Probing the “Dark Matter” of Protein Fold Space
We used a protein structure prediction method to generate a variety of folds as α-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unb...
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| Published in | Structure (London) Vol. 17; no. 9; pp. 1244 - 1252 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Inc
09.09.2009
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| Subjects | |
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| Abstract | We used a protein structure prediction method to generate a variety of folds as α-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter. |
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| AbstractList | We used a protein structure prediction method to generate a variety of folds as alpha-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter.We used a protein structure prediction method to generate a variety of folds as alpha-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter. We used a protein structure prediction method to generate a variety of folds as α-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter. We used a protein structure prediction method to generate a variety of folds as alpha-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter. We used a protein structure prediction method to generate a variety of folds as a-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter. |
| Author | MacDonald, James T. Jonassen, Inge Taylor, William R. Hollup, Siv Midtun Chelliah, Vijayalakshmi |
| Author_xml | – sequence: 1 givenname: William R. surname: Taylor fullname: Taylor, William R. email: wtaylor@nimr.mrc.ac.uk organization: Division of Mathematical Biology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK – sequence: 2 givenname: Vijayalakshmi surname: Chelliah fullname: Chelliah, Vijayalakshmi organization: Division of Mathematical Biology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK – sequence: 3 givenname: Siv Midtun surname: Hollup fullname: Hollup, Siv Midtun organization: Department of Informatics, University of Bergen, Norway – sequence: 4 givenname: James T. surname: MacDonald fullname: MacDonald, James T. organization: Division of Mathematical Biology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK – sequence: 5 givenname: Inge surname: Jonassen fullname: Jonassen, Inge organization: Computational Biology Unit, University of Bergen, Norway |
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| Snippet | We used a protein structure prediction method to generate a variety of folds as α-carbon models with realistic secondary structures and good hydrophobic... We used a protein structure prediction method to generate a variety of folds as alpha-carbon models with realistic secondary structures and good hydrophobic... We used a protein structure prediction method to generate a variety of folds as a-carbon models with realistic secondary structures and good hydrophobic... |
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| SubjectTerms | Models, Molecular Molecular Probes Protein Folding PROTEINS Proteins - chemistry |
| Title | Probing the “Dark Matter” of Protein Fold Space |
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