Evaluating the significance of protein functional similarity based on gene ontology

Gene ontology is among the most successful ontologies in the biomedical domain. It is used to describe, unambiguously, protein molecular functions, cellular localizations, and processes in which proteins participate. The hierarchical structure of gene ontology allows quantifying protein functional similarity by application of algorithms that calculate semantic similarities. The scores, however, are meaningless without a given context. Here, we propose how to evaluate the significance of protein function semantic similarity scores by comparing them to reference distributions calculated for randomly chosen proteins. In the study, thresholds for significant functional semantic similarity, in four representative annotation corpuses, were estimated. We also show that the score significance is influenced by the number and specificity of gene ontology terms that are annotated to compared proteins. While proteins with a greater number of terms tend to yield higher similarity scores, proteins with more specific terms produce lower scores. The estimated significance thresholds were validated using protein sequence-function and structure-function relationships. Taking into account the term number and term specificity improves the distinction between significant and insignificant semantic similarity comparisons.