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Computational Analysis of the Structure
of Human Histamine 2 GPCR
Presented by Alana Canfield
William Goddard
Ravi Abrol and Soo-Kyung Kim
SoCalBSI Program
August 21, 2008
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GPCR : G-Protein Coupled Receptor
H2 is a histamine receptor involved in gastric
acid secretion in gastrointestinal system.
Image courtesy of http://www.zmnh.uni-hamburg.de/schaller/gpcr.jpg
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Membrane proteins are involved in a large
number of biological processes.
◦ Signal transduction pathways
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Lack of crystal structures makes
computational approaches necessary.
Structures are needed in therapeutic drug
design.
◦ More than 50% of marketed drugs target GPCR’s
Beta-2 Receptor
Asp98
TM3
TM3
TM5
H2 Receptor: Optimize Asp98
Asp98
TM5
TM3
TM5
Individual Helices
Determine
transmembrane
residues.
Optimize helix kinks.
Predict orientations of
helices according to
template crystal structure.
Helix Bundle
Determine
helix
orientations in space.
Analyze final bundle
structurally and
energetically.
Bundle+Ligand
Add
extracellular loops.
Use final structure to
dock various ligands.
Analyze possible
activation pathways.
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Transmembrane (TM) regions predicted using
hydrophobicity profile and homology search.
Hydrophobicity Value
Hydrophobicity Plot
1
1 2 3
4
5
6 7
0.5
0
-0.5
0
100
200
-1
300
400
REGION
CONSENSUS RESIDUES
TM1
TM2
TM3
TM4
TM5
TM6
TM7
KITITVVLAVLILITVAGNVVVCLAV
NCFIVSLAITDLLLGLLVLPFSAIYQLSCK
NIYTSLDVMLCTASILNLFMISLD
RVAISLVLIWVISITLSFLSIH
EVYGLVDGLVTFYLPLLIMCITYYRIFK
KATVTLAAVMGAFIICWFPYFTAFVYRGLR
EAIVLWLGYANSALNPILYAALNR
-1.5
Residue Number
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The ‘cap’ regions (helix ends) must carefully be
considered.
Transmembrane Region 7
H1 :
H2 :
H3 :
H4 :
FINAL:
NEHLHMFTIWLGYINSTLNPLIYPLCNE
NEVLEAIVLWLGYANSALNPILYAALNR
PDYWYETSFWLLWANSAVNPVLYPLCHH
KSVWYRIAFWLQWFNSFVNPLLYPLCHK
EAIVLWLGYANSALNPILYAALNR
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Helices may have characteristic ‘kinks’.
For individual helices, all residues except Pro,
Gly, Thr, and Ser were alanized.
◦ This results in conformational sampling while
maintaining the over helix character
Kinked Helix
Un-kinked Helix
Bovine Rhodopsin AND Human Beta-2 Adrenergic Receptor
Area AND Rawmid
Minimum Energy AND Minimum RMSD
Not Alanized
Alanized
De-alanize All
De-alanize Raw
The Energetic/Structure Story:

Compare to Bovine Rhodopsin and Human
Beta-2 Crystal Structures
‘2-3-4’-Similar Network
NPxxY Region
THR2.49
TYR7.53
ASP2.50
SER2.45
ASN7.49
ASN3.42
The Energetic/Chemical Structure Story:
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Many favorable inter-helical hydrogen bonds.
Bond
RMSD/AREA & Dealanize All
RMSD/AREA & Dealanize Raw
Asp186-Arg257
2.64
2.64
Cys102-Tyr250
3.33
3.32
Tyr94-Tyr78
3.32
3.24
Asp64-Tyr288
2.74
2.75
Asp64-Asn284
2.83
2.85
Tyr288-Asn284
2.98
4.06
Thr63-Asn108
2.73
2.73
Tyr278-Gln79
2.72
2.72
Ser59-Asn108
3.10
3.08
Ser59-Thr63
3.98
3.96
Cys246-Asn280
3.36
3.36
Ser105-Asp64
3.77
3.62
Asn108-Ser59 (#2)
2.96
2.97
The Energetic/Chemical Structure Story:

Of the top energy structures, the two best structural
results are:
◦ 1) RMSD analysis, ‘area’ midpoint, ‘all’
dealanization.
 Rotation Angles: 90-30-0-120-180-330-0
◦ 2) RMSD analysis, ‘area’ midpoint, ‘raw’
dealanization.
 Rotation Angles: 90-30-0-120-180-330-0
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Note that the rotation angles are the same!
Further Structural Analysis - Homology:
Asn1.50 and W4.50
Rotations: 90-30-0-120-180-330-0
Rotations: 300-30-0-30-180-330-0
THR2.49
TRP4.50
THR2.49
ASN3.42
ASN3.42
SER2.45
TRP4.50
SER2.45
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Docking to four receptors:
◦ 1) Best energetic/chemical structure and 2) best
homology-based structure.
 Both 1) and 2) : with and without rotamer optimization
of Asp98.
optimize
Asp98
Asp98
Cimitidine (crystal)
Clobenpropit
ICL 162846
Tiotidine
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I am docking the ligand cimitidine.
Final goals for group: Compare the four
different histamine receptors in order to gain
insight into selectivity.
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Novel Insights Into Histamine H2 Receptor Biology,
John Del Valle and Ira Gantz, Am J Physiol
Gastrointest Liver Physiol 273:987-996, 1997.
A study of antagonist affinities for the human
histamine H2 receptor, JG Baker, British Journal of
Pharmacology (2008) 153, 1011–1021
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Structural diversity of G protein-coupled receptors
and significance for drug discovery, Malin C.
Lagerström and Helgi B. Schiöth, Nature Reviews,
Volume 7 , April 2008
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Caltech:
◦
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Professor Goddard
Ravi Abrol
Soo-Kyung Kim
Charlie Seto
SoCal Bioinformatics Research Institute:
◦ Core Instructors:
 Dr. Jamil Mommand, Dr. Sandra Sharp, Dr. Wendy Johnston
 Dr. Nancy Warter-Perez, Dr. Beverly Krilowicz
 Dr. Silvia Heubach, Dr. Jennifer Faust
◦ Program Coordinator: Ronnie Cheng
◦ All SocalBSI faculty and students
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Funding:
◦ NSF, NIH, Economic and Workforce Development