Protein Interactions

High throughput methods for detecting protein interactions require assessment of their accuracy. We present two forms of computational assessment. The first method is the expression profile reliability (EPR) index. The EPR index estimates the biologically relevant fraction of protein interactions detected in a high throughput screen. It does so by comparing the RNA expression profiles for the proteins whose interactions are found in the screen with expression profiles for known interacting and non-interacting pairs of proteins. The second form of assessment is the paralogous verification method (PVM). This method judges an interaction likely if the putatively interacting pair has paralogs that also interact. In contrast to the EPR index, which evaluates datasets of interactions, PVM scores individual interactions. On a test set, PVM identifies correctly 40% of true interactions with a false positive rate of ∼1%. EPR and PVM were applied to the Database of Interacting Proteins (DIP), a large and diverse collection of protein-protein interactions that contains over 8000 Saccharomyces cerevisiae pairwise protein interactions. Using these two methods, we estimate that ∼50% of them are reliable, and with the aid of PVM we identify confidently 3003 of them. Web servers for both the PVM and EPR methods are available on the DIP website (dip.doe-mbi.ucla.edu/Services.cgi).

[1]  William H. Press,et al.  Numerical Recipes: FORTRAN , 1988 .

[2]  Ed Anderson,et al.  LAPACK Users' Guide , 1995 .

[3]  E V Koonin,et al.  Sequence similarity analysis of Escherichia coli proteins: functional and evolutionary implications. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Thomas L. Madden,et al.  Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.

[5]  P. Legrain,et al.  Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens , 1997, Nature Genetics.

[6]  Patrick O. Brown,et al.  Observing the living genome , 1999, Nature Genetics.

[7]  M. Vidal,et al.  Yeast forward and reverse 'n'-hybrid systems. , 1999, Nucleic acids research.

[8]  Jack Dongarra,et al.  LAPACK Users' Guide, 3rd ed. , 1999 .

[9]  Ian Dix,et al.  Yeast Yeast 2000; 17: 95±110. Research Article , 2000 .

[10]  James R. Knight,et al.  A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae , 2000, Nature.

[11]  E. Winzeler,et al.  Genomics, gene expression and DNA arrays , 2000, Nature.

[12]  Marc Vidal,et al.  Yeast Two-hybrid Systems and Protein Interaction Mapping Projects for Yeast and Worm , 2022 .

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

[14]  P. Legrain,et al.  Genome‐wide protein interaction maps using two‐hybrid systems , 2000, FEBS letters.

[15]  B. Schwikowski,et al.  A network of protein–protein interactions in yeast , 2000, Nature Biotechnology.

[16]  Michael E. Cusick,et al.  The Yeast Proteome Database (YPD) and Caenorhabditis elegans Proteome Database (WormPD): comprehensive resources for the organization and comparison of model organism protein information , 2000, Nucleic Acids Res..

[17]  Ioannis Xenarios,et al.  DIP: the Database of Interacting Proteins , 2000, Nucleic Acids Res..

[18]  T. Ito,et al.  Toward a protein-protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[19]  D. Botstein,et al.  Genomic expression programs in the response of yeast cells to environmental changes. , 2000, Molecular biology of the cell.

[20]  E. Wolf,et al.  A computationally directed screen identifying interacting coiled coils from Saccharomyces cerevisiae. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[21]  W. Michael.  Nucleocytoplasmic shuttling signals: two for the price of one. , 2000, Trends in cell biology.

[22]  Ian M. Donaldson,et al.  BIND: the Biomolecular Interaction Network Database , 2001, Nucleic Acids Res..

[23]  G. Church,et al.  Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae , 2001, Nature Genetics.

[24]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[25]  P. Uetz,et al.  Towards an understanding of complex protein networks. , 2001, Trends in cell biology.

[26]  J. E. Kranz,et al.  YPD, PombePD and WormPD: model organism volumes of the BioKnowledge library, an integrated resource for protein information. , 2001, Nucleic acids research.

[27]  Marek S. Skrzypek,et al.  YPDTM, PombePDTM and WormPDTM: model organism volumes of the BioKnowledgeTM Library, an integrated resource for protein information , 2001, Nucleic Acids Res..

[28]  S. Fields,et al.  Networking proteins in yeast , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[29]  J M Gauthier,et al.  Protein--protein interaction maps: a lead towards cellular functions. , 2001, Trends in genetics : TIG.

[30]  M. Vidal,et al.  High-throughput yeast two-hybrid assays for large-scale protein interaction mapping. , 2001, Methods.

[31]  R. Ozawa,et al.  A comprehensive two-hybrid analysis to explore the yeast protein interactome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[32]  H. Herzel,et al.  Is there a bias in proteome research? , 2001, Genome research.

[33]  Michael Y. Galperin,et al.  The COG database: new developments in phylogenetic classification of proteins from complete genomes , 2001, Nucleic Acids Res..

[34]  D. Eisenberg,et al.  Protein interaction databases. , 2001, Current opinion in biotechnology.

[35]  M. Gerstein,et al.  Relating whole-genome expression data with protein-protein interactions. , 2002, Genome research.