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Prediction of Residues with Rare Function Not Represented in the Training Sets

Title:
Prediction of Residues with Rare Function Not Represented in the Training Sets

Description:
MFS was trained on a set of residues experimentally characterized to participate in canonical catalytic functionalities and protein-ligand interfaces. Protein binding to biomineral surfaces is a rare function and poorly understood process, for which the only diffraction structure available is osteocalcin binding metal ions (depicted as green spheres with ionic bonds to the γ-carboxy glutamic acid (gla) residues in transparent green tube) (PDB identifier: 1q8h).

The three gla residues of osteocalcin (represented as spheres, similar to the target residues in Figure 3 above) previously shown to bind the hydroxyapatite surface of bone are clearly selected by MFS within the top six of 49 residues, with or without knowledge of structural and post-translational modification to these residues. These residues are selected within the top eight by ConSurf, with much lower discrimination from scores for the other residues in osteocalcin. None of these residues are selected within the top-10 by ET. This example demonstrates the applicability of MFS to make highly accurate and specific predictions for proteins of vastly diverse functions.

Credit:
Wang K, Horst J, Cheng G, Nickle D, Samudrala R. Protein meta-functional signatures from combining sequence, structure, evolution and amino acid property information. PLoS Computational Biology 4: e1000181, 2008.

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This page last updated: February 26, 2014