Figure 1.

Schema of the method. The starting point is the SCOP2GO functional annotation of chains at the domain level (top left). The shapes represent the folds of the domains, while the colors represent assigned GO:MF functions. Structural alignments for the domains with the same fold and the same function are generated and PSSM profiles are derived from them. For benchmarking (left), an equivalent database is constructed merging all the domain sequences involved in these profiles. For assessing the performance of both resources for a given test sequence, new versions of both databases are built by excluding this sequence and all its homologs (transparent cylinders in the figure). Querying the test sequence against both resources produces list of hits which can be interpreted as predictions of folds and functions (colored shapes) associated to its domains. These predictions of both resources for the domains of the test sequence can be contrasted against its original SCOP2GO annotations (multi-colored triangle and circle). For predicting (right), a sequence of unknown domain characteristics in terms of fold and function is queried against the database of PSSMs. The hits can be interpreted as predictions of fold and function at the domain level. Additionally, the conservation pattern of the structural alignments associated to the matched PSSMs can give clues about functionally important residues.

Lopez and Pazos BMC Bioinformatics 2013 14(Suppl 3):S12   doi:10.1186/1471-2105-14-S3-S12