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 inPloS one Vol. 8; no. 4; p. e59004
Main Authors Nivón, Lucas Gregorio, Moretti, Rocco, Baker, David
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 02.04.2013
Public Library of Science (PLoS)
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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.
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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ContentType Journal Article
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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– notice: 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.
– notice: 2013 Nivón et al 2013 Nivón et al
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DocumentTitleAlternate Pareto-Optimal Protein Design Refinement Method
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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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Snippet 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...
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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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Title A Pareto-Optimal Refinement Method for Protein Design Scaffolds
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