Proteomics Session 1 Session 1 Introduction Introduction
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(2) Some basic concepts in biology and biochemistry.
(3) The hierarchy of biological organism. From “molecule” to “organism”.
(4) The micro environment: Cell.
(5) DNA vs. chromosome. DNA. Chromosome.
(6) Central dogma: the story of life. DNA. RNA. Protein.
(7) DNA structure. Atomic structure. Double helix.
(8) The basic unit in DNA. C. T. A. G.
(9) From DNA to Protein. 1. Transcription. 2. Translation.
(10) Step1: Transcription, generation of mRNA.
(11) Step2: Translation, protein assembly Amino acid carrier: tRNA.
(12) Peptide bond formation. Peptide Chain.
(13) Protein structure. Primary. Secondary. Tertiary. Quaternary.
(14) The bonds contribute to protein structure. 1. Hydrogen bond 2. Hydrophobic interaction 3. Ionic bond 4. Disulfide bond.
(15) Proteins are the molecule tools for most cellular functions.
(16) What is “bioinformatics”?. Let’s take minutes to see the hot topic” bioinformatics.
(17) What is “bioinformatics”?. (Molecular) Bio – informatics One idea for a definition? Bioinformatics is conceptualizing biology in terms of molecules (in the sense of physical-chemistry) and then applying “informatics” techniques (derived from disciplines such as applied math and statistics) to understand and organize the information associated with these molecules, on a large-scale. Bioinformatics is “MIS” for Molecular Biology Information. It is a practical discipline with many applications..
(18) Bioinformatics - History 1980. 1985. 1990. 1995. 2000. 2005. Single Structures Modeling & Geometry Forces & Simulation Docking Sequences, Sequence-Structure Relationships Alignment Structure Prediction Fold recognition Genomics Dealing with many sequences Gene finding & Genome Annotation Databases Integrative Analysis Expression & Proteomics Data Data mining Simulation again…..
(19) Growth of biological databases GenBank BASEPAIR GROWTH. Source: GenBank. 3D Structures Growth:. Source: http://www.rcsb. org/pdb/holdings.html.
(20) What bioinformatics can do for us?.
(21) Example: Drug Discovery. Target Identification – Which protein to inhibit?. Lead discovery & optimization – What sort of molecule will bind to this protein?. Toxicology – Side effects, target specificity. Pharmacokinetics – Metabolization and transport.
(22) Drug Development Life Cycle Discovery (2 to 10 Years). Preclinical Testing (Lab and Animal Testing). Phase I (20-30 Healthy Volunteers used to check for safety and dosage). With the aid of bioinformatics. Phase II (100-300 Patient Volunteers used to check for efficacy and side effects). Phase III (1000-5000 Patient Volunteers used to monitor reactions to long-term drug use). $600-700 Million! FDA Review & Approval. Post-Marketing Testing. Years 0. 2. 4. 6. 8. 10. 7-15 years. 12. 14. 16.
(23) Drug lead screening 5,000 to 10,000 compounds screened. 5 Drug Candidates enter Clinical Testing; 80% Pass Phase I. 250 Lead Candidates in Preclinical Testing. 30%Pass Phase II 80% Pass Phase III. One drug approved by the FDA.
(24) Drug Lead Screening & Docking. ? Complementarily – Shape – Chemical – Electrostatic.
(25) Introduction to proteomics.
(26) What’s “proteomics” ?. "The analysis of the entire protein complement expressed by a genome, or by a cell or tissue type.“ Wasinger VC et al Progress with gene-product mapping of the mollicutes: Mycoplasma genitalium. Electrophoresis 16 (1995) 1090-1094. Two most applied technologies:. 1. 2-D electrophoresis: separation of complex protein mixtures. 2. Mass spectrometry: Identification and structure analysis.
(27) Why proteomics becomes an important discipline. Significant DNA sequencing results: – 45 microorganism genomes have been sequenced and 170 more are in progress – 5 eukaryotes have been completed Saccharomyces cerevisiae Schizosaccharomyces pombe Arabodopsis thaliana Caenorhabditis elegans Drosophilia melanogaster Rice, Mouse and Human are nearly done. However, 2/3 of all genes “identified” have no known function.
(28) Only DNA sequence is not enough. Structure Regulation Information. Those are what we need to know about proteins. Computers cannot determine which of these 3 roles DNA play solely based on sequence (although we would all like to believe they can).
(29) Introduction to Proteomics. Definitions – 1. Classical - restricted to large scale analysis of gene products involving only proteins (small view) – 2. Inclusive - combination of protein studies with analyses that have genetic components such as mRNA, genomics, and yeast two-hybrid (bigger vi ew). Don’t forget that the proteome is dynamic, changing to reflect the environment that the cell is in..
(30) 1 gene = 1protein?. 1 gene is no longer equal to one protein The definition of a gene is debatable..(ORF, promoter, pseudogene, gene product, etc) 1 gene = how many proteins? (never known).
(31) Why Proteomics?.
(32) Differential protein expression RNA. DNA. Protein. Transcription. Translation. x1. x4. Scenario 1: can be analyzed by microarray technology DNA. Stimulus. RNA. Transcription. Protein Translation. x3. Scenario 2: can be solved by proteomics technology RNA. DNA Transcription. Stimulus Translation. x3. Protein.
(33) Co- and Post-translational modification. Co-translational modified. Post-translational modified.
(34) What proteomics can answer. Protein identification Protein Expression Studies Protein Function Protein Post-Translational Modification Protein Localization and Compartmentalization Protein-Protein Interactions.
(35) General classification for Proteomics. Protein Expression comparison (beginning) – Quantitative study of protein expression between samples that differ by some variable. Structural Proteomics (simulation) – Goal is to map out the 3-D structure of proteins and protein complexes. Functional Proteomics (everything) – To study protein-protein interaction, 3-D structures, cellular localization and PTMS in order to understand the physiological function of the whole set of proteome..
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