PINALOG: a novel approach to align protein interaction networks—implications for complex detection and function prediction

Motivation: Analysis of protein–protein interaction networks (PPINs) at the system level has become increasingly important in understanding biological processes. Comparison of the interactomes of different species not only provides a better understanding of species evolution but also helps with detecting conserved functional components and in function prediction. Method and Results: Here we report a PPIN alignment method, called PINALOG, which combines information from protein sequence, function and network topology. Alignment of human and yeast PPINs reveals several conserved subnetworks between them that participate in similar biological processes, notably the proteasome and transcription related processes. PINALOG has been tested for its power in protein complex prediction as well as function prediction. Comparison with PSI-BLAST in predicting protein function in the twilight zone also shows that PINALOG is valuable in predicting protein function. Availability and implementation: The PINALOG web-server is freely available from http://www.sbg.bio.ic.ac.uk/~pinalog. The PINALOG program and associated data are available from the Download section of the web-server. Contact: m.sternberg@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

[1]  Natasa Przulj,et al.  Integrative network alignment reveals large regions of global network similarity in yeast and human , 2011, Bioinform..

[2]  Johannes Berg,et al.  Cross-species analysis of biological networks by Bayesian alignment. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Michael J E Sternberg,et al.  The identification of similarities between biological networks: application to the metabolome and interactome. , 2007, Journal of molecular biology.

[4]  Thomas Lengauer,et al.  A new measure for functional similarity of gene products based on Gene Ontology , 2006, BMC Bioinformatics.

[5]  Gregory D. Schuler,et al.  Database resources of the National Center for Biotechnology , 2003, Nucleic Acids Res..

[6]  Annabel E. Todd,et al.  Evolution of function in protein superfamilies, from a structural perspective. , 2001, Journal of molecular biology.

[7]  M. Sternberg,et al.  Protein structure prediction on the Web: a case study using the Phyre server , 2009, Nature Protocols.

[8]  Hans-Werner Mewes,et al.  CORUM: the comprehensive resource of mammalian protein complexes , 2007, Nucleic Acids Res..

[9]  Jacques van Helden,et al.  Evaluation of clustering algorithms for protein-protein interaction networks , 2006, BMC Bioinformatics.

[10]  Carole A. Goble,et al.  Investigating Semantic Similarity Measures Across the Gene Ontology: The Relationship Between Sequence and Annotation , 2003, Bioinform..

[11]  Wojciech Szpankowski,et al.  Pairwise Alignment of Protein Interaction Networks , 2006, J. Comput. Biol..

[12]  Richard M. Karp,et al.  Comparing Protein Interaction Networks via a Graph Match-and-Split Algorithm , 2007, J. Comput. Biol..

[13]  J. Skolnick,et al.  How well is enzyme function conserved as a function of pairwise sequence identity? , 2003, Journal of molecular biology.

[14]  O. Kuchaiev,et al.  Simulating trait evolution for cross-cultural comparison , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[15]  Bonnie Berger,et al.  Global alignment of multiple protein interaction networks with application to functional orthology detection , 2008, Proceedings of the National Academy of Sciences.

[16]  Shoshana J. Wodak,et al.  CYGD: the Comprehensive Yeast Genome Database , 2004, Nucleic Acids Res..

[17]  R. Karp,et al.  From the Cover : Conserved patterns of protein interaction in multiple species , 2005 .

[18]  Gary D. Bader,et al.  An automated method for finding molecular complexes in large protein interaction networks , 2003, BMC Bioinformatics.

[19]  David Botstein,et al.  GO: : TermFinder--open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes , 2004, Bioinform..

[20]  Charlotte M. Deane,et al.  Functionally guided alignment of protein interaction networks for module detection , 2009, Bioinform..

[21]  Charlotte M. Deane,et al.  The function of communities in protein interaction networks at multiple scales , 2009, BMC Systems Biology.

[22]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[23]  Sourav Bandyopadhyay,et al.  Systematic identification of functional orthologs based on protein network comparison. , 2006, Genome research.

[24]  Serafim Batzoglou,et al.  Automatic Parameter Learning for Multiple Local Network Alignment , 2009, J. Comput. Biol..

[25]  Christine A. Orengo,et al.  Inferring Function Using Patterns of Native Disorder in Proteins , 2007, PLoS Comput. Biol..

[26]  Illés J. Farkas,et al.  CFinder: locating cliques and overlapping modules in biological networks , 2006, Bioinform..

[27]  R. Karp,et al.  Conserved pathways within bacteria and yeast as revealed by global protein network alignment , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[28]  M. Vidal,et al.  Protein interaction mapping in C. elegans using proteins involved in vulval development. , 2000, Science.

[29]  Antal F. Novak,et al.  networks Græmlin : General and robust alignment of multiple large interaction data , 2006 .

[30]  Q. Mcnemar.  Note on the sampling error of the difference between correlated proportions or percentages , 1947, Psychometrika.

[31]  O. Kuchaiev,et al.  Topological network alignment uncovers biological function and phylogeny , 2008, Journal of The Royal Society Interface.

[32]  H. Kuhn.  The Hungarian method for the assignment problem , 1955 .

[33]  M. Gerstein,et al.  Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs. , 2004, Genome research.

[34]  Mona Singh,et al.  How and when should interactome-derived clusters be used to predict functional modules and protein function? , 2009, Bioinform..

[35]  Rafael C. Jimenez,et al.  The IntAct molecular interaction database in 2012 , 2011, Nucleic Acids Res..

[36]  S. Dongen.  Graph clustering by flow simulation , 2000 .