2on8: Difference between revisions
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | ||
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==See Also== | |||
*[[Protein G|Protein G]] | |||
== References == | == References == | ||
<references/> | <references/> | ||
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</StructureSection> | </StructureSection> | ||
[[Category: Streptococcus sp. g148]] | [[Category: Streptococcus sp. g148]] | ||
[[Category: Heinemann, U | [[Category: Heinemann, U]] | ||
[[Category: Max, K E.A | [[Category: Max, K E.A]] | ||
[[Category: Alpha helix]] | [[Category: Alpha helix]] | ||
[[Category: Beta sheet]] | [[Category: Beta sheet]] | ||
[[Category: Improved hydrophobic packing of core residue]] | [[Category: Improved hydrophobic packing of core residue]] | ||
[[Category: Protein binding]] | [[Category: Protein binding]] | ||
Revision as of 17:57, 19 January 2015
Gbeta1 stabilization by in vitro evolution and computational designGbeta1 stabilization by in vitro evolution and computational design
Structural highlights
Evolutionary Conservation Check, as determined by ConSurfDB. You may read the explanation of the method and the full data available from ConSurf. Publication Abstract from PubMedComputational design and in vitro evolution are major strategies for stabilizing proteins. For the four critical positions 16, 18, 25, and 29 of the B domain of the streptococcal protein G (Gbeta1), they identified the same optimal residues at positions 16 and 25, but not at 18 and 29. Here we analyzed the energetic contributions of the residues from these two approaches by single and double mutant analyses and determined crystal structures for a variant from the calculation (I16/L18/E25/K29) and from the selection (I16/I18/E25/F29). The structural analysis explains the observed differences in stabilization. Residues 16, 18, and 29 line an invagination, which results from a packing defect between the helix and the beta-sheet of Gbeta1. In all stabilized variants, residues with larger side-chains occur at these positions and packing is improved. In the selected variant, packing is better optimized than in the computed variant. Such differences in side-chain packing strongly affect stability but are difficult to evaluate by computation. Optimization of the gbeta1 domain by computational design and by in vitro evolution: structural and energetic basis of stabilization.,Wunderlich M, Max KE, Roske Y, Mueller U, Heinemann U, Schmid FX J Mol Biol. 2007 Oct 26;373(3):775-84. Epub 2007 Aug 19. PMID:17868696[1] From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine. See AlsoReferences
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