Protein Interactomics & Interfaceomics Jong Bhak NGIC (National Genome Information Center)
KRIBB Acknowledgement People who do science because science is interesting and fun. People who support science and technology by paying tax.
MOST of Korea which funds NGIC. KRIBB for funding and support. Content Bioinformatics Protein Informatics Protein Interactomics & Interfaceomics Brief History of Bioinformatics
Darwin: A theoretical biologist Mendel: A theoretical prediction and validation Perutz and Kendrew: structural biologists Crick and Watson: DNA modellers Crick, Brenner, : Codon
Sanger: DNA sequencing: Genomics Sanger: Protein sequencing Sanger: Proteomics Lesk: Visualization of proteins Needleman & Wunch: Computer algorithms Southern: Hybridization Functional Genomics Tim Berners-Lee 1990: HTTPD Internet DNA modelling (Watson & Crick, 1953)
Darwin (evolution) Mendel (genetic analysis) Hemoglobin Myoglobin structure (Max Perutz,John Kentreu) : structure sequence structure Bio-Computation Methodology
(Chris Sander, Arther Lesk, etc ) DNA Dynamic program Sequence comparison app module (Niedleman & Bunsche) DNA chip &
Microarray technology Southern blot Hybridization methology Computer INTERNET codon
peptide anticodon sequence X-174 genome (F.sanger) : full genome sequencing DB construction (Gen Bank, PIR, ...)
Bioinformatics Expanded Structural genomics Comparative genomics Sequencing Functional genomics SNP Proteomics (Mass spec. protein chip) DataBases
Computational analysis Methodology Functions Bioinformatics People ? Explorers of 1300-1400 Charting the unknown territory of Biological Life.
Gangnido 1402 World Traffic Map Long Definition of Bioinformatics Bioinformatics is a discipline of science that analyses, seeks understanding and models the whole
life as an information processing phoenomenon utilizing energy with methods from philosophy, mathematics and computer science using biological experimental data. -- Jong Bhak A short definition of Bioinformatics Biology is bioinformatics and
bioinformatics is biology. -- Jong Bhak Research Domains of Bioinformatics Sequence Structure Expression Interaction
Function Literature What is Protein? The most informative object in the biological universe. Protein level is efficient to work with. a Naturally distinct unit. So, favoured by bioinformatic computing.
BioComplexity Density Chart Complexity degree Total complexity Relative complexity
10-e10 10-e9 10-e6 Size Scale 10-e3 1
10 Why Interactome and Interactomics? Context in Biology is always the problem of interactions Dan Bolser & Jong Bhak, Genome informatics
Why Protein Intearctome ? Protein Intearctome can give us the most valuable insights and information about biological functions in cells. (it is the best map you can have in biology) http://interactome.org Why Structural Interactomics ?
Most definite. Most informative Most accurate Directly connected to drug discovery. Structural certain well-known forces and physical rules are considered.
Most fun and beautiful to work with ? Funnel of Biological Drug Discovery Genomics Proteomics Interactomics
Structure Drug Discovery Physiomics The unit of Interaction Protein Structural Domains
What are Structural Domains ? Interaction among domains Protein A Protein B
Hydrophobic core (interior) Protein surface Interface scaffold Water Molecule Interaction crust (+) Water Molecule
geometric interface Protein surface Interaction crust (-) Interface scaffold
Hydrophobic core Detecting (defining) Domain Interaction ASA: Accessible Surface Area Voronoi Diagram A protein domain interaction map
What can we do with Interactomes? The main academic goal of Interactomics Mapping all the molecular interactions in cells Computational Human Interactome Mapping all the protein-protein and
protein-ligand interactions using computational and experimental methods. Practical Steps of Complete Human Interactome Structure DB Predicted
Human Interactome Comparative Interactomics A large scale analysis of comparing interactomes of species to understand the evolution and function of cells. Global view of protein family interaction networks for 146 genomes
Comparative Interactomics We found that all 146 interactomes are scale-free networks, and they share a core protein-interactome comprising 36 protein families related to indispensable functions in a cell. Daeui Park, Semin Lee, Dan Bolser, Michael Schroeder, Michael Lappe, Donghoon Oh, & Jong Bhak.
Bioinformatics, 2005. Eukarya and Prokarya We found two fundamental differences among prokaryotic and eukaryotic interactomes: 1) eukarya had significantly more hub families than archaea and bacteria, and 2) certain special hub families determined the
shapes of the eukaryotic interactomes. Core Interactome Interfaceomics http://interpare.net/ Analyzing the actual interaction interfaces
of protein-protein interactions. Interfaceome: the whole set of interacting molecular pairs in cells. Wankyu Kim, Dan M. Bolser and Jong Park, Bioinformatics, 2004, 20(7):1138-1150.
InterFacer Choi HanSol InterFacer http://www.interfacer.org/ Graphic User Interface of InterFacer.
Goal of Interactomics & Interfaceomics Fastest Drug Discovery Possible References Large scale co-evolution analysis of Protein Structural Interlogues using the global Protein Structural Interactome Map(PSIMAP). Wankyu Kim, Dan M. Bolser and Jong Park, Bioinformatics,
2004, 20(7):1138-1150. Visualisation and Graph-theoretic Analysis of a Large-scale Protein Structural Interactome Dan M Bolser , Panos Dafas, Richard Harrington , Jong H Park and Michael Schroeder BMC Bioinformatics 2003 4:45 Conservation of protein interaction network in evolution. Park J, Bolser D.
Genome Informatics. 2001 ;12:135-40. Mapping protein family interactions: intramolecular and intermolecular protein family interaction repertoires in the PDB and yeast. Park J, Lappe M, Teichmann SA. J Mol Biol. 2001 Mar 30;307(3):929-38. Brief Introduction on NGIC
(National Genome Information Center http://ngic.re.kr/ ) NGIC was established with the vision to become the hub of Korean bioinformatics effort: 1) collects and distributes genomic and proteomic data, 2) provides bioinformaatic databases and analysis platforms 3) promotes domestic and international research
collaborations in bioinformatics. Since 2001
