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電腦輔助藥物設計簡介新穎的藥物設計方法

國立清華大學生命科學系 林志侯

Drug design choose

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2D QSAR

1868, Crum-Brown, Fraser,

1960, Hansch model ( property-property relationship)

Free-Wilson model (structure-property relationship)

1. QSAR

)(Cf=Φ

kcMRbPaC

++++= .....log1

log σ

∑ += µiaC1log

1979, DYLOMMS (dynamic lattice oriented molecular modeling system) –regular grid, small molecules

1981, Molecular shape analysis (MSA)

1985, GRID – determining energetically favorable binding sites on macromolecules

1985, DG (distance geometry)

1988, CoMFA(comparative molecular field analysis)

1994, CoMSIA(comparative molecular similarity index analysis)

1995, Receptor surface model

1996, CoMMA(comparative molecular moment analysis)

1997, 4D QSAR2002, 5D QSAR

3D QSAR

3

MSA

1980 HopfingerConformation analysis + Hansch model

Activity knowing

Conformation parameter

http://bioinf.bmi.ac.cn/ebooks/bioinf/msi/cerius38/qsar/desc_msa.doc.html#335813

Activity ↔Ligand shape accommodate to binding site

DG

1. 3D structure development and use Z-matrix (or xyz matrix)present.

2. Use steric dots(matrix for the relative site) to displace the same character groups.

3. Design a binding model. Eicalc4. Use DG matrix to find the real

binding site. Eiobs

5 Compare 3&4

2

1)( icalc

N

i

iobs EE −=∆ ∑

=

ActivityActivity↔↔ Binding energyBinding energy

4

CoMFA

http://www.chem.swin.edu.au/modules/mod4/qsarwebp11.html

rr2 2 s F qs F q22rr2 2 s F qs F q22

Biological Activity

wwwcmc.pharm.uu.nl/moret/phd/ thesis/appendixII3.gif

ActivityActivity == aStericSteric+ bElecElectrictric

∑=

⎥⎦⎤

⎢⎣⎡=

Natoms

i ijij

jiC

RDQQE

1∑=

⎥⎦⎤

⎢⎣⎡=

Natoms

i ijij

jiC

RDQQE

1∑= ⎥

⎥⎦

⎤

⎢⎢⎣

⎡−=

Natoms

i ij

ij

ij

ijvdw R

BRAE

1612∑

= ⎥⎥⎦

⎤

⎢⎢⎣

⎡−=

Natoms

i ij

ij

ij

ijvdw R

BRAE

1612

5

4D & 5D QSAR

http:\\mod.life.nthu.edu.tw/bioinfo2/drugdesign/receptor/snap7.jpg

Drug-Receptor theories

Key and Lock Induced-fit

3D QSAR 4D & 5D QSAR

2. De Novo drug Design

Random connectionMethod (RC)

Sequential build-upMethod (SB)

Fragment connectionMethod (FC)

Site point connection Method (SP)

Whole molecule Method (WM)

Connection method

Active site analysis

Method (ASA)

6

www.life.nthu.edu.tw/~lslpc/SBDD/SBBD03.jpg

(SP)

(WM)

(FC)

(SB)

1

2 3 4

http://thalassa.ca.sandia.gov/~dcroe/builder.html

1

2

3

4

5

6

7

7

3. Database

Approaches to Virtual Screening

Type Task / Required Information Throughputmols/ hr/ CPU

1D Data cleaning, junk removal,property and bioavailabilityscreening, diversity selectionKnowledge about drugs in general

105 - 106

2D 2D pharmacophore screening,screening based on the activesubstructuresSet of active molecules

104 – 105

3D Virtual dockingInformation about the 3Dstructure of target

101 – 102

http://www.documentarea.com/qsar/peterertl.ppt

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何智雄SAMDL

何智雄chemdbCRYSTMET

何智雄SAICSD

何智雄SAISOSTAR

何智雄SACSD

謝昌煥SAGCG

謝昌煥SAPDB

何智雄SATripos/DBunity

何智雄xfireCrossFire

何智雄SASpecInfo

ContactAvailable PlatformPackage1.Geometric search2.Steric search3.Flexible conformation search 4.Similarity search

Search type

分子結構資料庫：acdfind.db：化合物商業來源資料庫mddr3d.db︰藥用化合物資料庫cmc3d.db：藥用化合物資料庫nci3d.db：美國癌症研究院分子結構資料庫nciaids.db：美國癌症研究院抗癌和抗愛滋病分子結構資料庫csd2d.db：英國劍橋晶體結構資料庫isismx.db：學習用分子結構資料庫化學反應資料庫：JSM，CHC，Orgsyn，Reflib，SPORE，CIRX92，CIRX93，CIRX94，CIRX95，CIRX96，CIRX97，CIRX98，CIRX99，CIRX00，CIRX01，CIRX02

Fragment-based Virtual Screening

linear fragments

substituents (Rgroups)

atoms with environment(HOSE codes)

rings

scaffolds

Inactive MoleculesActive Molecules

Statistical analysis of fragment frequencies in both sets and calculation of fragment “activity contributions”.

List of fragments List of fragments

http://www.documentarea.com/qsar/peterertl.ppt

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High through put screening

mod.life.nthu.edu.tw\bioinfo2\drugdesign\VS.htm

Docking method

∑ ∑ ∑+−=i R R GR

R

GR

RiGLR r

braqQE 126

Dock 5.0 manual

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Molecular surface calculation

H

H

O

H

Vdwsurface

Solvent accessible surface

Connolly surface

Probe

http://scsg9.unige.ch/fln/eng/partie1b.html

Rigid docking Geometric Hashing

(force fields)

Geometric

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Flexible Docking (soft docking)

1.Conformation Ensembles

2.Genetic algorithms (GA)GOLD (Genetic Optimisation for Ligand Docking)AutoDock (Simulate annealing + GA)

3.FragmentationFlexX

4.Simulationligand flexiblereceptor flexibleligand & receptor flexibleDock 5.0

Summary

mod.life.nthu.edu.tw/bioinfo2/drugdesign/fig/snap3.jpg

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Summary

CADD can help us to define lead discovery.

CADD can decrease R&D time and money.

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