BL5203 Molecular Recognition & Interaction

Section D: Molecular Modeling.

Chen Yu Zong

Department of Computational Science

National University of Singapore

Singapore 119260

Key Points

• Computer modeling of molecular recognition.

• Computer modeling of molecular interaction.

Molecular Surface:

Conformation change induced by a hinge motion

Molecular Surface:

Mechanism of Ligand Binding:

Molecular surface and substrate binding:

Mechanism of Substrate Binding:

Molecular surface and substrate binding:

DNA-protein complex

Computer Modeling of Molecular Surface

Molecular surface:

a smooth three-dimensional contour about a molecule can be generated by rolling probing spheres on the surface atom represented by a group of spheres of Van der Waals radii.

From Surface Profile to Cavity Recognition

EstrogenReceptor

Representation of a Cavity

HIV-1 Protease

.Modeling of molecular binding:

Ligand-protein docking

.Modeling of molecular binding:

Ligand-protein docking

.

.

Scoring Functions in Ligand-Protein Docking

Potential Energy Description:

Scoring Functions in Ligand-Protein Docking

Potential Energy Description:

Energy Functions inMolecular Mechanics

• Potential Energy Description:

– Torsion (bond rotation)– Hydrogen bonding– van der Waals interactions– Electrostatic interactions– Empirical solvation free energy

V = torsions 1/2 Vn [ 1 + cos(n-') ] +

H bonds [ V0 (1-e-a(r-r0) )2 - V0 ] +

non bonded [ Aij/rij12 - Bij/rij

6 + qiqj /r rij] +

atoms i i Ai

Applications of Ligand-Protein Docking in Drug Design

Existing M ethods:G iven a Protein,

F ind Potentia l B inding L iga ndsFrom a C hem ica l D a ta ba se

S uccess ful ly D ocked C om poundsas Puta tive L igands

Protein

C om pound D a ta ba seC om pound 1

...C om pound n

N ew M ethod:G iven a L iga nd,

F ind Potentia l P rotein T a rgetsFrom a Protein D a ta ba se

S uccess ful ly D ocked Prote insas Puta tive T arge ts

Liga nd

Protein D a ta ba seProte in 1

...Prote in n

Science 1992;257: 1078 Proteins 2001;43:217

Example 1: Study of Drug Resistant Mutations by Ligand-Protein Docking

Enzyme-inhibitor PDB IdEnzyme-inhibitor PDB Id Mutation introduced Mutation introduced

HIV-1 protease + MK 639 1HSG V82A, V82F, V82I, I84V, V82f/I84V, M46I/L63P,

V82T/I84V, M46I/L63P/V82T/I84V

HIV-1 protease + Saquinavir 1HXB V82F, V82I, I84V, G48V, V82F/I84V, V82T/I84V

HIV-1 protease + SB 203386 1SBG I32V/V47I/I82V

HIV-1 protease + VX 478 1HPV M46I/L63P, V82T/I84V, M46I/L63P/V82T/I84V

HIV-1 protease + U89360e 1GNO V82D, V82N, V82Q, D30F

HIV-1 RT + Nevirapine 1VRT L100I, K103N, V106A, E138K, Y181C, Y188H

HIV-1 RT + TIBO R82913 1TVR L100I, K103N, V106A, E138K, Y181C, Y188H

J. Mol. Graph. Mod. 19, 560-570 (2001).

Quality of Modelled Structures

Wild type X-ray structure: Blue

Modelled mutant: Red

Mutant X-ray structure: Green

Mutation induced energy change compared with observed drug resistance data

MK 639 VX 478 U89360e Saquinavir SB 203386

-8

-3

2

7

12

17

22

I84V

V82

A

V82

F

V82

I

V82

F/I8

4V

V82

T/I8

4V

M46

I/L63

P/V

82T/

I84V

V82

T/I8

4V

M46

I/L63

P/V

82T/

I84V V82

D

V82

N

V82

Q

D30

F

I84V

V82

F

V82

I

V82

F/I8

4V

V82

T/I8

4V

G48

V

I32V

/V47

I/V82

I

ln (Ki'/Ki) E (kcal/mol)

Figure 3: Line plot of binding energy change and ln(Ki'/Ki) between wild type and mutant HIV protease and inhibitors (Roberts et al, 1998; Klabe et al, 1998; Schock et al, 1996)

Mutations

E o

r ln(

Ki'/

Ki)

J. Bio. Chem.271, 31947 (1996)AIDS 12: 453 (1998)Biochemistry 37, 8735 (1998)

Example 2: Prediction of toxicity, side effect, pharmacokinetics and pharmacogenetics

by a receptor-based approach

Annu. Rev. Pharmacol Toxicol 2000, 40:353-3881997, 37:269-296

Pharmacological Rev. 2000, 52:207-236

Importance of prediction of side effect, toxicity, pharmacokinetics in early stages of drug discovery

• Most drug candidates fail to reach market

• Pharmacokinetics (60%), side-effect and toxicity (40%) are the main reason.

• Large portion of money (USD$350 million) and time (6-12 years) spent on a clinical drug has been wasted on failed drugs.

Drug Discov Today 1997; 2:72 Drug Candidates Drug Candidates

in Different Stages of Developmentin Different Stages of DevelopmentMajority of Majority of CandidatesCandidates Fail to Reach Fail to Reach

MarketMarketClin Pharmacol Ther. 1991; 50:471Clin Pharmacol Ther. 1991; 50:471

INVDOCK Testing on Toxicity TargetsCompound Number of

experimentally confirmed or implicated toxicity targets

Number of toxicity targets predicted by INVDOCK

Number of toxicity targets missed by INVDOCK

Number of toxicity targets without 3D structure or involving covalent bond

Number of INVDOCK predicted toxicity targets without experimental findingAspirin 15 9 2 4 2

Gentamicin

17 5 2 10 2

Ibuprofen 5 3 0 2 2

Indinavir 6 4 0 2 2

Neomycin 14 7 1 6 6

Penicillin G

7 6 0 1 8

Tamoxifen 2 2 0 0 4

Vitamin C 2 2 0 0 3

Total 68 38 5 25 29

J. Mol. Graph. Mod., 20, 199-218 (2001).

Toxicity and side effect targets of Aspirin identified from INVDOCK search of protein database

PDB ProteinExperimental

FindingTarget Status

Toxicity/Side Effect

Ref

1a42 Carbonic anhydrase II Activate enzyme activity that may lead to increase in plasma bicarbonate concentration.

Implicated Metabolic alkalosis (hypoventilation).

Puscas I

1a6a HLA-DR3 Change in HLA level

Implicated Aspirin-induced asthma

Dekker JW

1a7c Plasminogen activator inhibitor

Tissue-dependent response of protein.

Implicated Hypertension, thrombolysis

Smokovitis A

1d6n Hypoxanthine-guanine phosphoribosyltransferase

    Excess uric acid in serum*

 

1hdy Alcohol dehydrogenase Inhibition of activity

Confirmed Increased blood alcohol level

Gentry RT

J. Mol. Graph. Mod., 20, 199-218 (2001).