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The design of a hyperstable mutant of the Abp1p SH3 domain by sequence alignment analysis.

ABSTRACT: We have characterized the thermodynamic stability of the SH3 domain from the Saccharomyces cerevisiae Abp1p protein and found it to be relatively low compared to most other SH3 domains, with a Tm of 60 degrees C and a deltaGu of 3.08 kcal/mol. Analysis of a large alignment of SH3 domains led to the identification of atypical residues at eight positions in the wild-type Abp1p SH3 domain sequence that were subsequently replaced by the residue seen most frequently at that position in the alignment. Three of the eight mutants constructed in this way displayed increases in Tm ranging from 8 to 15 degrees C with concomitant increases in deltaGu of up to 1.4 kcal/mol. The effects of these substitutions on folding thermodynamics and kinetics were entirely additive, and a mutant containing all three was dramatically stabilized with a Tm greater than 90 degrees C and a deltaGu more than double that of the wild-type domain. The folding rate of this hyperstable mutant was 10-fold faster than wild-type, while its unfolding rate was fivefold slower. All of the stabilized mutants were still able to bind a target peptide with wild-type affinity. We have analyzed the stabilizing amino acid substitutions isolated in this study and several other similar sequence alignment based studies. In approximately 25% of cases, increased stability can be explained by enhanced propensity of the substituted residue for the local backbone conformation at the mutagenized site.

SUBMITTER: Rath A

PROVIDER: S-EPMC2144507 | biostudies-other | 2000 Dec

REPOSITORIES: biostudies-other

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The design of a hyperstable mutant of the Abp1p SH3 domain by sequence alignment analysis.

Rath A A Davidson A R AR

Protein science : a publication of the Protein Society 20001201 12

We have characterized the thermodynamic stability of the SH3 domain from the Saccharomyces cerevisiae Abp1p protein and found it to be relatively low compared to most other SH3 domains, with a Tm of 60 degrees C and a deltaGu of 3.08 kcal/mol. Analysis of a large alignment of SH3 domains led to the identification of atypical residues at eight positions in the wild-type Abp1p SH3 domain sequence that were subsequently replaced by the residue seen most frequently at that position in the alignment. ...[more]

PMID: 11206067

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Project description:MotivationState-of-the-art experimental data for determining binding specificities of peptide recognition modules (PRMs) is obtained by high-throughput approaches like peptide arrays. Most prediction tools applicable to this kind of data are based on an initial multiple alignment of the peptide ligands. Building an initial alignment can be error-prone, especially in the case of the proline-rich peptides bound by the SH3 domains.ResultsHere, we present a machine-learning approach based on an efficient graph-kernel technique to predict the specificity of a large set of 70 human SH3 domains, which are an important class of PRMs. The graph-kernel strategy allows us to (i) integrate several types of physico-chemical information for each amino acid, (ii) consider high-order correlations between these features and (iii) eliminate the need for an initial peptide alignment. We build specialized models for each human SH3 domain and achieve competitive predictive performance of 0.73 area under precision-recall curve, compared with 0.27 area under precision-recall curve for state-of-the-art methods based on position weight matrices. We show that better models can be obtained when we use information on the noninteracting peptides (negative examples), which is currently not used by the state-of-the art approaches based on position weight matrices. To this end, we analyze two strategies to identify subsets of high confidence negative data. The techniques introduced here are more general and hence can also be used for any other protein domains, which interact with short peptides (i.e. other PRMs).AvailabilityThe program with the predictive models can be found at http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/SH3PepInt.tar.gz. We also provide a genome-wide prediction for all 70 human SH3 domains, which can be found under http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/Genome-Wide-Predictions.tar.gz.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

The design of a hyperstable mutant of the Abp1p SH3 domain by sequence alignment analysis.

Publications

The design of a hyperstable mutant of the Abp1p SH3 domain by sequence alignment analysis.

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