Assignment of Folds for Proteins of Unknown Function in Three Microbial Genomes

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Abstract
Analysis of DNA sequences of several microbial genomes has revealed that a large fraction of predicted coding regions has no known protein function. Information about the three-dimensional folds of these proteins may provide insight into their possible functions. To predict the folds for protein sequences with little or no homology to proteins of known function, we used computational neural networks trained on the database of proteins with known three-dimensional structures. Global descriptions of protein sequences based on physical and structural properties of the constituent amino acids were used as inputs for neural networks. Of the 131, 498, and 868 protein sequences of unknown function from Mycoplasma genitalium, Haemophilus influenzae, and Methanococcus jannaschii (Fleischmann et al. 1995), we have made high-confidence fold assignments for 4, 10, and 19 sequences, respectively.