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Structure Prediction of human
Histamine 4 Receptor (hH4R)
Charlie Seto, Bioinformatics Summer Institute, CSULA
Ravi Abrol & Soo-Kyung Kim, MSC, CalTech
William Goddard, MSC, CalTech
Outline
Why Study GPCRs?
Objective
H4R
Structure Prediction & Building
Ligand docking
Future Work
“Core of Modern Medicine”
GPCRs have cell signaling
functions
40% of new drugs target
GPCRs
Novartis: Zelnorm (5-HT4)
Eli Lilly: Zyprexa (5-HT2)
Schering-Plough: Clarinex
(H1)
GlaxoSmithKline: Zantac
(H2)
(Source: Modern Drug Discovery, “It’s a GPCR
World”, Nov 2004)
H4R (Histamine H4 Receptor)
All H4 functions still not
known
Together with H1, asthma?
H4 is unique
Dissimilar to H1, H2, H3
Known Histamine receptor
ligands weak against H4R.
New ligands needed to
optimize drugs!
Or, to increase specificity
Histamine
Objective of your Project
Predict 3D structure of Histamine H4
Receptor (H4R) from AA sequence
Validate structure with known ligands,
Histamine etc.
Good structure for drug design
Other questions
Difference of H4R vs. other Histamine
receptors?
TM Prediction
Perform BLAST with H4R sequence
“Broad search”, E-value = 0.1
Run multiple-sequence alignment
Develop hydrophobicity profile by
averaging BLASTed sub-profiles
Prediction of TM regions based on
hydrophobicity
Get hydrophobic center, controls TM
“depth”
Hydrophobicity Profile
Hydrophobicity Profile of H4R from predictm, window=1
0.8
0.6
Hydrophobicity Value
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
-1.2
TM2 poorly defined
Large hydrophilic domain
implies cytosolic loop
hydrophobicity, residue
hpc, raw geometric center
Other PredictM output
PredicTM’s BLAST output
Nearest relative was H4R in Mouse & Rat
~79-80%
Histamine 3-R, paralog
~55%
identity, #6
Human β-2 Adrenergic (template)
TM
identity (#1 & #2)
~33% identity, #179
Bovine Rhodopsin (template)
~22%
identity, #1249
“Final” TM Sequence
TM
TM
TM
TM
TM
TM
TM
1:
2:
3:
4:
5:
6:
7:
15-RVTLAFFMSLVAFAIMLGNALVILA-39
51-SYFFLNLAISDFFVGVISIPLYIPHTLFEWDFGK-85
88-VFWLTTDYLLCTASVYNIVLISY-111
131-VLKIVTLMVAVWVLAFLVNGPMILV-155
169-EWYILAITSFLEFVIPVILVAYFNMNIYWS-203
303-KSLAILLGVFAVCWAPYSLF-327
336-KSVWYRIAFWLQWFNSFVN-359
Helix Kinking
Have:
TM sequences
Need:
3D structure
First:
Predict helix
kinking
Pro71
Helix
kinking caused by
Pro & Gly residues,
stabilized by Ser & Thr
Right: TM2, minrmsd method.
Pro75
Helix Building
Compare helices
to template
(human β2 ADR)
Template
determines angle
of insertion into
membrane,
orientation of TMs
0°
15°
30°
Rotation
Bihelix Pairing:
Adjacent helices
paired off, rotated (12
combinations)
Bihelix data
aggregated to build 7TM structures
Visual Analysis
Visually check H-bonds
Check for GPCR motifs
NPxxY
1-2-7 networks, etc
Structure Activity Data
Example: Mutate Asp94…no activity,
therefore…Asp94 important! (Assess angle
and coordinate)
Asn147 (4.57)
Theorized
imidazole
binding pocket
Glu182 (5.46)
Asp94 (3.32)
Ligands
“Build” in Maestro
Special pre-reqs for
selecting ligands
Need experimental
data for binding
Big Picture: Ligands
are to validate
structure!
Imetit, agonist
Current Progress
Analysis continues
Missing expected interhelical interactions
Causes
being investigated
A highly polar motif on TM2 may have shifted the
structure
Not found on other Histamines, or templates
Will continue with pre-docking
Assess
ligand affinity data after docking
Determine if structure “good/bad” by
comparison to experimental data
Special Thanks
Mentor: Ravinder Abrol & Soo-Kyung Kim, MSC,
Caltech
PI: William Goddard, MSC, Caltech
Other members of Biogroup, MSC
The SoCalBSI faculty team
Dr. Sandra Sharp
Dr. Wendie Johnston
Dr. Jamil Momand
Dr. Nancy Warter-Perez
…and others
Funding provided by:
References
D. FILMORE. “It’s a GPCR World” Modern Drug Discovery Nov
2004
N. SHIN, E. COATES, N. J. MURGOLO, K. L. MORSE, M. BAYNE,
C. D. STRADER, and F. J. MONSMA, JR. “Molecular Modeling
and Site-Specific Mutagenesis of the Histamine-Binding Site of
the Histamine H4 Receptor” Mol Pharmacol 62:38–47, 2002