QSAR-2.ppt

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Quantitative Structure-

Activity Relationships

(QSAR)

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Rationale for QSAR Studies

In drug design, in vitro potency addresses only part

of the need; a successful drug must also be able to

reach its target in the body hile still in its activeform!

"he in vivo activity of a substance is a composite of

many factors, including the intrinsic reactivity of

the drug, its solubility in ater, its ability to pass theblood-brain barrier, its non- reactivity ith non-

target molecules that it encounters on its ay to the

target, and others!

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Rationale for QSAR Studies!!!

A #uantitative structure-activity relationship (QSAR)

correlates measurable or calculable physical or

molecular properties to some specific biologicalactivity in terms of an e#uation!

$nce a valid QSAR has been determined, it should be

possible to predict the biological activity of related

drug candidates before they are put throughe%pensive and time-consuming biological testing! In

some cases, only computed values need to be &non

to ma&e an assessment!

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'istory of QSAR

"he first application of QSAR is attributed to 'ansch

(*), ho developed an e#uation that related

biological activity to certain electronic characteristics

and the hydrophobicity of a set of structures!

log (+) & log . - & /(log .)/ 0 & 1σ 0 & 2

for3 minimum effective dose

. octanol - ater partition coefficientσ 'ammett substituent constant

& % constants derived from regression analysis

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'ansch4s Approach

5og . is a measure of the drug4s hydrophobicity,

hich as selected as a measure of its ability to

pass through cell membranes! "he log . (or log .o+) value reflects the relative

solubility of the drug in octanol (representing the

lipid bilayer of a cell membrane) and ater (the

fluid ithin the cell and in blood)!

5og . values may be measured e%perimentally

or, more commonly, calculated!

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alculating 5og .

5og . 5og 6 (o+) 5og (789octanol+789ater)

most programs use a group additivity approach3

Aromatic ring :!<:

'4s on arbon !=<

->r bond -:!/:

al&yl :!= Sum /!/2 calc! log .

some use more complicated algorithms, includingfactors such as the dipole moment, molecular si?eand shape!

'/ >r

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'ansch4s Approach!!!

"he 'ammett substituent constant (σ) reflects the

drug molecule4s intrinsic reactivity, related to

electronic factors caused by aryl substituents! In chemical reactions, aromatic ring substituents

can alter the rate of reaction by up to * orders of

magnitude@

or e%ample, the rate of the reaction belo is B:=

times sloer hen 8 C$/ than hen 8 '1

'1$' l

'

8

φ

$'1 0 'l

'

φ

8

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'ammett D#uation

'ammett observed a linear free energy

relationship beteen the log of the relative rate

constants for ester hydrolysis and the log of therelative acid ioni?ation (e#uilibrium) constants

for a series of substituted ben?oic esters E acids!

log (& %+& ') log (6 %+6 ') ρσ

'e arbitrarily assigned ρ, the reaction constant,

of the acid ioni?ation of ben?oic acid a value of !

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Fefinition of 'ammettρ

C

O

OH

X

C

O

O

X

+ H

"heseσp values are obtained from the best fit line having a slope

Hammett Plot

y = 0.9992x - 4.5305

R2 = 0.9907

-5.3

-5.1

-4.9

-4.7

-4.5

-4.3

-4.1

-3.9

-3.7

-1 -0.5 0 0.5 1

sigma p

L o

g K

substituentσp Eq. constant log K

-NH2 -0.66 0.00000554 -5.25649

-OCH3 -0.27 0.000015 -4.82391

-CH3 -0.17 0.000023 -4.63827

-H 0.00 0.000034 -4.46852 -Cl 0.23 0.000055 -4.25964

-COCH3 0.5 0.000088 -4.05552

-CN 0.66 0.000128 -3.89279

-NO2 0.78 0.000166 -3.77989

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'ammett Rho E Sigma Galues

Substituent (Sigma) Galues σ

(the electronic effect of the substituent;

negative values are electron donating) p-C'/ -:!** p-l :!/1

p-$'1 -:!/ p-$'1 :!=:

p-'1 -:! p-C :!**

m-'1 -:!: p-C$/ :!<

Reaction (Rho) Galues ρ

'/$'1

$

'/$ 0 '1$'

$$'

ρ 0 /!2

8 8

'1$' l

'

8

φ

$'1 0 'l

'

φ

8ρ - =!:

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Holecular .roperties in QSAR

Hany other molecular properties have beenincorporated into QSAR studies; some of these

are measurable physical properties, such as3 density p6 a ioni?ation energy boiling point

'vapori?ation refractive inde%

molecular eight dipole moment (µ)

'hydration reduction potential

lipophilicity parameterπ

log .8 - log .'

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Holecular .roperties in QSAR

$ther molecular properties (descriptors) thathave been incorporated into QSAR studiesinclude calculated properties, such as3

ovality surface area, molec! volume '$H$ energy 5H$ energy polari?ability charges on individual atoms molecular volume solvent accessible surface area vdJ surface area ma%imum 0 and - charge molar refractivity hardness hydration energy "aft4s steric parameter

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QSAR Hethodology

$ften it is found that several descriptors are

correlated; that is, they describe observables that

are closely related, such as HJ and boiling point

in a homologous series!

Statistical analysis is used to determine hich of

the variables best describe (correlate ith) the

observed biological activity, and hich are cross-correlated! "he final QSAR involves only the most

important 1 to = descriptors, eliminating those

ith high cross-correlation!

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5imit to the K of Fescriptors

"he data set should contain at least = times asmany compounds as descriptors in the QSAR!

"he reason for this is that too fe compoundsrelative to the number of descriptors ill give afalsely high correlation3 / points e%actly determine a line (/ comp4ds, / prop)

1 points e%actly determine a plane (etc!, etc!) A data set of drug candidates that is similar in

si?e to the number of descriptors ill give a high(and meaningless) correlation!

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Statistical Analysis of Fata

Hultiple linear regression analysis can be

accomplished using standard statistical softare,

typically incorporated into sophisticated (and

e%pensive) drug design softare pac&ages, such as

MSI’s Cerius2 (academic price, over L/:6)

An ine%pensive statistical analysis softare StatMost

(academic price, L1) or&s Must fine!

"o discover correlated variables and determine hich

descriptors correlate best, a partial least s#uares or

principal component analysis is done!

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D%ample of a QSAR

X

Y

NCH3

CH3Br

Anti-adrenergic Activity and .hysicochemical .roperties

of 3,4- disubstituted C,C-dimethyl-α

-bromophenethylamines

π = Lipophilicity parameter

σ+ = Hammett Sigma+ (for benzylic cation!

"(meta! = #aft$ teric parameter

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D%ample of a QSAR!!!m-X p-Y π σ+ Es(meta) log (1/C)obs log (1/C)a log (1/C)b

H H 0.00 0.00 1.24 7.46 7.82 7.88

F H 0.13 0.35 0.78 7.52 7.45 7.43

H F 0.15 -0.07 1.24 8.16 8.09 8.17

Cl H 0.76 0.40 0.27 8.16 8.11 8.05

Cl F 0.91 0.33 0.27 8.19 8.38 8.34

Br H 0.94 0.41 0.08 8.30 8.30 8.22

I H 1.15 0.36 -0.16 8.40 8.61 8.51

Me H 0.51 -0.07 0.00 8.46 8.51 8.36

Br F 1.09 0.34 0.08 8.57 8.57 8.51

H Cl 0.70 0.11 1.24 8.68 8.46 8.60

Me F 0.66 -0.14 0.00 8.82 8.78 8.65

H Br 1.02 0.15 1.24 8.89 8.77 8.94

Cl Cl 1.46 0.51 0.27 8.89 8.75 8.77

Br Cl 1.64 0.52 0.08 8.92 8.94 8.94

Me Cl 1.21 0.04 0.00 8.96 9.15 9.08

Cl Br 1.78 0.55 0.27 9.00 9.06 9.11

Me Br 1.53 0.08 0.00 9.22 9.46 9.43

H I 1.26 0.14 1.24 9.25 9.06 9.26H Me 0.52 -0.31 1.24 9.30 8.87 8.98

Me Me 1.03 -0.38 0.00 9.30 9.56 9.47

Br Br 1.96 0.56 0.08 9.35 9.25 9.29

Br Me 1.46 0.10 0.08 9.52 9.35 9.33

Calc.Calc.

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D%ample of a QSAR!!!

QSAR D#uation a3 (using / variables)

log (+) != π - !2*2 σ

0 0 !<

(n //; r :!2=)

QSAR D#uation b3 (using 1 variables)

log (+) !/=π

- !2*:σ

0 0 :!/:< Ds(meta) 0 !*(n //; r :!=)

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D%ample of a QSAR!!!m-X p-Y π σ+ Es(meta) log (1/C)obs log (1/C)a log (1/C)b

H H 0.00 0.00 1.24 7.46 7.82 7.88

F H 0.13 0.35 0.78 7.52 7.45 7.43

H F 0.15 -0.07 1.24 8.16 8.09 8.17

Cl H 0.76 0.40 0.27 8.16 8.11 8.05

Cl F 0.91 0.33 0.27 8.19 8.38 8.34

Br H 0.94 0.41 0.08 8.30 8.30 8.22

I H 1.15 0.36 -0.16 8.40 8.61 8.51

Me H 0.51 -0.07 0.00 8.46 8.51 8.36

Br F 1.09 0.34 0.08 8.57 8.57 8.51

H Cl 0.70 0.11 1.24 8.68 8.46 8.60

Me F 0.66 -0.14 0.00 8.82 8.78 8.65

H Br 1.02 0.15 1.24 8.89 8.77 8.94

Cl Cl 1.46 0.51 0.27 8.89 8.75 8.77

Br Cl 1.64 0.52 0.08 8.92 8.94 8.94

Me Cl 1.21 0.04 0.00 8.96 9.15 9.08

Cl Br 1.78 0.55 0.27 9.00 9.06 9.11

Me Br 1.53 0.08 0.00 9.22 9.46 9.43

H I 1.26 0.14 1.24 9.25 9.06 9.26H Me 0.52 -0.31 1.24 9.30 8.87 8.98

Me Me 1.03 -0.38 0.00 9.30 9.56 9.47

Br Br 1.96 0.56 0.08 9.35 9.25 9.29

Br Me 1.46 0.10 0.08 9.52 9.35 9.33

Calc.Calc.

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QSAR of Antifungal Ceolignans

"he .H1 semi-empirical method as employed tocalculate a set of molecular properties (descriptors) of< neolignan compounds ith activities against

Epidermophyton floccosum, a most susceptible speciesof dermophytes! "he correlation beteen biologicalactivity and structural properties as obtained byusing the multiple linear regression method! "he QSARshoed not only statistical significance but alsopredictive ability! "he significant molecular descriptors

related to the compounds ith antifungal activity ere3hydration energy ('D) and the charge on N carbonatom (QN)! "he model obtained as applied to a set of: ne compounds derived from neolignans; five ofthem presented promising biological activities against

E floccosum!

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Ceolignans

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"o Host Important Fescriptors

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Antifungal QSAR

5og +C -/!<= - :!1< 'D - !2= QN

& /!*1, '/:!<*, Q/:!<:, SD.:!

here3

& is the isher test for significance of the e#4n!

'/ is the general correlation coefficient,Q/ is the predictive capability, and

SD. is the standard error of prediction!

A!A!! .inheiro, R!S! >orges, 5!S! Santos, !C! Alves,

Oournal of Holecular Structure3 "'D$'DH, Gol */, pp /=-/ (/::2)!

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QSAR-alculated Antifungal Activity

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Ce Ceolignans

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D%ample of a .harmacophore

/F 'ypothesis and Alignment

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1 Fimensional QSAR Hethods

Important regions of bioactive molecules are

Pmapped in 1F space, such that regions of

hydrophobicity, hydrophilicity, '-bonding

acceptor, '-bond donor,π

-donor, etc! are rendered

so that they overlap, and a general 1F pattern of

the functionally significant regions of a drug are

determined!

oHA (omparative

Holecular ield Analysis)

is one such approach3

tetoterone

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oHA of "estosterone>lue means electronegative

groups enhance, red means

Dlectn4g! gr4ps reduce binding

reen means bul&y groups

enhance, yello means they

reduce binding

QSAR-2.ppt

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