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Page 1: 1 Chapter 8Proteomics 暨南大學資訊工程學系 黃光璿 2004/06/07 2 proteome  the sum total of an organism’s proteins genome  the sum total of an organism’s genetic

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Chapter 8 Proteomics

暨南大學資訊工程學系黃光璿2004/06/07

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proteome the sum total of an organism’s proteins

genome the sum total of an organism’s genetic

material

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8.1 From Genomes to ProteomesWe want to know what proteins are present in cells; what those proteins do and how they

function.

However, it’s not easy.

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Why?

1. The longevity (壽命 ) of an mRNA and the protein it codes for are very different.

2. Many proteins are extensively modified after translation.

3. Many proteins are not functionally relevant until they are assembled into larger complexes or delivered to an appropriate location.

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4. Proteins require more careful handling than DNA.

Function may change. Protein identification requires

mass spectrometric analysis specific antibodies.

Obtaining large numbers of protein molecules requires chemical isolation for living cells.

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8.2 Protein Classification

Based on protein function

six categories evolutionary history & structural

similarity 1000 homologous families

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8.2.1 Enzyme Nomenclature

Started at 1950s

International Union of Biochemistry and Molecular Biology

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8.2.2 Family and Superfamily

Modern-day proteins may be derived from ~ 1000 original proteins.

folds superfamilies families databases

SCOP, CATH, DALI

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fold the same major secondary structure & topologi

cal connections superfamily

probable evolutionary relationships family

clear evolutionary relationships

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8.3 Experimental Techniques

2D Electrophoresis Mass Spectrometry

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2D Electrophoresis

http://tw.expasy.org/cgi-bin/map1

liver kidney

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Problems tens of thousand v.s. thousands under presentation of membrane-bound pr

oteins difficult to determine exactly which protein

is represented

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8.3.2 Mass Spectrometry

2D mass spectrometry, for identification

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8.3.3 Protein Microarrays

Use antibodies as probes.

Problems Single proteins will interact with

multiple probes. The binding kinetics of each probe are

different. Proteins are sensitive to their

environment.

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8.4 Inhibitors and Drug Design development & testing of a new drug

~ 15 years, US$ 700 million discovery

target identification lead discovery & optimization toxicology (毒理學 ) pharmacokinetics

testing

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HIV protease has an active site; cuts a single, large polypeptide chain into

many proteins.

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8.5 Ligand Screening

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8.5.1 Ligand Docking

Determine how two molecules of known structure will interact.

Three issues: Identify the energy of a particular

molecular conformations. Search for the conformation that

minimizes the free energy.

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How to deal with flexibility in both the protein and the putative ligand. Lock and key approaches

rigid protein structure, flexible ligand structure induced fit docking

flexible in both protein and ligand

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Softwares AutoDock FTDock DOCK Hammerhead Gold FlexX

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8.5.2 Database Screening

Primary consideration complete and accurate search with a reasonable computational complexity

SLIDE Fig. 8.4

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8.6 X-Ray Crystal Structures

W. C. Roentgen (1895) discovered X-rays. M. von Laue (1912) discovered crystals diffr

act X-rays. D. Hodgkin, etc. (1950s), crystallized compl

ex organic molecules and determined their structures.

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grow a crystal of the protein

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File formats PDB formatted text mmCIF (MacroMolecular Crystallographic Infor

mation File)

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databases & resources PDB PIR ExPASy

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Visualizing Tools Fig. 8.8 RasMol Swiss PDB viewer VMD (Visual Molecular Dynamics) Spock Protein explorer DINO

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8.7 NMR Structures

~ 200 amino acids the structures determined are not

unique

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8.8 Empirical Methods and Prediction Techniques Example: Fig. 8.9 extracting features learning, training testing

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8.9 Post-Translational Modification Prediction Remove segments of a protein. Covalently attach sugars, phosphates,

or sulfate groups into surface residues. Cross-link residues within a protein

(disulfide bond).

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8.9.1 Protein Sorting

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associated with membranes not associated with membranesTable 8.3 (Case 2)

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PSORT: nearest neighbor classifier Prediction of protein subcellular localization

SignalP: artificial neural networks Prediction of signal peptide cleavage sites

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8.9.2 Proteolytic Cleavage

chymotrypsin cleaves polypeptides on the C-terminal side of

bulky and aromatic residues trypsin

cleaves on the carboxyl side elastase

cleaves on the C-terminal side of small residues

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Prediction proteasomes, > 98%, by neural network

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8.9.3 Glycosylation

The process of covalently linking an oligosaccharide to the side chain of a protein surface residue (科學人 )

N-linked, 75% O-linked, 85%

by neural network

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8.9.4 Phosphorylation

kinases : add phosphatases : remove

signal

NetPhos, > 70%, neural network

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參考資料及圖片出處

1. Fundamental Concepts of BioinformaticsDan E. Krane and Michael L. Raymer, Benjamin/Cummings, 2003.

2. Merrian-Webster Dictionary