Literature DB >> 11805293

Protein topology and stability define the space of allowed sequences.

Patrice Koehl1, Michael Levitt.   

Abstract

We describe a new approach to explore and quantify the sequence space associated with a given protein structure. A set of sequences are optimized for a given target structure, using all-atom models and a physical energy function. Specificity of the sequence for its target is ensured by using the random energy model, which keeps the amino acid composition of the sequence constant. The designed sequences provide a multiple sequence alignment that describes the sequence space compatible with the structure of interest; here the size of this space is estimated by using an information entropy measure. In parallel, multiple alignments of naturally occurring sequences can be derived by using either sequence or structure alignments. We compared these 3 independent multiple sequence alignments for 10 different proteins, ranging in size from 56 to 310 residues. We observed that the subset of the sequence space derived by using our design procedure is similar in size to the sequence spaces observed in nature. These results suggest that the volume of sequence space compatible with a given protein fold is defined by the length of the protein as well as by the topology (i.e., geometry of the polypeptide chain) and the stability (i.e., free energy of denaturation) of the fold.

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Year:  2002        PMID: 11805293      PMCID: PMC122181          DOI: 10.1073/pnas.032405199

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  34 in total

1.  A hierarchical approach to protein molecular evolution.

Authors:  L D Bogarad; M W Deem
Journal:  Proc Natl Acad Sci U S A       Date:  1999-03-16       Impact factor: 11.205

2.  Origin of the designability of protein structures.

Authors:  R Tatsumi; G Chikenji
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  1999-10

3.  Native protein sequences are close to optimal for their structures.

Authors:  B Kuhlman; D Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

4.  The SWISS-PROT protein sequence data bank.

Authors:  A Bairoch; B Boeckmann
Journal:  Nucleic Acids Res       Date:  1991-04-25       Impact factor: 16.971

5.  When blind is better: protein design by evolution.

Authors:  F H Arnold
Journal:  Nat Biotechnol       Date:  1998-07       Impact factor: 54.908

6.  De novo protein design: fully automated sequence selection.

Authors:  B I Dahiyat; S L Mayo
Journal:  Science       Date:  1997-10-03       Impact factor: 47.728

7.  De novo protein design. II. Plasticity in sequence space.

Authors:  P Koehl; M Levitt
Journal:  J Mol Biol       Date:  1999-11-12       Impact factor: 5.469

8.  Conserved residues and the mechanism of protein folding.

Authors:  E Shakhnovich; V Abkevich; O Ptitsyn
Journal:  Nature       Date:  1996-01-04       Impact factor: 49.962

9.  A new approach to the design of stable proteins.

Authors:  E I Shakhnovich; A M Gutin
Journal:  Protein Eng       Date:  1993-11

10.  The FSSP database of structurally aligned protein fold families.

Authors:  L Holm; C Sander
Journal:  Nucleic Acids Res       Date:  1994-09       Impact factor: 16.971

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  36 in total

1.  Sequence variations within protein families are linearly related to structural variations.

Authors:  Patrice Koehl; Michael Levitt
Journal:  J Mol Biol       Date:  2002-10-25       Impact factor: 5.469

2.  Thoroughly sampling sequence space: large-scale protein design of structural ensembles.

Authors:  Stefan M Larson; Jeremy L England; John R Desjarlais; Vijay S Pande
Journal:  Protein Sci       Date:  2002-12       Impact factor: 6.725

3.  Natural selection of more designable folds: a mechanism for thermophilic adaptation.

Authors:  Jeremy L England; Boris E Shakhnovich; Eugene I Shakhnovich
Journal:  Proc Natl Acad Sci U S A       Date:  2003-07-03       Impact factor: 11.205

4.  Folding free energy function selects native-like protein sequences in the core but not on the surface.

Authors:  Alfonso Jaramillo; Lorenz Wernisch; Stéphanie Héry; Shoshana J Wodak
Journal:  Proc Natl Acad Sci U S A       Date:  2002-10-04       Impact factor: 11.205

5.  Energy landscape and dynamics of the beta-hairpin G peptide and its isomers: Topology and sequences.

Authors:  Buyong Ma; Ruth Nussinov
Journal:  Protein Sci       Date:  2003-09       Impact factor: 6.725

6.  Stability and the evolvability of function in a model protein.

Authors:  Jesse D Bloom; Claus O Wilke; Frances H Arnold; Christoph Adami
Journal:  Biophys J       Date:  2004-05       Impact factor: 4.033

7.  Protein structure and evolutionary history determine sequence space topology.

Authors:  Boris E Shakhnovich; Eric Deeds; Charles Delisi; Eugene Shakhnovich
Journal:  Genome Res       Date:  2005-03       Impact factor: 9.043

8.  Protein sequence entropy is closely related to packing density and hydrophobicity.

Authors:  H Liao; W Yeh; D Chiang; R L Jernigan; B Lustig
Journal:  Protein Eng Des Sel       Date:  2005-03-23       Impact factor: 1.650

9.  Symmetry and frustration in protein energy landscapes: a near degeneracy resolves the Rop dimer-folding mystery.

Authors:  Yaakov Levy; Samuel S Cho; Tongye Shen; José N Onuchic; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2005-02-08       Impact factor: 11.205

10.  Comparing folding codes in simple heteropolymer models of protein evolutionary landscape: robustness of the superfunnel paradigm.

Authors:  Richard Wroe; Erich Bornberg-Bauer; Hue Sun Chan
Journal:  Biophys J       Date:  2004-10-22       Impact factor: 4.033

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