EFICAz: Enzyme Function Inference by a Combined Approach (Beta-release)

EFICAz (Enzyme Function Inference by a Combined Approach) is an automatic engine for large-scale enzyme function inference that combines predictions from four different methods developed and optimized to achieve high prediction accuracy: (i) recognition of functionally discriminating residues (FDRs) in enzyme families obtained by a Conservation-controlled HMM Iterative procedure for Enzyme Family classification (CHIEFc), (ii) pairwise sequence comparison using a family specific Sequence Identity Threshold, (iii) recognition of FDRs in Multiple Pfam enzyme families, and (iv) recognition of multiple Prosite patterns of high specificity. For FDR (i.e. conserved positions in an enzyme family that discriminate between true and false members of the family) identification, we have developed an Evolutionary Footprinting method that uses evolutionary information from homofunctional and heterofunctional multiple sequence alignments associated with an enzyme family. The FDRs show a significant correlation with annotated active site residues. EFICAz algorithm is described in Tian W, Arakaki AK, Skolnick J. (2004) Nucleic Acids Res. 32:6226-39. The reannotation of 245 genomes using EFICAz is described in Arakaki AK, Tian W, Skolnick J. (2006) BMC Genomics 7:315.