1psv
From Proteopedia
(New page: 200px<br /> <applet load="1psv" size="450" color="white" frame="true" align="right" spinBox="true" caption="1psv" /> '''COMPUTATIONALLY DESIGNED PEPTIDE WITH A BET...) |
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| - | [[Image:1psv.gif|left|200px]]<br /> | + | [[Image:1psv.gif|left|200px]]<br /><applet load="1psv" size="350" color="white" frame="true" align="right" spinBox="true" |
| - | <applet load="1psv" size=" | + | |
caption="1psv" /> | caption="1psv" /> | ||
'''COMPUTATIONALLY DESIGNED PEPTIDE WITH A BETA-BETA-ALPHA FOLD SELECTION, NMR, 32 STRUCTURES'''<br /> | '''COMPUTATIONALLY DESIGNED PEPTIDE WITH A BETA-BETA-ALPHA FOLD SELECTION, NMR, 32 STRUCTURES'''<br /> | ||
==Overview== | ==Overview== | ||
| - | Several groups have applied and experimentally tested systematic, quantitative methods to protein design with the goal of developing general | + | Several groups have applied and experimentally tested systematic, quantitative methods to protein design with the goal of developing general design algorithms. We have sought to expand the range of computational protein design by developing quantitative design methods for residues of all parts of a protein: the buried core, the solvent exposed surface, and the boundary between core and surface. Our goal is an objective, quantitative design algorithm that is based on the physical properties that determine protein structure and stability and which is not limited to specific folds or motifs. We chose the betabetaalpha motif typified by the zinc finger DNA binding module to test our design methodology. Using previously published sequence scoring functions developed with a combined experimental and computational approach and the Dead-End Elimination theorem to search for the optimal sequence, we designed 20 out of 28 positions in the test motif. The resulting sequence has less than 40% homology to any known sequence and does not contain any metal binding sites or cysteine residues. The resulting peptide, pda8d, is highly soluble and monomeric and circular dichroism measurements showed it to be folded with a weakly cooperative thermal unfolding transition. The NMR solution structure of pda8d was solved and shows that it is well-defined with a backbone ensemble rms deviation of 0. 55 A. Pda8d folds into the desired betabetaalpha motif with well-defined elements of secondary structure and tertiary organization. Superposition of the pda8d backbone to the design target is excellent, with an atomic rms deviation of 1.04 A. |
==About this Structure== | ==About this Structure== | ||
| - | 1PSV is a [http://en.wikipedia.org/wiki/Protein_complex Protein complex] structure of sequences from [http://en.wikipedia.org/wiki/ ]. The following page contains interesting information on the relation of 1PSV with [[http://pdb.rcsb.org/pdb/static.do?p=education_discussion/molecule_of_the_month/pdb70_1.html Designer Proteins]]. Full crystallographic information is available from [http:// | + | 1PSV is a [http://en.wikipedia.org/wiki/Protein_complex Protein complex] structure of sequences from [http://en.wikipedia.org/wiki/ ]. The following page contains interesting information on the relation of 1PSV with [[http://pdb.rcsb.org/pdb/static.do?p=education_discussion/molecule_of_the_month/pdb70_1.html Designer Proteins]]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=1PSV OCA]. |
==Reference== | ==Reference== | ||
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[[Category: Designer Proteins]] | [[Category: Designer Proteins]] | ||
[[Category: Protein complex]] | [[Category: Protein complex]] | ||
| - | [[Category: Dahiyat, B | + | [[Category: Dahiyat, B I.]] |
| - | [[Category: Mayo, S | + | [[Category: Mayo, S L.]] |
| - | [[Category: Sarisky, C | + | [[Category: Sarisky, C A.]] |
[[Category: beta-beta-alpha fold]] | [[Category: beta-beta-alpha fold]] | ||
[[Category: dead end elimination]] | [[Category: dead end elimination]] | ||
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[[Category: sequence optimization]] | [[Category: sequence optimization]] | ||
| - | ''Page seeded by [http:// | + | ''Page seeded by [http://oca.weizmann.ac.il/oca OCA ] on Thu Feb 21 14:32:14 2008'' |
Revision as of 12:32, 21 February 2008
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COMPUTATIONALLY DESIGNED PEPTIDE WITH A BETA-BETA-ALPHA FOLD SELECTION, NMR, 32 STRUCTURES
Overview
Several groups have applied and experimentally tested systematic, quantitative methods to protein design with the goal of developing general design algorithms. We have sought to expand the range of computational protein design by developing quantitative design methods for residues of all parts of a protein: the buried core, the solvent exposed surface, and the boundary between core and surface. Our goal is an objective, quantitative design algorithm that is based on the physical properties that determine protein structure and stability and which is not limited to specific folds or motifs. We chose the betabetaalpha motif typified by the zinc finger DNA binding module to test our design methodology. Using previously published sequence scoring functions developed with a combined experimental and computational approach and the Dead-End Elimination theorem to search for the optimal sequence, we designed 20 out of 28 positions in the test motif. The resulting sequence has less than 40% homology to any known sequence and does not contain any metal binding sites or cysteine residues. The resulting peptide, pda8d, is highly soluble and monomeric and circular dichroism measurements showed it to be folded with a weakly cooperative thermal unfolding transition. The NMR solution structure of pda8d was solved and shows that it is well-defined with a backbone ensemble rms deviation of 0. 55 A. Pda8d folds into the desired betabetaalpha motif with well-defined elements of secondary structure and tertiary organization. Superposition of the pda8d backbone to the design target is excellent, with an atomic rms deviation of 1.04 A.
About this Structure
1PSV is a Protein complex structure of sequences from [1]. The following page contains interesting information on the relation of 1PSV with [Designer Proteins]. Full crystallographic information is available from OCA.
Reference
De novo protein design: towards fully automated sequence selection., Dahiyat BI, Sarisky CA, Mayo SL, J Mol Biol. 1997 Nov 7;273(4):789-96. PMID:9367772
Page seeded by OCA on Thu Feb 21 14:32:14 2008
