Predicting function from sequence using computational tools is a highly complicated procedure that is generally done for each gene individually. This review focuses on the added value that is provided by completely sequenced genomes in function prediction. Various levels of sequence annotation and function prediction are discussed, ranging from genomic sequence to that of complex cellular processes. Protein function is currently best described in the context of molecular interactions. In the near future it will be possible to predict protein function in the context of higher order processes such as the regulation of gene expression, metabolic pathways and signalling cascades. The analysis of such higher levels of function description uses, besides the information from completely sequenced genomes, also the additional information from proteomics and expression data. The final goal will be to elucidate the mapping between genotype and phenotype.

Homology search techniques based on the iterative PSI-BLAST method in combination with various filters for low sequence complexity are applied to assign folds to all Mycoplasma genitalium proteins. The resulting procedure (implemented as a web server) is able to predict at least one domain in 37% of these proteins automatically, with an estimated accuracy higher than 98%. Taking structural features such as coiled coil or transmembrane regions aside, folds can be assigned to more than half of the globular proteins in a bacterium just by iterative sequence comparison.

We have analyzed the base-pairing probability distributions of 16 S and 16 S-like, and 23 S and 23 S-like ribosomal RNAs of Archaea, Bacteria, chloroplasts, mitochondria and Eukarya, as predicted by the partition function approach for RNA folding introduced by McCaskill. A quantitative analysis of the reliability of RNA folding is done by comparing the base-pairing probability distributions with the structures predicted by comparative sequence analysis (comparative structures). We distinguish two factors that show a relationship to the reliability of RNA minimum free energy structure. The first factor is the dominance of one particular base-pair or the absence of base-pairing for a given base within the base-pairing probability distribution (BPPD). We characterize the BPPD per base, including the probability of not base-pairing, by its Shannon entropy (S). The S value indicates the uncertainty about the base-pairing of a base: low S values result from BPPDs that are strongly dominated by a single base-pair or by the absence of base-pairing. We show that bases with low S values have a relatively high probability that their minimum free energy (MFE) structure corresponds to the comparative structure. The BPPDs of prokaryotes that live at high temperatures (thermophilic Archaea and Bacteria) have, calculated at 37 degrees C, lower S values than the BPPDs of prokaryotes that live at lower temperatures (mesophilic and psychrophilic Archaea and Bacteria). This reflects an adaptation of the ribosomal RNAs to the environmental temperature. A second factor that is important to consider with regard to the reliability of MFE structure folding is a variable degree of applicability of the thermodynamic model of RNA folding for different groups of RNAs. Here we show that among the bases that show low S values, the Archaea and Bacteria have similar, high probabilities (0.96 and 0.94 in 16 S and 0.93 and 0.91 in 23 S, respectively) that the MFE structure corresponds to the comparative structure. These probabilities are lower in the chloroplasts (16 S 0.91, 23 S 0.79), mitochondria (16 S-like 0.89, 23 S-like 0.69) and Eukarya (18 S 0.81, 28 S 0.86).