Protein design using continuous rotamers.
<h4>Unlabelled</h4>Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22279426/?tool=EBI |
| _version_ | 1818341732921638912 |
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| author | Pablo Gainza Kyle E Roberts Bruce R Donald |
| author_facet | Pablo Gainza Kyle E Roberts Bruce R Donald |
| author_sort | Pablo Gainza |
| collection | DOAJ |
| description | <h4>Unlabelled</h4>Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE.<h4>Availability</h4>Software is available under the Lesser GNU Public License v3. Contact the authors for source code. |
| first_indexed | 2024-12-13T16:03:29Z |
| format | Article |
| id | doaj.art-5feabd4b820f4aa0ba4cb7fbba107b47 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-13T16:03:29Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-5feabd4b820f4aa0ba4cb7fbba107b472022-12-21T23:39:06ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582012-01-0181e100233510.1371/journal.pcbi.1002335Protein design using continuous rotamers.Pablo GainzaKyle E RobertsBruce R Donald<h4>Unlabelled</h4>Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE.<h4>Availability</h4>Software is available under the Lesser GNU Public License v3. Contact the authors for source code.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22279426/?tool=EBI |
| spellingShingle | Pablo Gainza Kyle E Roberts Bruce R Donald Protein design using continuous rotamers. PLoS Computational Biology |
| title | Protein design using continuous rotamers. |
| title_full | Protein design using continuous rotamers. |
| title_fullStr | Protein design using continuous rotamers. |
| title_full_unstemmed | Protein design using continuous rotamers. |
| title_short | Protein design using continuous rotamers. |
| title_sort | protein design using continuous rotamers |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22279426/?tool=EBI |
| work_keys_str_mv | AT pablogainza proteindesignusingcontinuousrotamers AT kyleeroberts proteindesignusingcontinuousrotamers AT brucerdonald proteindesignusingcontinuousrotamers |