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Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites
Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a hom...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335499/ https://www.ncbi.nlm.nih.gov/pubmed/25671604 http://dx.doi.org/10.1371/journal.pgen.1004918 |
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author | Melamed, Daniel Young, David L. Miller, Christina R. Fields, Stanley |
author_facet | Melamed, Daniel Young, David L. Miller, Christina R. Fields, Stanley |
author_sort | Melamed, Daniel |
collection | PubMed |
description | Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a homologue is substituted into a protein and tested for its ability to support function. Therefore, substitutions that inhibit function can identify interaction sites that changed over evolution. However, most of the sequence differences within a protein family remain unexplored because of the small-scale nature of these complementation approaches. Here we use existing high throughput mutational data on the in vivo function of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein, Pab1, to analyze its sites of interaction. Of 197 single amino acid differences in 52 Pab1 homologues, 17 reduce the function of Pab1 when substituted into the yeast protein. The majority of these deleterious mutations interfere with the binding of the RRM2 domain to eIF4G1 and eIF4G2, isoforms of a translation initiation factor. A large-scale mutational analysis of the RRM2 domain in a two-hybrid assay for eIF4G1 binding supports these findings and identifies peripheral residues that make a smaller contribution to eIF4G1 binding. Three single amino acid substitutions in yeast Pab1 corresponding to residues from the human orthologue are deleterious and eliminate binding to the yeast eIF4G isoforms. We create a triple mutant that carries these substitutions and other humanizing substitutions that collectively support a switch in binding specificity of RRM2 from the yeast eIF4G1 to its human orthologue. Finally, we map other deleterious substitutions in Pab1 to inter-domain (RRM2–RRM1) or protein-RNA (RRM2–poly(A)) interaction sites. Thus, the combined approach of large-scale mutational data and evolutionary conservation can be used to characterize interaction sites at single amino acid resolution. |
format | Online Article Text |
id | pubmed-4335499 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43354992015-03-04 Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites Melamed, Daniel Young, David L. Miller, Christina R. Fields, Stanley PLoS Genet Research Article Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a homologue is substituted into a protein and tested for its ability to support function. Therefore, substitutions that inhibit function can identify interaction sites that changed over evolution. However, most of the sequence differences within a protein family remain unexplored because of the small-scale nature of these complementation approaches. Here we use existing high throughput mutational data on the in vivo function of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein, Pab1, to analyze its sites of interaction. Of 197 single amino acid differences in 52 Pab1 homologues, 17 reduce the function of Pab1 when substituted into the yeast protein. The majority of these deleterious mutations interfere with the binding of the RRM2 domain to eIF4G1 and eIF4G2, isoforms of a translation initiation factor. A large-scale mutational analysis of the RRM2 domain in a two-hybrid assay for eIF4G1 binding supports these findings and identifies peripheral residues that make a smaller contribution to eIF4G1 binding. Three single amino acid substitutions in yeast Pab1 corresponding to residues from the human orthologue are deleterious and eliminate binding to the yeast eIF4G isoforms. We create a triple mutant that carries these substitutions and other humanizing substitutions that collectively support a switch in binding specificity of RRM2 from the yeast eIF4G1 to its human orthologue. Finally, we map other deleterious substitutions in Pab1 to inter-domain (RRM2–RRM1) or protein-RNA (RRM2–poly(A)) interaction sites. Thus, the combined approach of large-scale mutational data and evolutionary conservation can be used to characterize interaction sites at single amino acid resolution. Public Library of Science 2015-02-11 /pmc/articles/PMC4335499/ /pubmed/25671604 http://dx.doi.org/10.1371/journal.pgen.1004918 Text en © 2015 Melamed et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Melamed, Daniel Young, David L. Miller, Christina R. Fields, Stanley Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites |
title | Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites |
title_full | Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites |
title_fullStr | Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites |
title_full_unstemmed | Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites |
title_short | Combining Natural Sequence Variation with High Throughput Mutational Data to Reveal Protein Interaction Sites |
title_sort | combining natural sequence variation with high throughput mutational data to reveal protein interaction sites |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335499/ https://www.ncbi.nlm.nih.gov/pubmed/25671604 http://dx.doi.org/10.1371/journal.pgen.1004918 |
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