articles/PMC3184965?pdf=render |
| spellingShingle | Daniel Restrepo-Montoya David Becerra Juan G Carvajal-Patiño Alvaro Mongui Luis F Niño Manuel E Patarroyo Manuel A Patarroyo Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. PLoS ONE |
| title | Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. |
| title_full | Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. |
| title_fullStr | Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. |
| title_full_unstemmed | Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. |
| title_short | Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. |
| title_sort | identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models |
| url | http://europepmc.org/articles/PMC3184965?pdf=render |
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