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1. G Protein Coupled Receptors. A project of David Lutje Hulsik and Tim Hulsen. May 7th, 2001. 2. What are GPCRs?. Membrane-bound receptors. Transducing messages as photons, organic odorants, nucleotides, nucleosides, peptides, lipids and proteins. 6 different families.
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G Protein Coupled Receptors A project of David Lutje Hulsik and Tim Hulsen May 7th, 2001 2
What are GPCRs? Membrane-bound receptors Transducing messages as photons, organic odorants, nucleotides, nucleosides, peptides, lipids and proteins. 6 different families A very large number of different domains both to bind their ligand and to activate G proteins. 3
GPCR Structure Seven transmembrane regions Hydrophobic/ hydrophilic domains Conserved residues and motifs (i.e. NPXXY) 4
GPCR-G protein coupling Receptor gets activated by agonist G protein binds to activated receptor Agonist binding to receptor becomes stronger upon G protein coupling GDP is released G protein takes up GTP GTP uptake triggers release of G protein from receptor 5
Research goals To determine whetherpredictions made about the structure of GPCRs are correct To see which methods give the best results 6
Major research difficulties • Residue numbering: Schwartz / Baldwin (e.g. V.16) Ballesteros-Weinstein (e.g. 6.50) etc. Available high-resolution structural information Bacteriorhodopsin as template 7
Bacteriorhodopsin Photosynthetic bacteria Proton pumping G proteins not involved Helical arrangement Conformation 8
Studies on GPCRs Mutation studies Spinlabel NMR Cystein scanning Protease studies Photoaffinity 9
Methods Collecting data • Making alignment with the use of several articles which compare a GPCR with bacteriorhodopsin Structure validation with WHAT-IF 10
Collecting Data • Articles Oldfashioned library work Online libraries (PubMed) • Websites Different GPCR-groups • Online databases GPCRDB 11
Making Alignments • Structural alignment rhodopsin/bacteriorhodopsin ---------- -WIWLALGTA LMGLGTLYFL VK-------- BRh ----PWQFSM LAAYMFLLIM LGFPINFLTL YVTVQ----- Rh • Comparing with alignments made by other GPCR-experts ---------- -WIWLALGTA LMGLGTLYFL VK-------- BRh ----PWQFSM LAAYMFLLIM LGFPINFLTL YVTVQ----- Rh ---------P EWIWLALGTA LMGLGTLYFL VKGM------ BRh Vriend ---------Q FSMLAAYMFL LIMLGFPINF LTLY------ Rh Vriend Difference: +3 • Helix 3 means trouble Differences were larger then +10. Complete alignment 12
Structure validation with WHAT-IF I • Structure predictions by Baldwin et al. Electron density maps 493 GPCR (a.a.)sequences Helical orientation Interacting residues Helical orientation as predicted was correct Only a few residues interact: :17 G P VII:18 :18 N A II:11D II:14 :21 V A II:11 Y VII:21 13
Structure validation with WHAT-IF II • Structure predictions by Thirstrup et al. Construction of zinc binding site -opioid receptor Helical orientation Helix-helix interactions Measured distances between zinc ion and residues too large; even with the use of the ‘tors’ command 14
Residue Contact Greenhalgh et al. Contact WhatIF Difference Arg-82 Extracellular about 5 Tyr-79 6.1 1.1 Asp-85 Extracellular about 9 Tyr-79 10.8 1.8 Asp-96 Intracellular within 7 Val-101 8.8 1.8 Structure validation with WHAT-IF III • Structure predictions by Greenhalgh et al. Spin label; electron paramagnetic resonance spectroscopy Mapping residue positions (relative to aqueous boundaries) Distances for bacteriorhodopsin (in Å): Differences are within range; spin-labeling could be a reasonably safe way to predict the structure of membrane proteins 15
Conclusions Predicting a structure with such low level of homology is very hard Availability of real data (e.g. electron density maps) improves structure prediction Most predictions are in the right direction, but still need some refinement 16
Take a look at our website! http://go.to/gpcr 17
Learning points Programming in Python What-IF GPCRs Website building (e.g. CGI) 17