Single Nucleotide Polymorphism (SNP) ACTCGAGCTA ACTCGCGCTA

Single Nucleotide Polymorphism (SNP)

ACTCGAGCTA

ACTCGCGCTA

TYPE EXAMPLE EFFECT

Neutral Non-coding, non-regulatory, synonymous

No effect

…

TYPE EXAMPLE EFFECT


No effect

Individual characteristics

Big Nose… Mating success

TYPE EXAMPLE EFFECT


No effect



Drug Efficacy Cytochrome P450 Disease treatment

TYPE EXAMPLE EFFECT


No effect




Multi-factorial, complex trait, poly-genic late disease

APOE, FAS1,…. Alzheimer

Multi-factorial early disease

?,?,?

Asthma

TYPE EXAMPLE EFFECT


No effect







?,?,?

Asthma

Single factor, mono-genic disease (‘mild’)

Sickle cell hemoglobin

Anemia

Single factor disease (severe)

Cu transporter Early death

TYPE EXAMPLE EFFECT


No effect







?,?,?

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

Aldehyde Dehydrogenase 10

Missense Mutation: Leu-106 to Arg-106

Disease: Sjogren-Larsson Syndrome

Distribution of the Effects of Missense cSNPs on

Protein Molecular Function for the SNP-Disease Set

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

Steady State Abundance

d[P]/dt = 0 = C – k1.[P] – k2.[P]e-∆G/kT

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

Jung & Ley 1999, Journal of Immunology

http://www.SNPS3D.org

Zhen Wang Peng Yue Eugene Melamud

Documents

Single Nucleotide Polymorphism (SNP) ACTCGAGCTA ACTCGCGCTA