Centre for Integrative Bioinformatics VU (IBIVU)

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Bioinformatics master course DNA/Protein structure-function analysis and prediction Lecture 13: Protein Function Centre for Integrative Bioinformatics VU (IBIVU) Faculty of Sciences / Faculty of Earth & Life Sciences

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Bioinformatics master course DNA/Protein structure-function analysis and prediction Lecture 13: Protein Function. Centre for Integrative Bioinformatics VU (IBIVU) Faculty of Sciences / Faculty of Earth & Life Sciences. Sequence-Structure-Function. Sequence Structure Function. - PowerPoint PPT Presentation

Transcript of Centre for Integrative Bioinformatics VU (IBIVU)

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Bioinformatics master courseDNA/Protein structure-function analysis and prediction

Lecture 13: Protein Function

Centre for Integrative Bioinformatics VU (IBIVU)

Faculty of Sciences / Faculty of Earth & Life Sciences

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Sequence-Structure-Function

Sequence

Structure

Function

ThreadingAb initio

BLAST

Folding: impossible but for the smallest structures

Function prediction from structure – very difficult

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Experimental

• Structural genomics

• Functional genomics

• Protein-protein interaction

• Metabolic pathways

• Expression data

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Protein function categories• Catalysis (enzymes)

• Binding – transport (active/passive)

– Protein-DNA/RNA binding (e.g. histones, transcription factors)

– Protein-protein interactions (e.g. antibody-lysozyme) (experimentally determined by yeast two-hybrid (Y2H) or bacterial two-hybrid (B2H) screening )

– Protein-fatty acid binding (e.g. apolipoproteins)

– Protein – small molecules (drug interaction, structure decoding)

• Structural component (e.g. -crystallin)

• Regulation

• Signalling

• Transcription regulation

• Immune system

• Motor proteins (actin/myosin)

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Catalytic properties of enzymes

Km kcat

• E + S ES E + PE = enzymeS = substrateES = enzyme-substrate complex (transition state)P = productKm = Michaelis constantkcat = catalytic rate constant (turnover number)Kcat/Km = specificity constant (useful for comparison)

[S]

Mol

es/s

Vmax

Vmax/2

Km

Vmax × [S]V = ------------------- Michaelis-Menten equation Km + [S]

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Protein interaction domains

Protein Interaction Domains

    

     

 

   

      

          

 

     

   

 

     

 

     

      

 

     

     

 

      

       

      

      

    

      

     

       

      

    

     

   

 

      

   

     

 

    

 

    

     

      

     

       

      

     

     

     

       

     

     

      

         

         

       

     

                  

http://pawsonlab.mshri.on.ca/html/domains.html

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Energy difference upon binding

Examples of protein interactions (and functional importance) include: • Protein – protein (pathway analysis); • Protein – small molecules (drug interaction, structure decoding); • Protein – peptides, DNA/RNA  (function analysis)

 The change in Gibb’s Free Energy of the protein-ligand binding interaction can be monitored

and expressed by the following; G = H – T S        (H=Enthalpy, S=Entropy and T=Temperature)

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Protein function

• Many proteins combine functions

• Some immunoglobulin structures are thought to have more than 100 different functions (and active/binding sites)

• Alternative splicing can generate (partially) alternative structures

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Protein function

Active site / binding cleft

Protein-protein interaction

Shape complementarity

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Protein function evolution

Chymotrypsin

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How to infer function

• Experiment• Deduction from sequence

– Multiple sequence alignment – conservation patterns– Homology searching

• Deduction from structure– Threading– Structure-structure comparison– Homology modelling

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Mevalonate plays a role in epithelial cancers: it can inhibit EGFR

Cholesterol biosynthesis primarily occurs in eukaryotic cells. It is necessary for membrane synthesis, and is a precursor for steroid hormone production as well as for vitamin D. While the pathway had previously been assumed to be localized in the cytosol and ER, more recent evidence suggests that a good deal of the enzymes in the pathway exist largely, if not exclusively, in the peroxisome (the enzymes listed in blue in the pathway to the left are thought to be at least partly peroxisomal). Patients with peroxisome biogenesis disorders (PBDs) have a variable deficiency in cholesterol

biosynthesis

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Epidermal Growth Factor as a Clinical Target in Cancer

Introduction:

A malignant tumour is the product of uncontrolled cell proliferation. Cell growth is controlled by a delicate balance between growth-promoting and growth-inhibiting factors. In normal tissue the production and activity of these factors results in differentiated cells growing in a controlled and regulated manner that maintains the normal integrity and functioning of the organ. The malignant cell has evaded this control; the natural balance is disturbed (via a variety of mechanisms) and unregulated, aberrant cell growth occurs. A key driver for growth is the epidermal growth factor (EGF) and the receptor for EGF (the EGFR) has been implicated in the development and progression of a number of human solid tumours including those of the lung, breast, prostate, colon, ovary, head and neck.

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Energy housekeeping: Adenosine diphosphate (ADP) – Adenosine triphosphate (ATP)

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Metabolic Metabolic networksnetworks

Glycolysis Glycolysis and and

GluconeogenesisGluconeogenesis

Kegg database (Japan)

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Gene Ontology (GO)

• Not a genome sequence database

• Developing three structured, controlled vocabularies (ontologies) to describe gene products in terms of:– biological process– cellular component– molecular function

in a species-independent manner

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The GO ontology

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Gene Ontology Members

• FlyBase - database for the fruitfly Drosophila melanogaster • Berkeley Drosophila Genome Project (BDGP) - Drosophila informatics; GO database & software, Sequence Ontology development • Saccharomyces Genome Database (SGD) - database for the budding yeast Saccharomyces cerevisiae • Mouse Genome Database (MGD) & Gene Expression Database (GXD) - databases for the mouse Mus musculus • The Arabidopsis Information Resource (TAIR) - database for the brassica family plant Arabidopsis thaliana • WormBase - database for the nematode Caenorhabditis elegans • EBI GOA project : annotation of UniProt (Swiss-Prot/TrEMBL/PIR) and InterPro databases • Rat Genome Database (RGD)  - database for the rat Rattus norvegicus • DictyBase  - informatics resource for the slime mold Dictyostelium discoideum • GeneDB S. pombe - database for the fission yeast Schizosaccharomyces pombe (part of the Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute) • GeneDB for protozoa - databases for Plasmodium falciparum, Leishmania major, Trypanosoma brucei, and several other protozoan parasites (part of the Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute) • Genome Knowledge Base (GK) - a collaboration between Cold Spring Harbor Laboratory and EBI) • TIGR - The Institute for Genomic Research • Gramene - A Comparative Mapping Resource for Monocots • Compugen (with its Internet Research Engine) • The Zebrafish Information Network (ZFIN) - reference datasets and information on Danio rerio