A Pareto-Optimal Refinement Method for Protein Design Scaffolds
Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme...
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Published in | PloS one Vol. 8; no. 4; p. e59004 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
02.04.2013
Public Library of Science (PLoS) |
Subjects | |
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Abstract | Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design. |
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AbstractList | Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design. Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design.Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or "scaffolds", are searched to find regions where functional sites (an enzyme active site, ligand binding pocket, protein-protein interaction region, etc.) can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design. |
Audience | Academic |
Author | Baker, David Nivón, Lucas Gregorio Moretti, Rocco |
AuthorAffiliation | 1 Department of Biochemistry, University of Washington, Seattle, Washington, United States of America 2 Howard Hughes Medical Institute (HHMI), University of Washington, Seattle, Washington, United States of America University of Michigan, United States of America |
AuthorAffiliation_xml | – name: 1 Department of Biochemistry, University of Washington, Seattle, Washington, United States of America – name: University of Michigan, United States of America – name: 2 Howard Hughes Medical Institute (HHMI), University of Washington, Seattle, Washington, United States of America |
Author_xml | – sequence: 1 givenname: Lucas Gregorio surname: Nivón fullname: Nivón, Lucas Gregorio – sequence: 2 givenname: Rocco surname: Moretti fullname: Moretti, Rocco – sequence: 3 givenname: David surname: Baker fullname: Baker, David |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23565140$$D View this record in MEDLINE/PubMed |
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Copyright | COPYRIGHT 2013 Public Library of Science 2013 Nivón et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2013 Nivón et al 2013 Nivón et al |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: LGN RM DB. Performed the experiments: LGN RM. Analyzed the data: LGN RM. Contributed reagents/materials/analysis tools: LGN RM. Wrote the paper: LGN RM DB. |
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SubjectTerms | Algorithms Amino acids Amino Acids - chemistry Backbone Binding Sites Biochemistry Biology Computational biology Computer applications Computer Simulation Design Energy Enzymes Ligands Methods Molecular biology Mutation Optimization Packaging Pareto optimum Protein Conformation Protein Interaction Domains and Motifs Proteins Proteins - chemistry Proteins - metabolism Protocol Scaffolds Structure |
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