Short Co-occurring Polypeptide Regions Can Predict Global Protein Interaction Maps

A goal of the post-genomics era has been to elucidate a detailed global map of protein-protein interactions (PPIs) within a cell. Here, we show that the presence of co-occurring short polypeptide sequences between interacting protein partners appears to be conserved across different organisms. We present an algorithm to automatically generate PPI prediction method parameters for various organisms and illustrate that global PPIs can be predicted from previously reported PPIs within the same or a different organism using protein primary sequences. The PPI prediction code is further accelerated through the use of parallel multi-core programming, which improves its usability for large scale or proteome-wide PPI prediction. We predict and analyze hundreds of novel human PPIs, experimentally confirm protein functions and importantly predict the first genome-wide PPI maps for S. pombe (∼9,000 PPIs) and C. elegans (∼37,500 PPIs).

[1]  J. Greenblatt,et al.  Interacting proteins Rtt109 and Vps75 affect the efficiency of non-homologous end-joining in Saccharomyces cerevisiae. , 2008, Archives of biochemistry and biophysics.

[2]  Kara Dolinski,et al.  The BioGRID Interaction Database: 2011 update , 2010, Nucleic Acids Res..

[3]  angesichts der Corona-Pandemie,et al.  UPDATE , 1973, The Lancet.

[4]  Menglong Li,et al.  PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment , 2010, BMC Research Notes.

[5]  Ronald W. Davis,et al.  Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. , 1999, Science.

[6]  Nazar Zaki,et al.  Protein-protein interaction based on pairwise similarity , 2009, BMC Bioinformatics.

[7]  Juwen Shen,et al.  Predicting protein–protein interactions based only on sequences information , 2007, Proceedings of the National Academy of Sciences.

[8]  Peter B. McGarvey,et al.  Infrastructure for the life sciences: design and implementation of the UniProt website , 2009, BMC Bioinformatics.

[9]  Ashkan Golshani,et al.  Computational methods for predicting protein-protein interactions. , 2008, Advances in biochemical engineering/biotechnology.

[10]  Sandhya Rani,et al.  Human Protein Reference Database—2009 update , 2008, Nucleic Acids Res..

[11]  S. Roy,et al.  Differences in in vivo acceptor specificity of two galactosyltransferases, the gmh3+ and gma12+ gene products from Schizosaccharomyces pombe. , 1998, European journal of biochemistry.

[12]  Jean-Loup Faulon,et al.  Predicting protein-protein interactions using signature products , 2005, Bioinform..

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

[14]  Yanzhi Guo,et al.  Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences , 2008, Nucleic acids research.

[15]  Yungki Park,et al.  Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences , 2009, BMC Bioinformatics.

[16]  Christopher W. V. Hogue,et al.  Structure-Templated Predictions of Novel Protein Interactions from Sequence Information , 2007, PLoS Comput. Biol..

[17]  R. Nussinov,et al.  Allo-network drugs: harnessing allostery in cellular networks. , 2011, Trends in pharmacological sciences.

[18]  Darby Tien-Hao Chang,et al.  Predicting protein-protein interactions in unbalanced data using the primary structure of proteins , 2010, BMC Bioinformatics.

[19]  Jennifer M. Rust,et al.  The BioGRID Interaction Database , 2011 .

[20]  Beatriz García Jiménez,et al.  EcID. A database for the inference of functional interactions in E. coli , 2008, Nucleic Acids Res..

[21]  T. Gibson,et al.  Systematic Discovery of New Recognition Peptides Mediating Protein Interaction Networks , 2005, PLoS biology.

[22]  Mark Gerstein,et al.  The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics , 2007, PLoS Comput. Biol..

[23]  William Stafford Noble,et al.  Choosing negative examples for the prediction of protein-protein interactions , 2006, BMC Bioinformatics.

[24]  Le Hoa Tan,et al.  Recent advances in protein–protein interaction prediction: experimental and computational methods , 2011, Expert opinion on drug discovery.

[25]  Albert Chan,et al.  PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs , 2006, BMC Bioinformatics.

[26]  J. R. Green,et al.  Global investigation of protein–protein interactions in yeast Saccharomyces cerevisiae using re-occurring short polypeptide sequences , 2008, Nucleic acids research.