Research article summary (published 29 Sep 2009):

Computational protein design as a tool for fold recognition.

Full Abstract

Computationally designed protein sequences have been proposed as a basis to perform fold recognition and homology searching. To investigate this possibility, an automated procedure is used to completely redesign 24 SH3 proteins and 22 SH2 proteins. We use the experimental backbone coordinates as fixed templates in the folded state and a molecular mechanics model to compute the pairwise interaction energies between all sidechain types and conformations. Energy calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is then used to scan the sequence and conformational space for optimal solutions. We produced 200,000-450,000 sequences for each backbone template. The designed sequences ressemble moderately-distant, natural homologues of the initial templates, according to their identity scores and their similarity with respect to the Pfam sets of SH2 and SH3 domains. Standard homology detection tools document their native-like character: the Conserved Domain Database recognizes 61% (52%) of our low-energy sequences as SH3 (SH2) domains; the SUPERFAMILY, Hidden-Markov Model library recognizes 81% (84%). Conversely, position specific scoring matrices (PSSMs) derived from our designed sequences can be used to detect natural homologues in sequence databases. Within SwissProt, a set of natural SH3 PSSMs detects 772 SH3 domains, for example; our designed PSSMs detect 67% of these, plus one additional sequence and two false positives. If six amino acids involved in substrate binding (a selective pressure not accounted for in our design) are reset to their experimental types, then 77% of the experimental SH3 domains are detected. Results for the SH2 domains are similar. Several directions to improve the method further are discussed.

Author information

Author/s: am Busch, Marcel Schmidt (MS); Mignon, David (D); Simonson, Thomas (T);

Affiliation: Laboratoire de Biochimie (CNRS UMR7654), Department of Biology, Ecole Polytechnique, 91128 Palaiseau, France.

Journal and publication information

Publication Type: Journal Article

Journal: Proteins (Proteins), published in United States. (Language: eng)

Reference: 2009-Oct; vol 77 (issue 1) : pp 139-58

Dates: Created 2009/08/24; Completed 2009/10/29;

PMID: 19408297, status: MEDLINE (last retrieval date: 10/29/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms Computational Biology - methods Protein Folding

Protein Folding Proteins - chemistry Software

Associated Chemicals: Proteins (0)

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