Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily
Abstract In this work, we applied the sequence-based statistical coupling analysis approach to characterize conserved amino acid networks important for biochemical function in the pancreatic-type ribonuclease (ptRNase) superfamily. This superfamily-wide analysis indicates a decomposition of the RNas...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2017-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-017-03298-4 |
| _version_ | 1828903484496281600 |
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| author | Chitra Narayanan Donald Gagné Kimberly A. Reynolds Nicolas Doucet |
| author_facet | Chitra Narayanan Donald Gagné Kimberly A. Reynolds Nicolas Doucet |
| author_sort | Chitra Narayanan |
| collection | DOAJ |
| description | Abstract In this work, we applied the sequence-based statistical coupling analysis approach to characterize conserved amino acid networks important for biochemical function in the pancreatic-type ribonuclease (ptRNase) superfamily. This superfamily-wide analysis indicates a decomposition of the RNase tertiary structure into spatially distributed yet physically connected networks of co-evolving amino acids, termed sectors. Comparison of this statistics-based description with new NMR experiments data shows that discrete amino acid networks, termed sectors, control the tuning of distinct functional properties in different enzyme homologs. Further, experimental characterization of evolutionarily distant sequences reveals that sequence variation at sector positions can distinguish homologs with a conserved dynamic pattern and optimal catalytic activity from those with altered dynamics and diminished catalytic activities. Taken together, these results provide important insights into the mechanistic design of the ptRNase superfamily, and presents a structural basis for evolutionary tuning of function in functionally diverse enzyme homologs. |
| first_indexed | 2024-12-13T16:35:19Z |
| format | Article |
| id | doaj.art-e1f69c4e9b494b9dbefb82876d0eca19 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-13T16:35:19Z |
| publishDate | 2017-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-e1f69c4e9b494b9dbefb82876d0eca192022-12-21T23:38:25ZengNature PortfolioScientific Reports2045-23222017-06-01711910.1038/s41598-017-03298-4Conserved amino acid networks modulate discrete functional properties in an enzyme superfamilyChitra Narayanan0Donald Gagné1Kimberly A. Reynolds2Nicolas Doucet3INRS – Institut Armand Frappier, Université du Québec, 531 Boulevard des PrairiesINRS – Institut Armand Frappier, Université du Québec, 531 Boulevard des PrairiesGreen Center for Systems Biology, UT Southwestern Medical CenterINRS – Institut Armand Frappier, Université du Québec, 531 Boulevard des PrairiesAbstract In this work, we applied the sequence-based statistical coupling analysis approach to characterize conserved amino acid networks important for biochemical function in the pancreatic-type ribonuclease (ptRNase) superfamily. This superfamily-wide analysis indicates a decomposition of the RNase tertiary structure into spatially distributed yet physically connected networks of co-evolving amino acids, termed sectors. Comparison of this statistics-based description with new NMR experiments data shows that discrete amino acid networks, termed sectors, control the tuning of distinct functional properties in different enzyme homologs. Further, experimental characterization of evolutionarily distant sequences reveals that sequence variation at sector positions can distinguish homologs with a conserved dynamic pattern and optimal catalytic activity from those with altered dynamics and diminished catalytic activities. Taken together, these results provide important insights into the mechanistic design of the ptRNase superfamily, and presents a structural basis for evolutionary tuning of function in functionally diverse enzyme homologs.https://doi.org/10.1038/s41598-017-03298-4 |
| spellingShingle | Chitra Narayanan Donald Gagné Kimberly A. Reynolds Nicolas Doucet Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily Scientific Reports |
| title | Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily |
| title_full | Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily |
| title_fullStr | Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily |
| title_full_unstemmed | Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily |
| title_short | Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily |
| title_sort | conserved amino acid networks modulate discrete functional properties in an enzyme superfamily |
| url | https://doi.org/10.1038/s41598-017-03298-4 |
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