Protein interaction networks

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Lars Juhl Jensen

Tecnología

Szklarczyk, Franceschini et al., Nucleic Acids Research , 2011

Korbel et al., Nature Biotechnology , 2004

Beyer et al., Nature Reviews Genetics , 2007

Letunic & Bork, Trends in Biochemical Sciences , 2008

Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology , 2009

BIND Biomolecular Interaction Network Database

BioGRID General Repository for Interaction Datasets

MIPS Munich Information center for Protein Sequences

KEGG Kyoto Encyclopedia of Genes and Genomes

PID NCI-Nature Pathway Interaction Database

von Mering et al., Nucleic Acids Research , 2005

Gauthier et al., Nucleic Acids Research , 2007

de Lichtenberg, Jensen et al., Science , 2005

de Lichtenberg, Jensen et al., Cell Cycle , 2007

PDSP K i Psycoactive Drug Screening Program

Kuhn et al., Nucleic Acids Research , 2010

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In interactome, basically for interaction of proteins there is certain key elements requited, they are: Interactomics and Proteomics, Complementation groups, Modifier screens 1. Interactomics and Proteomics Field of interactomics is concerned with interactions between genes or proteins. They can be genetic interactions, in which two genes are mainly involved in the same functional pathway (leading to a particular phenotype), or physical interactions, in which there is direct physical contact between two proteins (or between protein and DNA) (Janga et al.,2008). 2. Complementation groups Using forward saturation genetics, one may recover several independent mutants with the same (or similar) phenotype (Hernández et al., 2007). There are two possibilities: a) Mutations are in the same gene b) Mutations are in different genes involved in the same pathway. Scenario (b) Can be tested genetically with a complementation test:  Cross two homozygous mutants (samples) and observe heterozygous offspring phenotypes(samples) Mutations in the same gene will not complement  offspring have mutant phenotype Mutations in different genes will complement  offspring have wild Type phenotype  Do pairwise crosses for all mutants to identify complementation groups  Typically each complementation group represents a different gene  If many mutations are recovered in the same genes, this implies saturation

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Proteins facilitates most biological processes in a cell, including gene expression, cell growth, proliferation, nutrient uptake, morphology, motility, intercellular communication and apoptosis. Protein–protein interactions (PPIs) refer to physical contacts established between two or more proteins as a result of biochemical events. These interactions are very important in our lives as any disorder in them can lead to fatal diseases such as Alzheimer’s and Creutzfeld- Jacob Disease. The most well known example of Protein-Protein Interaction is between Actin and Myosin while regulating Muscular contraction in our body. The protein –protein interaction have commonly been termed the ‘INTERACTOME’ by scientists. Homo-Oligomers: Complexes having one type of protein subunits. E.g. : PPIs in Muscle Contraction Hetero-Oligomers: Complexes having multiple types protein subunits. E.g. : PPI between Cytochrome Oxidase and TRPC3 (Transient receptor potential cation channels

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Protein-Protein interactions discovered by the existing high-throughput techniques contain very high amount of false positives. Here we present an SVM based approach to generate a model that is built on sequence and non-sequence based information of the interacting proteins. This model is used to assess the reliability of given protein-protein interactions. It was run on the interaction data of a pathogenic bacterium; Treponema pallidum (causes Syphilis in humans) obtained from Yeast two hybrid experiments. Various kernels were used for building the model and of all, Sigmoid kernel performed well when used with all the features combined with area under the receiver operating curve (ROC) as 0.53.

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