Blueprint for NACST/Sim Blueprint for NACST/Sim

2002.10.25신수용

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Main conceptMain concept

Implementing Hybridization first. Then, ligation, PCR, and so on..

Can be implemented easily based on hybridization concept.

그외 .. Gel electrophoresis is easy. Bead seperation 은 아직 고려하지 않음

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Main conceptMain concept

Probabilistic model!

Sequence Collision Probability Tube 에서 sequence 들이 어떻게 분포하고 있으

며 , 어떤 sequence 들이 서로 만날 것인가에 대한 모델

Sequence Hybridization Probability 서로 만난 sequence 들의 결합가능성 판단

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Collision modelCollision model

Based on Artificial Chemistry Artificial Chemistries: A Review, P. Dittrich, J. Ziegl

er, and W. Banzhaf Multi-Agent Systems inspired by Artificial Chemistri

es: A Case Study in Automated Theorem Proving, J. Bush and W. Banzhaf

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Collision model (AC)Collision model (AC)

현재의 DNAC 를 위해서는 초기에 입력은 전부 주어지며 , 출력도 없는 단순한 모델로 충분 .

Sequence 들은 uniform distribution 에 근거하여 확률적으로 선택됨

Hybridization 이 되어 긴 sequence 가 새로 생기면 추가적인 input 으로 가정

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Hybridization modelHybridization model

Based on Sequence Alignment Algorithms Dynamic Programming!

Smith-Waterman Algorithm(?) 좀 더 빠른 알고리즘을 원함 .! 독일에서 만든 알고리즘은 시퀀스 2 개 주고

결과를 얻기 위해서는 대략 5-9 초 정도의 시간이 필요 .

DNASIM: 1998, Jens Niehaus

Blast 도 동일한 알고리즘을 사용

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Hybridization model (DP)Hybridization model (DP)

Biological sequence analysis: Probabilistic models of proteins and nucleic acids, R. Dublin, S. R. Eddy, A. Krogh, and G. Mitchison

Introduction to Algorithms, T. H. Cormen, C. E. Leiserson, and R. L. Rivest

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Hybridization model (DP)Hybridization model (DP)

Sequence matching table(?) 이 중요 .

Free enery A T G C -A X O X X XT O X X X XG X X X O XC X X O X X- X X X X X

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor model for Nearest-neighbor model for TmTm

)4/|ln(| Tm CRS

HT

R : Boltzmann’s constant (1.987 cal/(K mol))[C]] : total molar strand concentrationT : Kelvin

3.269][7.01

][log6.16

)4/|ln(| 10

Na

Na

CRS

HT

Tm

[Na+] concentrations different from 1M

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor model for Nearest-neighbor model for TmTm

}{

}{

stackskkinitends

stackskkinitends

SSSS

HHHH

• Self-complement : [CT]/4 [CT]/2• The strands are not in equimolar concentration, but one strand is present in gross excess over the other : [CT]/4 [CT]• mismatched base pairs : “virtual stacks” (see references)

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: Perfect WC basepairing: Perfect WC basepairing

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

ExampleExample

GCTAGC at 0.1mM

H = 2(-11.1) + 2(-6.1) + (-6.3) = -40.7 kcal/molS = 2(-28.4) + 2(-16.1) + (-18.5) – 5.9 –1.4 = -114.8eu

CK

molKcalmolKcal

molcalTm

6.328.305

)10ln() /(998.1) /(8.114

/407004

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: GT mismatch: GT mismatch Thermodynamics and NMR of Internal G.T Mis

matches in DNA, H. T. Allawi and J. SantaLucia, Jr., Biochemistry 1997, 36, 10581-10594

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: GT mismatch: GT mismatch

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: GA mismatch: GA mismatch Nearest Neighbor Thermodynamic Parameters

for Internal GA Mismatches in DNA, H. T. Allawi, J. SantaLucia, Jr., Biochemistry 1998, 37, 2170-2179

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: GA mismatch: GA mismatch

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: CT mismatch: CT mismatch Thermodynamics of internal CT mismatches in

DNA, H. T. Allawi and J. SantaLucia, Jr., Nucleic Acids Research, 1998, 26(11): 2694-2701

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: CT mismatch: CT mismatch

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: AC mismatch: AC mismatch Nearest-Neighbor Thermodynamics of Internal

AC Mismatches in DNA: Sequence Dependence and pH Effects, H. T. Allawi and J. SantaLucia, Jr., Biochemistry, 1998, 37, 9435-9444

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: AC mismatch: AC mismatch

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: AA, CC, GG, and TT : AA, CC, GG, and TT mismatchmismatch Nearest-Neighbor Thermodynamics and NMR

of DNA sequences with Internal AA, CC, GG, and TT Mismatches, N. Peyret, P. A. Senevirante, H. T. Allawi, and J. SantaLucia, Jr., Biochemistry 1999, 38, 3468-3477

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: AA, CC, GG, and TT : AA, CC, GG, and TT mismatchmismatch

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: Single base bulge: Single base bulge The Effect of Base Sequence on the Stability o

f RNA and DNA Single Base Bulges, J. Zhu and R. M. Wartell, Biochemistry 1999, 38, 15986-15993

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: Single base bulge: Single base bulge

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: Hairpin: Hairpin Melting Studies of Short DNA Hairpins: Influen

ce of Loop Sequence and Adjoining Base Pair Identity on Hairpin Thermodynamic Stability, P. M. Vallone, T. M. Paner, and J. Hilario, M. J. Lane, B. D. Faldasz, and A. S. Benight, Biopolymers, 50, 425-442 (1999)

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: Dangling ends: Dangling ends Thermodynamic parameters for DNA sequence

s with dangling ends, S. Bommarito, N. Peyret, and J. SantaLucia, Jr., Nucleic Acids Research, 2000, 28(9): 1929-1934

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

Nearest-neighbor dataNearest-neighbor data: Dangling ends: Dangling ends

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

EtcEtc

Ionic condition… Differences between DNA Base Pair Stacking Energ

ies Are Conserved over a Wide Range of Ionic Conditions, T. Johnson, J, Zhu, and R. M. Wartell, Biochemistry 1998, 37, 12343-12350

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

For implementationFor implementation

We need to know HOW MANY MOLECULES ARE NECESSARY? HOW MUCH TIME IS NECESSARY?

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

HOW MANY MOLECULES ARE HOW MANY MOLECULES ARE NECESSARY? (V) NECESSARY? (V) i.e. v1, v2, v3, v4, e1, e2, e3

e1 : v1->v2, e2 : v2->v3, e3 : v3->v4

1. v1, v2, e1 -> p1

2. p1, v3, e2 -> p2

3)(

1

)()()( EVEVEVEV NNNNV

V

NNV

V

NNV

V

3

2

)2)((2)(2)(2)(

1

EVEVEVEV NNV

V

NNV

V

NNV

V

NNV

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

HOW MANY MOLECULES ARE HOW MANY MOLECULES ARE NECESSARY? (V)NECESSARY? (V)3. p2, v4, e3 -> p3

3

2

)4)((4)(4)(4)(

1

EVEVEVEV NNV

V

NNV

V

NNV

V

NNV

…

0)2)(()(

1 1

1

2

3

EN

i EVEV iNNV

V

NNP

적정한 양 ?

© 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

HOW MUCH TIME IS HOW MUCH TIME IS NECESSARY? (x)NECESSARY? (x)

0)2)(()(

1 1

1

2

3

EN

i EVEV ixNNV

V

NNP