Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design.
Predicting which mutations proteins tolerate while maintaining their structure and function has important applications for modeling fundamental properties of proteins and their evolution; it also drives progress in protein design. Here we develop a computational model to predict the tolerated sequen...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2012-01-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002639&type=printable |
| _version_ | 1826799382147629056 |
|---|---|
| author | Elisabeth Humphris-Narayanan Eyal Akiva Rocco Varela Shane Ó Conchúir Tanja Kortemme |
| author_facet | Elisabeth Humphris-Narayanan Eyal Akiva Rocco Varela Shane Ó Conchúir Tanja Kortemme |
| author_sort | Elisabeth Humphris-Narayanan |
| collection | DOAJ |
| description | Predicting which mutations proteins tolerate while maintaining their structure and function has important applications for modeling fundamental properties of proteins and their evolution; it also drives progress in protein design. Here we develop a computational model to predict the tolerated sequence space of HIV-1 protease reachable by single mutations. We assess the model by comparison to the observed variability in more than 50,000 HIV-1 protease sequences, one of the most comprehensive datasets on tolerated sequence space. We then extend the model to a second protein, reverse transcriptase. The model integrates multiple structural and functional constraints acting on a protein and uses ensembles of protein conformations. We find the model correctly captures a considerable fraction of protease and reverse-transcriptase mutational tolerance and shows comparable accuracy using either experimentally determined or computationally generated structural ensembles. Predictions of tolerated sequence space afforded by the model provide insights into stability-function tradeoffs in the emergence of resistance mutations and into strengths and limitations of the computational model. |
| first_indexed | 2024-12-17T15:26:06Z |
| format | Article |
| id | doaj.art-19eaeda4c66a420a902d5cc7848c00e9 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2025-03-17T00:34:11Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-19eaeda4c66a420a902d5cc7848c00e92025-02-21T05:32:12ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582012-01-0188e100263910.1371/journal.pcbi.1002639Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design.Elisabeth Humphris-NarayananEyal AkivaRocco VarelaShane Ó ConchúirTanja KortemmePredicting which mutations proteins tolerate while maintaining their structure and function has important applications for modeling fundamental properties of proteins and their evolution; it also drives progress in protein design. Here we develop a computational model to predict the tolerated sequence space of HIV-1 protease reachable by single mutations. We assess the model by comparison to the observed variability in more than 50,000 HIV-1 protease sequences, one of the most comprehensive datasets on tolerated sequence space. We then extend the model to a second protein, reverse transcriptase. The model integrates multiple structural and functional constraints acting on a protein and uses ensembles of protein conformations. We find the model correctly captures a considerable fraction of protease and reverse-transcriptase mutational tolerance and shows comparable accuracy using either experimentally determined or computationally generated structural ensembles. Predictions of tolerated sequence space afforded by the model provide insights into stability-function tradeoffs in the emergence of resistance mutations and into strengths and limitations of the computational model.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002639&type=printable |
| spellingShingle | Elisabeth Humphris-Narayanan Eyal Akiva Rocco Varela Shane Ó Conchúir Tanja Kortemme Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design. PLoS Computational Biology |
| title | Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design. |
| title_full | Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design. |
| title_fullStr | Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design. |
| title_full_unstemmed | Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design. |
| title_short | Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design. |
| title_sort | prediction of mutational tolerance in hiv 1 protease and reverse transcriptase using flexible backbone protein design |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002639&type=printable |
| work_keys_str_mv | AT elisabethhumphrisnarayanan predictionofmutationaltoleranceinhiv1proteaseandreversetranscriptaseusingflexiblebackboneproteindesign AT eyalakiva predictionofmutationaltoleranceinhiv1proteaseandreversetranscriptaseusingflexiblebackboneproteindesign AT roccovarela predictionofmutationaltoleranceinhiv1proteaseandreversetranscriptaseusingflexiblebackboneproteindesign AT shaneoconchuir predictionofmutationaltoleranceinhiv1proteaseandreversetranscriptaseusingflexiblebackboneproteindesign AT tanjakortemme predictionofmutationaltoleranceinhiv1proteaseandreversetranscriptaseusingflexiblebackboneproteindesign |