Biological CorrelationsâThe Hansch Approach

11 Structure-Activity Relationships in Antifungal Agents: A Survey Downloaded by UNIV OF CALIFORNIA SAN DIEGO on March 7, 2016 | http://pubs.acs.org Publication Date: August 1, 1974 | doi: 10.1021/ba-1972-0114.ch011

ERIC J. LIEN School of Pharmacy, University of Southern California, Los Angeles, Calif. 90007 CORWIN HANSCH Department of Chemistry, Pomona College, Claremont, Calif. 91711

Using computerized regression analysis, a generalized equa tion and a few of its simplified forms can be used to correlate the antifungal activity of more than 560 compounds with their chemical structures. The general equation is: log activity = parabolic function of log Ρ + k (electronic) + k' (steric) + k" Hydrophobic character as measured by the octanol/water partition coefficient (log P or π) and electronic effects of substituents as measured by Hammett's σ constant appear to be the most important factors in determining the relative potency of congeneric members of drugs while the intrinsic activity is governed by the functional group(s) of the mole cules. The correlations obtained should serve as useful guidelines for predicting the design of more specific new antifungal agents.

m o n g the 70,000 k n o w n species of f u n g i m a n y are parasitic to a n i m a l s a n d plants. F u r t h e r m o r e , u n d e r p r o p e r c o n d i t i o n s almost a n y m a t e r i a l is o p e n to f u n g a l attack i f not a d e q u a t e l y p r o t e c t e d b y a f u n g i c i d e . It is not s u r p r i s i n g , t h e n , that thousands of c o m p o u n d s are s y n t h e s i z e d a n d tested each year for a n t i f u n g a l a c t i v i t y . A n u m b e r of a n t i f u n g a l agents have thus b e c o m e c o m m e r c i a l l y a v a i l a b l e for v a r i o u s purposes (1-3). 155

Van Valkenburg; Biological Correlations—The Hansch Approach Advances in Chemistry; American Chemical Society: Washington, DC, 1974.

156

BIOLOGICAL CORRELATIONS

Table l a .

Equations Correlating Antifungal

log A c t i v i t y = ki l o g Ρ + Organism

Type of

T H E HANSCH A P P R O A C H

k

2

Action

Compound

Units of Activity

Η

Downloaded by UNIV OF CALIFORNIA SAN DIEGO on March 7, 2016 | http://pubs.acs.org Publication Date: August 1, 1974 | doi: 10.1021/ba-1972-0114.ch011

S.

inh.

sarciîiaeforme spores

Ϊ

I/ED50

μΜ/cm

2

CH S.

sarcinaeforme

inh.

N - R

I

0=N

I/ED50

μΜ/cm

2

NH CH

V.

inaequales spores

3

RNH—C—NH

2

inh.

% inh. germination

inh.

pC

inh.

pC

inh.

pC

inh

pC

inh.

pC

Ri

T.

mentagrophytes OCH

M.

3

verrucaria

C.

albicans

HOC H COOR

T.

mentagrophytes

R RN(CH ) N(CH )

C.

albicans

RiR N(CH ) N(CH )

A.

niger

RCOO-

kill

pC

RCOO-

kill

pC

RCOO-

inh.

pC

XPh(CH ) NCS

inh.

pC

XPhCH NCS

inh.

pC

T. A. P. A.

interdigitale niger cyclopium niger

6

4

1

2

2

2

2

2

2

3

2

2

3

2

2


11.

L I E N A N D HANSCH

Antifungal

157

Agents

A c t i v i t y with Physicochemical Constants


ki

k

r

2

6

s

c

Equation

Ref.

3

0.99

0.24

1

4

6

3

0.99

0.30

2

4

d

5

0.94

0.16

3

4

0.90

12

0.95

0.16

4

4

0.79

0.93

9

0.93

0.15

5

4

0.70

0.95

7

0.97

0.21

6

8

0.53

1.37

22

0.89

0.50

7

8

0.34

1.74

19

0.86

0.40

8

8

0.67

2.08

8

0.97

0.18

9

8

0.76

2.43

14

0.99

0.13

10

8

0.55

2.66

10

0.96

0.21

11

8

0.46

2.79

6

0.97

0.06

12

8

0.55

3.28

13

0.90

0.15

13

8

0.51

-0.94

1.65

0.06

0.15

1.51

0.81

d


158



Table l a . log A c t i v i t y = k ι log Ρ + Organism


M.

k

2

Action

Φ*

kill

pC

Ο

fructicola

Units of Activity

Compound

Type of

Ο

A.

oleracea

kill

pC

C.

albicans

inh.

pC

XPhHN

Ν

NHPhX

Ο II

N.

•0>

crassa

-SCCI3

inh.

pC

Ο

"Footnotes for Tables l a , b, c are given in Table Id (p.

176).

I n spite of the tremendous a m o u n t of d a t a r e p o r t e d i n the l i t e r a t u r e , f e w g e n e r a l i z e d q u a n t i t a t i v e s t r u c t u r e - a c t i v i t y c o r r e l a t i o n studies been reported

(4-8);

have

that is, little i n v e s t i g a t i o n , u s i n g a g e n e r a l i z e d

m o d e l , into correlations b e t w e e n the drug's m o l e c u l a r structure a n d the resultant b i o l o g i c a l a c t i v i t y has been done.

W e n o w report that w i t h

the use of c o m p u t e r i z e d regression analysis, a g e n e r a l i z e d e q u a t i o n a n d a f e w of its s i m p l i f i e d forms c a n be u s e d to correlate the a n t i f u n g a l ac t i v i t y of m o r e t h a n 560 c o m p o u n d s

w i t h t h e i r c h e m i c a l structures.

The

correlations o b t a i n e d s h o u l d serve as guidelines for the design of

new

a n t i f u n g a l agents.


11.


Antifungal

159

Agents

Continued


ki

k

n°

2

r

s

6

d

Equation

Réf.

0.88

3.53

10

0.86

0.58

14

8

0.73

3.74

10

0.83

0.56

15

8

0.50

4.15

8

0.96

0.22

16

.8

0.55

4.37

7

0.92

0.21

17

7

e

Method T h e b i o l o g i c a l d a t a w e r e c o l l e c t e d f r o m a survey of the l i t e r a t u r e u p to D e c e m b e r 1970. A l t h o u g h a n enormous a m o u n t of w o r k has b e e n p u b l i s h e d , o n l y d a t a suitable f o r q u a n t i t a t i v e analysis c o u l d b e

con-

sidered. T h e p h y s i c o c h e m i c a l constants u s e d i n the s t u d y w e r e l o g F or 7Γ, w h e r e Ρ is the o c t a n o l / w a t e r p a r t i t i o n coefficient of the w h o l e m o l e c u l e a n d 7Γ is defined as: x = log P

x

-

log Ρ π


160 (P

X



is the p a r t i t i o n coefficient of a d e r i v a t i v e a n d P

is that for the p a r e n t

H

compound.)

A l s o u s e d w e r e H a m m e t t ' s σ constant, Taft's p o l a r

stant, σ*, a n d Taft's steric parameter, E . s

con

I n a f e w examples ( E q u a t i o n s

17, 21, 24, a n d 3 0 ) , F values f r o m o l e y l a l c o h o l / w a t e r have b e e n used. I n one instance ( E q u a t i o n 69) the c h e m i c a l shift of a p h e n o l i c p r o t o n has b e e n u s e d for c o m p a r i s o n w i t h the σ constant. e x p e r i m e n t a l l y m e a s u r e d p a r t i t i o n coefficients

W h e r e possible, the

for a l l m e m b e r s

of

the


series h a v e b e e n used. I n other instances o n l y one m e m b e r of a set has b e e n m e a s u r e d . V a l u e s for the other m e m b e r s w e r e o b t a i n e d b y t a k i n g a d v a n t a g e of the a d d i t i v i t y p r i n c i p l e s of l o g F a n d π. D e t a i l s are g i v e n elsewhere (4, 7, a n d 8 ) .

F o r the n e w w o r k of T a b l e I I , l o g F values for

the p a r e n t c o m p o u n d s are g i v e n i n the footnotes. T h e "best" equations are assembled i n T a b l e s l a , b , a n d c. H e r e w e h a v e g i v e n the equations w i t h the m a x i m u m n u m b e r of variables justified b y the F statistic w h e r e a ^

0.10.

s t u d i e d i n w h i c h o n l y p o o r correlations w e r e o b t a i n e d . i n c l u d e d these. (r =

independent

M a n y sets w e r e W e have

not

O u r s t a n d a r d for a g o o d c o r r e l a t i o n was set at r ^

0.9

c o r r e l a t i o n coefficient).

O n l y a f e w examples w i t h r s l i g h t l y b e l o w

0.9 h a v e b e e n i n c l u d e d . A t present w e are t r y i n g to establish a basic set of equations w i t h w h i c h others c a n be c o m p a r e d

in quantitative

studies. F o r p r a c t i c a l w o r k i n d e s i g n i n g n e w f u n g i c i d e s one w o u l d w a n t to use equations h a v i n g l o w e r correlations for g u i d a n c e to d e s i g n n e w derivatives for synthesis. I n T a b l e s l a , b , a n d c, η is the n u m b e r of d a t a points u s e d i n the least-squares fit of the d a t a a n d s is the s t a n d a r d de v i a t i o n f r o m the regression. tivity) / d log F =

Log P

0

was o b t a i n e d b y setting d ( l o g

ac

0 a n d s o l v i n g for l o g F . It represents the o p t i m u m

l i p o p h i l i c character for the g i v e n set of congeners. theses u n d e r this constant are the 9 5 % instances confidence

T h e figures i n p a r e n

confidence

intervals. I n some

intervals are m i s s i n g because it is not possible to

c a l c u l a t e t h e m . A n e x p l a n a t i o n of this c a l c u l a t i o n is g i v e n elsewhere W h e r e possible, a c t i v i t y has b e e n expressed as l o g 1 / C

(9).

(i.e., p C )

w h e r e C is the m o l a r c o n c e n t r a t i o n r e q u i r e d to cause a s t a n d a r d response ( s u c h as E D - , M I C , or L D i o o ) .

I n m a n y instances the intercepts of

these equations c a n be c o m p a r e d .

W h e r e a c t i v i t y is expressed i n other

) 0

units, s u c h comparisons are not possible. I n a f e w examples the r e l a t i v e v a l u e , F C , the m o l a r p h e n o l coefficient, has b e e n used. I n T a b l e s I l a - d n e w d a t a not p r e v i o u s l y c o r r e l a t e d are assembled. Results and Discussion I n T a b l e s l a a n d l b w e h a v e p l a c e d a l l equations w h i c h are corre l a t e d b y the single p a r a m e t e r , l o g F . E x c e p t for those equations i n w h i c h a c t i v i t y c o u l d not be defined b y p C (i.e., l o g 1 / C ) , a l l equations h a v e


11.

Antifungal


161

Agents

b e e n a r r a n g e d b y i n c r e a s i n g v a l u e of t h e intercept.

S i n c e a c t i v i t y for

these is defined as t h e r e c i p r o c a l of the m o l a r c o n c e n t r a t i o n of f u n g i c i d e ( 1 / C ) , the larger t h e v a l u e of the intercept, t h e greater the i n t r i n s i c a c t i v i t y of the p h a r m a c o p h o r i c f u n c t i o n of a g i v e n congeneric

set.

In

c o m p a r i n g the intercept of these equations w e are c o n s i d e r i n g t h e case where Ρ = compare

1 or log Ρ =

completely

0.

C o m p a r i n g intercepts thus a l l o w s one to

different sets of congeners a c t i n g o n


different b i o c h e m i c a l systems u n d e r the c o n d i t i o n w h e r e t h e h a v e the same l i p o p h i l i c character.

completely molecules

If c o m p a r i s o n of t w o or m o r e

sets

of congeners is b e i n g m a d e o n a n i d e n t i c a l test system ( s a m e o r g a n i s m , t e m p e r a t u r e , n u t r i e n t , a n d so f o r t h ) , t h e n differences

i n intercept c a n

b e t a k e n as differences i n w h a t m i g h t b e c a l l e d the i n t r i n s i c a c t i v i t y of the c o m m o n p h a r m a c o p h o r i c f u n c t i o n . S t a t e d another w a y , i f l o g F ac counts for differences i n a c t i v i t y caused b y t h e h y d r o p h o b i c

character

of the drugs ( a n d this is the o n l y v a r i a b l e i n our e q u a t i o n ) , t h e n other differences b e t w e e n sets are c o n t a i n e d i n the intercept.

A t o u r present

l e v e l of refinement i n e x t r a t h e r m o d y n a m i c correlations these m i g h t l u m p e d together u n d e r t h e c o m m o n nately, it turns out (10)

be

h e a d i n g stereoelectronic.

Fortu

that w h e n the o c t a n o l / w a t e r reference

system

is u s e d as a s t a n d a r d , the intercept for the most nonspecific k i n d s of b i o l o g i c a l response is 0.0 ± l o g P)

.5; t h a t is, equations

( i n the single v a r i a b l e

correlating simple protein denaturation, narcotic action on frog

hearts, narcosis of tadpoles, a n d the l i k e h a v e intercepts near zero.

This

holds o n l y for n e u t r a l molecules s u c h as alcohols, ketones, esters, a n d so f o r t h . I o n i c c o m p o u n d s s u c h as R C O O " a n d R N ( C H ) +

3

3

deviate f r o m

this greatly. It m u s t also be k e p t i n m i n d t h a t t h e v a l u e of the i n t e r c e p t depends o n the l e v e l of response; that is, the intercept for a n E D i o o w o u l d b e l o w e r t h a n that for a n E D

5 0

.

W e c a n c a u t i o u s l y b e g i n to use intercepts s u c h as those i n T a b l e s l a a n d l b to order v a r i o u s f u n c t i o n a l groups i n terms of t h e i r r e l a t i v e effects o n v a r i o u s b i o c h e m i c a l systems. T h e r e is a n a d v a n t a g e i n m a k i n g comparisons of molecules o n a n i s o l i p o p h i l i c basis e a r l y i n structure-ac t i v i t y studies, w h i c h c a n be i l l u s t r a t e d as follows.

O m i t t i n g t h e t w o ex

treme examples ( E q u a t i o n s 2 a n d 3, w h i c h are b a s e d o n little d a t a ) , the m e a n a n d s t a n d a r d d e v i a t i o n for the slopes of the other 15 cases i n T a b l e l a is 0.62 ±

0.15.

O n this basis, molecules i n different c o n g e n e r i c

sets

w h i c h differ b y 3 i n l o g Ρ values w o u l d h a v e differences i n a c t i v i t y of 1.86 l o g units, or 70-fold.

W h i l e this w o u l d i n d i c a t e g r e a t l y different

a c t i v i t y for the t w o isolated examples, i f the intercepts for the t w o e q u a tions c o r r e l a t i n g the S A R for the sets are the same, little i m p o r t a n c e is to be a t t a c h e d to the 70-fold difference i n a c t i v i t y . T h i s c a n b e a c h i e v e d for a n y m e m b e r s of the sets s i m p l y b y m a n i p u l a t i o n of the l o g Ρ values.


162

BIOLOGICAL

CORRELATIONS

Table l b . log A c t i v i t y = Organism


T.

Equations Correlating Antifungal

(log P )

-kx

Type of


2

+ k log Ρ +

Compound

rosaceum

2

k

s

Action

Units of Activity

inh.

PC

inh. Mycelia

mm/day

inh. Mycelia

mm/day

inh.

relative

inh.

PC

It A.

niger

with EDTA

OH R A.

niger

OH

0 II

A.

cV

tenuis

C

/

NSCC1,

II

ο

C.

albicans Br

V.

inaequales spores

E.

graminis

RNH + 3

•o' V

,N—SCCU

inh.

% Germination

inh.

% reduction in infection

Ο


11.

Antifungal


163

Agents

A c t i v i t y with Physicochemical Constants

Equa-


ki

k

2

k

log P

0.11

1.68

-2.68

d

0.14

1.36

-2.36

d

0.13

1.20

-1.84

d

0.21

1.13

-1.59

d

0.08

1.32

-0.89

d

0.18

1.38

-0.85

d

1.12

3.87

1.90

3

d

η

r

s

Hon

Ref.

7.3 (6.2-11)

22

0.99

0.13

18

8

5.0 (4.9-5.2)

9

0.99

0.08

19

4

4.7 (4.6-5.0)

11

0.96

0.11

20

4

2.8 (2.3-31)

6

0.98

0.08

21

7

7.8 (6.2-15)

14

0.99

0.12

22

8

3.9 (3.5-5.5)

5

0.99

0.07

23

4

1.7 (0.7-2.0)

6

0.96

0.32

24

7

c


164



Table l b . log A c t i v i t y =


Organism

- f c i (log P ) + k l o g Ρ + 2

2

Type of Compound

Ο-*

h

Action

Units of Activity

kill

Ι/μΜ/cm

2

M.

fructicola

P.

infestons

χ-

kill

Ι/μΜ/cm

2

A.

oleracea

x-

kill

Ι/μΜ/cm

2

V.

inaequales

X-

kill

Ι/μΛί/cm

2

kill

Ι/μΜ/cm

2

^ ^ N + - R

R BrV.

inaequales

0

II

S.

Biological CorrelationsâThe Hansch Approach

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