Evaluation of physical and functional protein-protein interaction prediction methods for detecting biological pathways.
BACKGROUND
Cellular activities are governed by the physical and the functional interactions among several proteins involved in various biological pathways. With the availability of sequenced genomes and high-throughput experimental data one can identify genome-wide protein-protein interactions using various computational techniques. Comparative assessments of these techniques in predicting protein interactions have been frequently reported in the literature but not their ability to elucidate a particular biological pathway.


METHODS
Towards the goal of understanding the prediction capabilities of interactions among the specific biological pathway proteins, we report the analyses of 14 biological pathways of Escherichia coli catalogued in KEGG database using five protein-protein functional linkage prediction methods. These methods are phylogenetic profiling, gene neighborhood, co-presence of orthologous genes in the same gene clusters, a mirrortree variant, and expression similarity.


CONCLUSIONS
Our results reveal that the prediction of metabolic pathway protein interactions continues to be a challenging task for all methods which possibly reflect flexible/independent evolutionary histories of these proteins. These methods have predicted functional associations of proteins involved in amino acids, nucleotide, glycans and vitamins & co-factors pathways slightly better than the random performance on carbohydrate, lipid and energy metabolism. We also make similar observations for interactions involved among the environmental information processing proteins. On the contrary, genetic information processing or specialized processes such as motility related protein-protein linkages that occur in the subset of organisms are predicted with comparable accuracy. Metabolic pathways are best predicted by using neighborhood of orthologous genes whereas phyletic pattern is good enough to reconstruct central dogma pathway protein interactions. We have also shown that the effective use of a particular prediction method depends on the pathway under investigation. In case one is not focused on specific pathway, gene expression similarity method is the best option.
Computational and Functional Genomics Group, Centre for DNA Fingerprinting and Diagnostics, Hyderabad, India.
Vijaykumar Yogesh
VY
Muley
Akash
A
Ranjan
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000235:genetics / Q000378:metabolism*; D016680:Genome, Bacterial / Q000235:genetics; D053858:Metabolic Networks and Pathways; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D015203:Reproducibility of Results
D029968:Escherichia coli Proteins