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Computational Approaches to GPCR Structure anf function Christopher A Reynolds Department of Biological Sciences University of Essex United Kingdom Essex.

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Presentation on theme: "Computational Approaches to GPCR Structure anf function Christopher A Reynolds Department of Biological Sciences University of Essex United Kingdom Essex."— Presentation transcript:

1 Computational Approaches to GPCR Structure anf function Christopher A Reynolds Department of Biological Sciences University of Essex United Kingdom Essex Campus, John Constable (original in Washington)

2 Acknowledgements Bruck Tadesse (GPCR Modelling) Shabana Vohra (GPCR Modelling) Kevin Smith (docking) David Poyner (Aston) James Barwell (Aston) Alex Conner (Warwick) Mike Woolley (Warwick) Debbie Hay (Aukland, NZ) Harriett Watkins (Aukland, NZ) Graham Upton (Maths, Essex, Statistics) BHF for funding (grant about to start) Key publications: Vohra et al. (2013), Wooley et al. (2013), J. Roy. Soc. Interface

3 Introducing Class B GPCRs CGRP (calcitonin gene-related peptide receptor) Involved in vasodilation Potential target for cardiovascular drugs, migrane Aim: understand structure, mechanism Motivation: new drug target c.f. well-known class A GPCRs, e.g. Dopamine D2 100 90 80 70 60 50 40 30 20 10 0 Percentage Identity Twilight zone (18 – 25% ) N-terminus Helical domain CGRP peptide RAMP: receptor activity modifying protein CLR (no function) Functional CGRPR (CLR + RAMP) Challenge: no structure no known motifs in common alignment in ‘midnight zone’ i.e. %ID 13%, below threshold

4 Other Class B GPCRs (144 Residues) Blue – no effect on cAMP production Orange / purple– no effect Mutagenesis data: Class B GPCRs CGRP (122 residues)

5 Class A profile (TM3) Class B profile (TM3) Helix alignment: novel method Pair-wise alignments (1000s) # of votes (scaled 0 – 1) Alignment

6 Product score -8 -4 0 4 8 alignment -8 -4 0 4 8 alignment -8 -4 0 4 8 alignment The class A –class E (GCR1) – class B alignment Potential for the best method for aligning remote homologues? Develop for class C GPCRs (e.g. mGluR5, Parkinson’s) Systematic studies of all GPCR families (Good test cases welcome)

7 Red: only fits 0 alignment Blue: consistent with alignment Grey: inconclusive Model verification: interpreting mutations Multiple MD refined models: 2 inactive: Implicit membrane Explicit membrane 2 Active: G-protein bound Peptide bound (MD essential to get active models) Residue function? Consistent with alignment?

8 DRY/ YLH R...H...E RKLHxxxN disulfide W 4.50 FxxP IxxL KxxK P...W EVxxxL NPXXY/ VAVLY R 2.43 – T 6.37 ionic lock closed cf R 3.50 – E 6.30 open Motifs common to class A, GCR1 and class B GPCRs No motifs in common?

9 Experimental approach to ECL2 conformation

10 A1A1 T6T6 T288 A203 TM5 TM1 TM2 TM4 (B) Verified docked pose from sequence analysis (correlated mutations) C 2 -C 7 (C) Built helical extension (mutagenesis); generated 100 conformations of extracellular loop 2 (go beyond sampling limits of MD). ECL2 Modeller DOPE score Number of interactions Computational approach to ECL2 conformation (A) Docked CGRP 1-7 (docking methodology under development, MRC funding)

11 Validation of ECL2 conformation? Y277 Y278 Y287 R274 CGRP A273 L290 L291 TM5 TM4 TM5 TM3 TM 6 TM7 TM3 TM4 TM5 TM2 TM6 TM1 T288 A5A5 W283 D280 R 11 H 10 I284 T6T6 S285 T4T4 D3D3 CGRP (A) (B) (C) TM3 TM4 H8 TM1 TM2 TM3 TM1 TM2 TM3 TM7 TM6 TM4 TM5 ECL2: CLR (CGRP) CLR (AM) CRF1R GCGR (D) (E) Interactions suggest mechanisms for helix movement / activation...to be explored further


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