single nucleotide polymorphism (snp) actcgagcta actcgcgcta
TRANSCRIPT
TYPE EXAMPLE EFFECT
Neutral Non-coding, non-regulatory, synonymous
No effect
Individual characteristics
Big Nose… Mating success
TYPE EXAMPLE EFFECT
Neutral Non-coding, non-regulatory, synonymous
No effect
Individual characteristics
Big Nose… Mating success
Drug Efficacy Cytochrome P450 Disease treatment
TYPE EXAMPLE EFFECT
Neutral Non-coding, non-regulatory, synonymous
No effect
Individual characteristics
Big Nose… Mating success
Drug Efficacy Cytochrome P450 Disease treatment
Multi-factorial, complex trait, poly-genic late disease
APOE, FAS1,…. Alzheimer
Multi-factorial early disease
?,?,?
Asthma
TYPE EXAMPLE EFFECT
Neutral Non-coding, non-regulatory, synonymous
No effect
Individual characteristics
Big Nose… Mating success
Drug Efficacy Cytochrome P450 Disease treatment
Multi-factorial, complex trait, poly-genic late disease
APOE, FAS1,…. Alzheimer
Multi-factorial early disease
?,?,?
Asthma
Single factor, mono-genic disease (‘mild’)
Sickle cell hemoglobin
Anemia
Single factor disease (severe)
Cu transporter Early death
TYPE EXAMPLE EFFECT
Neutral Non-coding, non-regulatory, synonymous
No effect
Individual characteristics
Big Nose… Mating success
Drug Efficacy Cytochrome P450 Disease treatment
Multi-factorial, complex trait, poly-genic late disease
APOE, FAS1,…. Alzheimer
Multi-factorial early disease
?,?,?
Asthma
Single factor, mono-genic disease (‘mild’)
Sickle cell hemoglobin
Anemia
Single factor disease (severe)
Cu transporter Early death
Fatal ?,?,? Non-Viable Fetus
Monogenic Versus PolygenicDisease
• Monogenic: One base change = disease.
Relatively easy to detect and analyze.
• Polygenic: A set of base changes affect the probability of disease.
Subtle – hard to detect and analysis
Total: 10263 nsSNPs 731 Proteins
Structure: 3219 231
Non-disease Mutations (Inter-species Single base differences):
Total: 16,946 ‘nsSNPs’ 348 Proteins
Structure: 3,621 188
Independent: 1,866 135
Monogenic disease mutations (From HGMD):
Structure Modeling
• High throughput
• >40% sequence ID
• Fixed backbone
• Graph based search for side chain arrangements
• Identify unreliable regions
Retinol (Vitamin A) Binding Protein Missense Mutation: Gly-75 to Asp-75
Disease: Vitamin A Deficiency
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
S-S13
Bch
arge
8 Ove
rpac
king
5 BPola
r5
Bbstra
in
4 Pola
r-cha
rge
3 hy
drop
hobi
c
3 EsR
epul
sion
3 Cha
rge-
char
ge2
Cavity
1 Pola
r-pola
r
0.5
HighB
0.3
surfa
ce
Non-deleterious DatasetDisease Dataset
0
0.05
0.1
0.15
0.2
0.25
BCharge+
Overp
acking
EsRepulsi
on+Overp
acking
BPolar+
Overp
acking
Overp
acking+LowB
Charge-p
olar+
Buried
BbStrain+lowB
Cavity+
hydro
phobic
Charge-c
arge+Burie
d
Polar-polar+
Buried
Disease dataset Non-deleterious Dataset
Punfold = e ∆G/kT
∆G = -10 Kcal/mol, Punfold = 2.10-9
∆G = - 8 Kcal/mol, Punfold = 1.10-7
Protein Stability and Unfolding
Relationship of Experimental Total PAH Enzyme Activity (%) and the Protein Level (%)
0
20
40
60
80
100
0 20 40 60 80 100
Total PAH enzyme activity (%)
PAH
imm
uno-
reac
tive
pro
tein
(%
)
Our results:
20 mutants blue affect stability 4 mutants magenta affect binding and stability 2 mutants red affect binding only 2 mutants green have no effect
The Structure of a TCR Heterodimer
Framework Region (FR)
Four hypervariable regions in V-domain:
Complementarity-Determining Region(CDR), CDR1, CDR2 and CDR3 for
pMHC binding
The Fourth Hypervariable Region (HV4) with CDR1, CDR2 of Vβ for
superantigen binding
Effect of Missense SNPs in the Framework Regions (FR) of TCR Vβs
Total 42 in FR
35 no effect7 affect stability
Cys-111 to Arg-111Arg-63 to Gln-63Arg-55 to Gln-55
Asp-105 to Tyr-105Thr-105 to Ala-105
Gly-35 to Val-35Gly-35 to Arg-35
CDR1 CDR2 HV4