From Protein Structure to Function with Bioinformatics.pdf

258 R.A. Laskowski10.2.5 Protein InteractionsThe final set of features extracted by ProKnow relate to protein-protein interactionstaken from the Database of Interacting Proteins (DIP) (Xenarios et al. 2002) andfunctional annotations from the Prolinks Database (Bowers et al. 2004). Anysequence matched by the PSI-BLAST search can return a functional linkage ifpresent in either DIP or Prolinks.10.2.6 Combining the PredictionsOnce all processes have completed, the functions (i.e. GO terms) associated with anyextracted features that reoccur are combined using Bayes’ Theorem weighting. Thisprovides an estimate of the significance of any predicted GO term. Only terms relatingto molecular function and biological process are considered – i.e. terms relating to cellularcomponent are ignored. The significance of any predicted GO term is reflectedby three numbers. The first is the Bayesian weight which represents the probability,0.0–1.0, of the predicted GO term being correct. The second is the evidence rank andrelates to how reliable a particular GO assignment is deemed to be in the first place.GO assignments come from various sources: inferred by the curator, inferred fromdirect assay, inferred from sequence or structural similarity, and so on. These have arange of reliabilities, the most reliable being any that have direct experimental evidenceto support them. The source of the annotation is recorded by the evidence codein the GO data. In ProKnow, each type of evidence code is assigned a rank to quantifyits reliability, and the ranks from several predictions are averaged to give the evidencerank. The third measure of significance is the clue count which is the number ofweights used to calculate the Bayesian weight and is related to how many of theProKnow sequence and structure methods contributed to a given GO prediction.10.2.7 Prediction SuccessFigure 10.3 shows some of the output on our example structure, 2fck. The Dali foldmatches were almost exclusively to acetyltransferases. The UniProt BLASTsearches found a number of strong sequence matches to acetyltransferases. TheRIGOR search threw in a few red herrings with matches to fibroblast growth factors,a lipid-binding protein called lipovitellin, and an integrase. More red herrings werecontributed by the PROSITE hits, all to short motifs, two being phosphorylationsites and one a myristoylation site (all are annotated on the PROSITE web site withthe comment: “This entry can, in some cases, be ignored by a program (because itis too unspecific)”). The DIP search returned nothing. Nevertheless, the overwhelminglystrongest prediction was the one that appears to be the correct one; namely, thatthe protein is an acetyltransferase. So in this case the overall prediction looks right.