Indian Jou rnal of Chemistry Vol. 41 B, November 2002. pp. 2376-2384

QSAR by molecular topology of 2,4-dihydroxythiobenzanilides-·A virtual screening approach to optimize the antifungal activity

R Garcia-Domenech l*, A I Catalii2, A Garcia-Garcia ', A Soriano ', V Perez-Mondejar l & J G ~i l vez'

I Unidad de Investigac ion de Di seno de Farmaeosy Conecti vi dad Molecular. Departameillo de Qufmica Ffsica. Facu ltat de Farmacia. Universitat de Valencia. 46 100 Burja 'sot, Valencia, Spain.

e-ma il : ramon.1!arc ia .@uv.es 2 Departamento de Cienc ias Qufmicas. UI~iversidad Cardenal Herrera-CEU. Spain

Recei ved 30 Jllly 2001; accepled 19 February 2002

Molecular topology has been success full y used to get QSAR models able to predict the antifungal ac tiv ity of 2,4-dih ydroxythiobenzil anilides. Minimal inhibition conceillrations (MI C) from different Epiden llopiIyloll j /OCCOSlIIlI, Micro­~pUrulll gypselllll and TriciIopiIyloll iwerdig iIale strains arc used as key properties to eva luate. The results obwined establi sh clearly the high efficien cy of molecular topology in the prediction or such MIC val ues ( errors about ± I dilu tion or lower in 97% of the data ). Cross-validation by leave-one-out tests ha ve been also rea li zed to study the stability of the conncc ti vity functi ons selectcd.

Some structure-acti vity relations ha ve been studi ed as we ll. From them, it stands ou t the presence, on all the se lected equ ations, of the ST(-OH) descriptor which ta kes into accou nt thc lipophylli c cha racter of compounds w al. Jccordingly, should plJy a important role over the antifunga l activity.

A virtual screening to optimize such acti vity was also performed lead ing to clear improvement, part icul arly on the pre­di ction of activity for the Microsporulll gypselllli strain .

The pred iction of biological properties of organic compounds is one of the main objectives of the meth­ods based on quantitative structure-activi ty relation­ships (QSAR). The success of these methods is very dependent on an appropriate characteri zation of the molecular structure and se lect ion of the molecular structure descriptors.

Molecular topology ha ~ w idely demonstrated its ability for an easy and effici ent characteri zation of molecular structure by so-ca lled " topologica l indices", Tl si. When these indices are adcqual t> ly selected, it is poss ible to obtain a very specifi c charac teri zati on of each chemical compound , and therefore , they can be used in QSAR models2

.J.

In [his way the TI s have demonstrated their utility in the prediction of diverse physica l, chemical and bio­logica l properti es for different t y pe~ of compounds4

•7

,

and for the selection and d\.·' ign of n w antiviral sh, cy -

. 9 d ' Ih . If) I ' II . t' tostatlcs, se atlve:; ypnolics . an a gt's lt':s , anti un-I 17 b h d' l 1\ . h' . 1·1 . ga s -, ronc 0 I ators . , <L iltl Ista!llIllIl'S, antl -

toxoplasmatics 15, etc. I r. ~ ()n It" cases. tile predicted structures can be regarded :l'i nnv lC':IL! drug;..

Thi obenzanilides, bc in ~' an:t Jogub of LCIl 7.:l nilides, including sal icy lallilides, hel oag tf) J group ot drugs wi th interesti ll g pharmaceutical properti es since they ~lrf' charac!:;! ized by a w' df' speci I'll m ()f biological

activity depending largely on the type of subst itution . Most of them exhibit anti mycobacterial , herbi ­cidaI 16

.17

, in sect i cida l t ~ and fungicidal effects against a number of phytopathogenic fungi 19.2 . Recently , the

fungicidal potency of these compounds against some varieties of dermatophytes has been demonstrated2 1

.

The purpose of the present paper is to investigate the relationships between the structure described by the mo­lecular topology, and the fungicidal activity of 2,4-dihydroxythiobenzanilides and, using the prediction models obtained, to pelform a virtual screening in order to optimi ze the antifungal activity of these compounds

Matcl'ials and Methods Studied compounds

W e have selec ted a group of 33 compounds, 2,-1

dih ydroxythi obenzanilid f ~. The common structure u!

these compounds is shown in FigUl-e 1. T he bio logical ac ti v ity of these compounds again .: '

different dermatophy te,', is shown in Tables L II a:ld III. lis ing the dilu ti on melilod, the minimal Inhi bll l" n conce ntration (M IC) of indiv idll:1 1 compounds ag;:II I1 \i

I11I e , fungi ~pec i t:s (Epider/llophytoll / lnccosum. M i. crosporum gy!'seum and Trichophvtul! interdi;;IfIi/(, ')

was detennined2i. The concent rat ion intervCl l ran f'c:d

from 0.9 [ 0 1000 )lg/mL.

GARcrA-DOMENECH el al.: QSAR BY MOLECULAR TOPOLOGY OF 2,4-DIHYDROXYTHI OBENZAN ILIDES 2377

Table I-Prediction of the minimal inhibitory concentration MIC (~g/mL) using Eq I obtained for a EpidennophYlonj/occosum strain

Compd Substituents

II

III

IV

V

VI

VII

VIII

IX

X

XI

XII

Xlll

XIV

XV

XVI

XVII

XVIII

XIX

Rr R6 =-H

R2, R4 = -CH)

R4 = -secC4H9

R2=-F

R) = -F

R4 =-F

R2, R4 =-F

R2 = -CI

R) = -CI

R4 = -CI

R2, R4 = -CI

R2, Rs = -CI

R), R4 = -CI

R) = -CI, R4 = -F

R2 = -Br

R4 = -1

R) = -CH), Rs = -F

R4 = -CH), R) = -CI

R2 = -CI, R4 = -CH)

XX R2 = -CF)

XXI R2 = -OCH)

XXII R4 = -OCH)

XXIII R) = -OH

XXIV R2 = -CH), R4 = -OH

XXV R4 = -COOH

XXVI R) = -COOH, R4 = -OH

XXVII R2 = -C(=O)OCH)

XXVII/ R4 = -C(=O)CH)

XXIX R4 = -C(=O)CH2CH)

XXX R4= -CN

XXXI R2= -OH, R4 = -N02 XXXII R4 = -C(=O)NH2

XXXlll R4= -C(=O)NHCH2COOH

Phia ST(-OH) MIC(Obs)" MIC(Cald MIC(Calc)cvC

3.607 18.838

4.068

4.538

3.783

3.783

3.783

3.963

4.059

4.059

4.059

4.520

4.520

4.520

4.236

4.210

4.413

4.015

4.290

4.290

4.382

4.362

4.362

3.805

4.037

4.332

4.533

4.895

.:! - 4.363

19.026

19.095

18.797

18.805

18.811

18.770

18.897

18.885

18.877

18.936

18.944

18.924

18.858

18.932

18.910

18.896

18.960

18.972

18.847

18.995

18.944

28. 168

28.293

27.699

37.275

19.058

18.961

4.927 19.016

3.996 18.904

4.332 18.932

5.985 27.569

15 .7

31.2

3.9.

15.7

3.9

15.7

7.8

31.2

15 .8

7.8

3.9

3.9

1.9

3.9

3.9

7.8

31.2

3.9

3.9

15.7

3.9

3.9

31.2

62.3

31.2

249.0

1.9

3.9

3.9

7.8

3.9

15 .7

8.7

7.0

5.5

7.8

7.8

7.9

7.0

6.9

6.8

6.8

5.3

5.4

5.3

6.2

6.4

5.6

7.0

6.1

6.1

5.7

5.9

5.9

62.1

56.0

41.6

312.5

4.5

5.9

4.3

7.1

5.9

16.0

8.6

6.7

5.6

7.7

8.0

7.7

7.0

6.6

6.7

6.8

5.4

5.4

5.6

6.3

6.5

5.6

6.7

6.2

6.2

5.4

6.0

5.9

73.4

54.9

43 .2

377.4

4.8

6.0

4.4

7.1

6.0

16.1

(a) From reference 2 1; (b)From Eq. I; (c)From cross-validation study .

9

17 1,/2 ~~ S R2 R3

HO \10 *,3 13 8 1

14 ~ H~ 0.,0 4 R 4

OH 6 5 16 R6 R5

Figure 1 - Structure of thiobcnzanilidcs.

Topological descriptors Tis are structure descriptors derived from a graph

theoretical representation of molecules22. Thus, each

molecule is described by a graph, where atoms are represented by points called vertices and bonds by segments (called edges) between vertices. Graphs can be analytically expressed by matrices from which one single TI or a set of them may be derived. These indices, if well chosen, can be a very good characteri­zation of the molecular structure) .

INDIAN J. CHEM., SEC B, NOVEMBER 2002

Table II-Prediclion of Ihe minimal inhibitory concentrat ion MIC ().lg/mL) using E4. 2 obtained fo: a Microsporulll gvpsell!ll strai n

Compd

II

III

IV

V

VI

VII

VIII

IX

X

XI

XII

XI II

XIV

XV

XV I

XV II

XV III

XIX

XX

XX I

XX II

XX III

XX IV

XXV

XXV I

XXV II

XXV III

XX IX

XXX

XXX I

XXX II

XXX III

0.397

0.542

0.567

0.480

0.416

0.474

0.542

0.480

0.4 16

0.474

0.542

0.487

0.482

0.482

0.480

0.474

0.427

0.482

0.542

0.531

0.497

0.51 1

0.4 16

0.542

0.54 1

0.625

0.573

0.54 1

0.6 12

0.5 11

0.603

0.541

0.794

ST(-OH)

18.838

19.026

19.095

18.797

18.805

18.8 11

18.770

18.897

18.885

18.877

18.936

18.944

18.924

18.858

18.932

18.9 10

18.896

18.960

18.972

18.847

18.995

18.944

28. 168

28.293

27 .699

37 .275

19058

18.96 1

19.0 16

18.904

28.6 15

18.932

27.569

4.344

7.455

6.233

4.862

4.4 18

4.640

4.936

5. 122

4.677

4.899

5.455

5.455

5.455

5. 196

5. 185

5.058

5.529

6.455

6.455

6.344

5. 144

4.922

4.589

6.366

7.655

8. 122

8.2 10

8.32 1

8.433

7.380

5.528

7.655

11.002

G v 5

0.329

0.673

0.837

0.374

0.326

0.36 1

0.405

0.380

0.3 12

0.382

0.433

0.363

0.364

0.344

0.39 1

0.394

0.388

0.444

0.5 13

0.499

0.582

0.520

0.3 12

0.586

0.447

0.479

0.757

0.534

0.652

0.428

0.56 1

0.457

0.673

0.444

0.568

0.450

0.523

0.497

0.510

0.568

0.523

0.497

0.5 10

0.568

0.568

0.568

0.568

0.523

0.510

0.53 1

0.568

0.568

0.46 1

0.500

0.488

0.497

0.568

0.526

0.578

0.517

0.526

0.506

0.537

0.522

0.526

0.531

J v 5

0.02 1

0.037

0.042

0.022

0.0 19

0.02 1

0.023

0.022

0.0 18

0.023

0.024

0.020

0.020

0.0 19

0.023

0.023

0.022

0.025

0.029

0.025

0.032

0.029

0.0 18

0.033

0.024

0.024

0.038

0.028

0.033

0.024

0.028

0.024

0.029

MIC(obs)" MI C(ca le)"

3 1.2 66.3

62.3 3 1.1

3.9 3.2

62.3 32.3

7.8 18.4

3 1.2 31.3

3 1.2 14. 1

62.3 38.5

3 1.2 2 1.2

3 1.2 38.3

7.8 17.9

3 1.2 12.7

7.8 11 .4

7.8 10.6

3 1.2 39.9

31.2 40.7

31.2 10.6

7.8 17.2

15.7 27.0

3 1.2 17.8

15.7 15.5

62.3 23.7

62.3 93.0

62.3 88.0

497.9 2 13.7

995.3 604.7

3.9 7.5

62.3 52.4

3 1.2 3 1.4

31.2 70.3

15.7 3 1.6

62.3 52.3

124.6 171.4

MIC(calc)cv"

9 1.9

20.8

2.7

30.4

20.7

31.3

11.1

36.9

20.0

39.1

20.9

10.8

12.3

11 .4

40.7

41.7

7.7

19.8

29.2

15.4

15 .5

19.9

11 2. 1

103.3

177.1

382.6

9.9

50.4

3 1.5

81.3

44.8

5 1.0

280.7

(a)From reference 21; (b) From Eq. 2; (c) From cross-validation study.

The T Is that we will use in the present study are: A seri es of molecu lar connecti vity indices, Xi,

which were firstly defined by Rand ic in 197523 and then extended to a seri es of descriptors by Kier and Ha Il 2~ . These Ti s were the most success ful ones when app lied in QS A R studi esJ,24.

A seri es of topologica l charge indices, TCls, These descriptors were introduced by our research group25

and evaluate the charge transfer between atoms, Ji , and the global transfer of intra-molecu lar charge, Gi .

Kappa indices, Ki , which were introduced by Kier and Hal1 26 and contain informati on about aspects re­lated to the molecular shape,

Electrotopological state indices, E-state. These de­scri ptors were introduced by Kier and Half7 and con­tain i nformation about polarity and steric access ibility

GARCIA-DOMENECH el (II.: QSAR BY MOLECULAR TOPOLOGY OF 2,4-D IH YDROXYTHIOBENZAN ILIDES 23 9

Table III- Predic tion of the minimal inhibitory concentrati on MIC (!lgiIllL) lIsing Eq 3 obtained for J Trichof!hYIOI/ illlerdigitale strain

Compd

II

III

IV

V

V I

V II

V III

IX

X

X I

X II

X III

X IV

XV

XV I

XV II

XVIII

X IX

XX

XX I

XX II

XXI II

XX IV

XXV

XXVI

XXV II

XXV III

XX IX

XXX

XXXI

XXXII

XXX III

0. 802

1.263

2.0 14

0.901

0.863

0.874

0.964

1.136

0.999

1.020

1.327

1 . .334

1.532

1. 158

1.394

1.290

1.0 18

I A65

i .303

1. 136

0.969

0.948

0.875

1.163

1.022

1.123

1.084

1.133

1. 146

0.935

1.1 0 1

1.048

1.1 0 1

TId(4) S9

106.206 5.1 8 1

I 18.026 5.273

127.693 5.287

120.342 5.074

11 9.899 5.101

11 9.78 1 5.1 20

134.332 5.013

111.775 5. I R2

III A88 5.1 8 1

III A II 5.ISO

11 7.203 5. 1:-11

11 7.255 5.I R2

11 7.005 5.18 1

125.51 4 5.120

11 0.578 5.2 19

109.948 5.212

125.S9 1 5. 145

11 7A I 2 5.214

11 7.606 5.214

153.5 17 4.996

123.255 5.233

122.540 5.21 1

11 7A47 5.142

123.6 19 5.2 11

135.895 5. 149

148 .347 5. 11 2

142. 172 5.2 11

130.330 5.198

135 .1 95 5.22 1

125.106 5.1 77

151A80 5.0RO

133 .30 1 5. 173

164.872 5. 191

S\>C=)

OA II

OA21

OA I 3

0.1 78

0.248

0.291

0.058

0.334

0.356

0.370

0.293

0.279

0.3 16

0.236

0.388

OA II

0.252

0.359

0.336

-0.079

0.349

0.378

0.304

0.339

-0.735

- 1. 12 1

-0.264

0.327

OA I 9

0.335

0.094

-0.204

-1.376

ST(-OH)

18.S3R

19.()26

19 (l95

18.797

18.805

18.81 1

I S.770

18.897

18.885

I R.S77

18.936

I S.944

18.924

18.858

18.932

18.9 10

18.896

18.960

18.972

18.847

18.995

18.944

28. 168

28.293

27.699

37.275

19.058

18.96 1

19.0 16

18.904

28.6 15

18.932

27.569

(a)From reference 2 1; (b)Frolll Eq. 3; (c)From cross-validati on study .

of each atom i, derived from its intrinsic state Ii (de­pending on electronegati vity and the ratio of 11: ane alone pair electrons to the count of (J bonds) and from 'electronegativity gradients ' describing the perturba­tion of Ii by each other atom28

. The E-state indices, Sj , are fully described with many examples in a recent book29. An extension of the E-state formalism is the use of an atom-type index, STj, making it possible to

ST(_F)

0.000

0.000

0.000

13A06

12.987

12.727

26 .1 75

0.000

0.000

o.oon 0.000

0.000

0.000

13.007

0.000

0.000

13.247

0.000

0.000

38.603

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

MIC(obs)"

7.8

15.7

3.9

15.7

3.9

31.2

15.7

15.7

31.2

7.8

3.9

3.9

1.9

7.8

7.8

3.9

31.2

3.9

3.9

15.7

7.8

7.8

15.7

62.3

3 1.2

249. 1

7.8

7.8

3.9

7.8

3.9

3.9

62.3

M IC(ca l/

12.6

14.5

3A

9.6

13.7

16.2

12A

6.5

8.0

7.5

4.0

4. 1

2.7

9.0

6.9

7A

16.6

4.6

6.4

2 1.0

12.3

9. 1

33 .7

43 .2

46.8

172.0

8.0

4.5

4.7

5.5

4.0

6. 1

57.3

M IC(Calc)c\,e

13.9

14. 1

3.0

88

15.9

15.0

11.5

6.0

7.1

7.5

4.0

4.1

3.0

9.0

6.S

7.9

15A

4.7

6.6

31.3

13.4

9.3

45.6

34.7

52 .0

11 4.9

8. 1

4.2

4.9

5.2

4.3

6.7

52.2

T study molecules of noncongeneric structure. S j is calculated by summing of Sj for all atoms of the same type in the molecule.

The li st of all the topological descriptors used in this paper is given in Table IV. The TIs have been computed with the MOLCONN -Z and Etopo II programs30

.31

.

2380 INDIAN J. CHEM., SEC B, NOVEMBER 2002

Table IV-Symbols for topological indices and their defi nitions

Index sy mbol Definition References

"'Xl' Path connectivity index oforder.m=O- IO 23,24

IllX"p Path valence connecti vity index of order m=O-1 0 23,24

IIlXc Cluster con nectivity index of order 111=0-4 23,24

IHXVC Cluster valence connecti vi ty index or order m=O-4 23 ,24

"'XI'C Path-cluster connec ti vity index of order m=0-4 23,24

IllX "' pc Path-cluster va lence connectivity index of order m=0-4 23,24

Gill Charge index of order m=0-5 25

J", Bound charge index of order m=0-5 2S

GV

m Valence charge index of order m=O-S 25

JY

I1l Va lence bound charge index of order m=0-5 25

K Kappa index 26

Sj E. state index 27 ,29

STi Atom-type E-state index 27 ,29

TTd(4) Total topological indices (valence, with atom types) 30

QSAR studies The regression equations were obtained by corre­

lating the experimental values of MIC with the calcu­lated TIs, us ing mu ltili near regression analysis, MLRA. The Furnival-Wi lson algorithm32 was fo l­lowed to find subsets of descriptors. Equations were selected according to the criterion of the minimum of Mallows' Cp parameter33

. To validate the models, we carried out a cross-validation by leave-one-out. From the residuals obtained, the standard error of estimate SEE(cY) is determined for the cross-validation.

Virtual screening to optimize antifungal activity Molecular topology is a work tool that presents

some advantage in relation to molecular mechanics or quantum chemistry. The most remarkable is the calcu­lati on speed. Hundreds of compounds can be analyzed in a few minutes .

For thi s reason, mo lecular topology is well suited to evaluate possible biological ac ti vities of com­pounds represented in big databases or virtual librar­ies.

When the predictive power of the QSAR models obtained is sati sfac tory, they can be used to model and to optimi ze the acti vity .

In this paper, we have designed a virtu I library of 2,4-dihydroxythiobenzani lides, using the base struc­ture, Figure 1, and vary ing the position and number of substituents used in thi s study. Since the theoreti cal number of cases is too hi gh, we have selected those

substituents and positions in the base structure occur­ring in the most active compounds.

Results and DisclIssion The first objective was to fi nd the best QSAR

models for describing the antifungal activity against each of the strains studied.

The best linear regression equations obtained to­gether with the statistical parameters for each model are ill ustrated in the Table V.

Eq. 1 , log MICr:l'iti f/occ., was selected without the intercept since its stati stical significance was under 95 % . All the other variables and equations showed significance higher than 98%.

The observed and calculated MIC for each com­pound are presented in Tables I , II and III , together with the MIC pred icted in the leave-one-out approach. The models are very stable with respect to the exclu­sion of data points as demonstrated by the standard error of estimation of the cross-val ida tion, SEE(cv), and by plott ing residual vs residua ls(cv) (see Figures 2, 3 and 4). On ly compound XXX I was el iminated when Eq.! was obtained.

The prediction was found to be sati sfactory if we consider that we are dealing with a property with dis­crete values. The degree of uncertainty in the obtained value of MICexp. is, in any case, about ±! dilution (a MIC= !5.7 has an uncertainty which ranges between the previous dilLition, MIC=31.2 and the following one, MIC=7.8).

GARCIA-DOMENECH et al.: QSAR BY MOLECULAR TOPOLOGY OF 2,4-DIHYDROXYTHIOBENZANILIDES 2381

Table V---Connecti vity fun ctions selected through multi-linear regress ion analys is

Descriptor Coe ff (B) SE (B) p-Ievel

Log MICci,id.j7occ._ Eq . I

Constant

ST(-OH) 0.097 0.013 0.0000

Phia -0.243 0.062 0.0005

N = 32 r= 0.9614 F=1 83

SEE = 0.304 SEEley) = 0.324 p<O.OOOI

Log MICMicTO.W ~y".<e"m_ Eq. 2

Constant 0.017 0.004 0.011

ST(-OH) 0.070 0.013 0.000

Gsv - 16.9 16 3.483 0.000

G2v 0.267 0.064 0.003

1s v 280.42 64 .724 0.002

h -6.367 1.848 0.019 9Xp 4.932 1.879 0.014

N = 33 r = 0.8629 F=12.6

SEE = 0.289 SEE(ev) = 0.375 p<O.OOI

Log Mlen"ic". i" 'ml._ Eq . 3

Constant -30.730 8.06 1 0.001

"Xpcv -0.776 0.222 0.002

TTd(4) -0.015 0.055 0.01 2

S9 6.282 1.548 0.000

ST(>C=) -0.5 11 0.183 0.010

ST(-OH) 0.090 0.016 0.000

ST(_F) 0.054 0.011 0.000

N = 33 r = 0.8732 F=13.9

SEE = 0.248 SEE(cv) = 0.296 p<O.OOOI

0.9

0.6 0

>' 0

0 u 0.3 0° '-"" Vl

(; 0 ::l

"0 o~ ' Vi 0 <I.l 0

0:: #b

-0.3 0 0 0

0

-0.6 -0.6 -0.3 0 0.3 0.6 0.9

Residuals

Figure 2 - Plo t of residua ls vers us cross-va lidated re-

s iduals for a Epidermophytol1 floccosum s tra in.

0.9

0.6 0

>' 0 ocr::rP ~ 0.3 0 0 Vl 00 C;; 0 '" 0

"0 0 0 ' in (L)

o ~ 0:: -0.3

~c& 0

-0.6

-0.6 -0.3 0 0.3 0.6 0.9

Residuals

Figure 3 - Plot of res iduals versus cross-validated residu­

als for a Microsporum gypseum s train.

0.9

0.6 0

>- 0

"* 0.3 o 6l

oOJ -;:; 00 " &JB "0

'0; 0 <.> 0::

-0.3 o ~o 0

-0.6

-0.6 -0.3 0 0.3 0.6 0.9

Residuals

Figure 4 - P lot of residuals versus cross-validated res idu­

al s for a Trichophyton interdigitale stra in .

If we consider this fact, for a total of 98 predictions

of MIC (32 for Epidermophyton jloccosum, 33 for

Microsporum gypseum and 33 for Trichophyton

interdigitale) the error of prediction exceeds 2

di lutions in only three cases (see compounds II , VIII

and XVII , Table J). Thus, in 97% of the cases, the

error of the prediction of MIC ranges about ±l

dilution or lower, which represents a significant

degree of prediction.

T The S (-OH) descriptor appears In all equations

with a positive coefficient, indicating that the

presence of a hydroxyl group in the mol ecule slightly

increases the M IC va lue (see the compounds XXIII ,

XX IV, XXV, XXVI and XXXIIl ). Generall y, a higher

2382 INDIAN J. CHEM., SEC B, NOVEMBER 2002

lipophyl licity promotes activity of the compounds against dermatophytes2 1

. The presence of the -OH group lowers the lipophyll icity and therefore, increases the MIC values .

In Eq. I the Phia descriptor is present with a nega­ti ve coeffic ient. This index is the result of combining two kappa indices (Phia = (KUIKu3/N), where N is the number of non-hydrogen atoms in the molecul e. This descriptor is related to the molecuiar fl ex ibility index of Kier. According to Eg. I. , hi gher fl ex ibility in­creases anti funga l activity. Although the mechani sm of' action thi s kind of drugs is un know n, it is reason­ab le to ass ume that independent of the site of recogni­tion (superfi cial or through the fun gous walls) , mo­lecular tlex ibility plays ,mttillportant ro le.

Although not in a very clear way, the presence of the ~Xpc" and ST(>C =) descriptors, both with negati ve coefficients , shows that substituents in the aromatic ring as such with carbon atoms =C< (C(=O)CH) and C(=0)CH2CH 3, compounds XXVIII and XXIX) in­crease the antifunga l activi ty . The presence of four TCls in Eg. 2 suggests the influence of intramolecular charge transfer on the antifungal activity for the Mi­crOSpOrt1l1l GypseulII strain.

The second objec ti ve of thi s work was to make profit from the predictor capacity of the obtained QSAR models, Egs I , 2 and 3, to model and to opti­mise the antifunga l activity of analogous 2,4-dihydrox yth iobenzi lani I ides.

After building a virtual library made with hundreds of compounds (modify i g the number and position of the substitutes in R2, R3, R~ and Rs from the base structure, Figure 1), we made a virtual screening with the help of Egs I, 2 and 3, with the aim of selecting those mol ecules which offered a better ac tiv ity . Table VI shows some of the most significant results.

Some interest ing comments can be stated: When we modify the position of one of the -CH)

frag ments of compound ]J (-CH3 in position R2 to po­sition R3, compound IA), we slightly improve the ac­ti vity against all the strains (from 31.2 to 7.0 against Epidermophyton floccosum; from 62.3 to 24.7 against Microsporum gypseulIl and from 15 .7 to 9.0 against Trichophyton interdigitale).

If we also introduce a C l atom in position Rs, compound XXXVIIlA, the act ivi ty improvement is

eveli more important in relati on to the starting com­pound II (from 31.2 to 5.5 against c/Jidenllophytoll jloccosul7l; from 62.3 to 7.2 ag inst MicrosporulII gypseum, and from 15.7 to 3.8 against Trichophyton in te rdig i tale).

If we add a -CH3 third group , in pos ition R3,

compound XXXIA, we improve the antifunga l acti vity against the MicrosporulII gypseulII strai n (from 62.3 to 7. 8) .

If we substitute, for instance, the fu nctional group C(=0)CH3 in compound XXVIII by a more vol umi ­nous and branched one, C(=O)C(CH3h, compou nd XXXVIA, a different improvement of the antifunga l activity is predicted, (from 62.3 to 2.6 against Micro­sporum gypseulII and from 7.8 to 1.6 agai nst Tric/ID ­phyton interdigitate). The same would happen if we changed the C(=0)CH2CH3 group in compound XXIX into C(=0)CH2C(CH3h, compound XXXVII A. in particul ar in the Microsporum gypseulII strain (from 3 1.2 to 0.9).

Another way of furth er i mprov ing the anti fun gal activity agai nst the Microsporum gypseum strain could be changing the C(=0)CH3 group from R~ po~i­

tion, compound XXVTII , to R3 and Rs pos iti ons, com­pound XIIA (the MTCMicrosp. gYIJ.l'elllll decreases from 62.3 to 0.3).

The results obtained in thi s virtual screening study are very interestin g as they predict new chemical structures with a better antifungal ac[ivity , particularly agai nst the Microsporum gypseu /'ll strain. Thi s offers a fast and easy tool to model and to opti mi ze a determined pharmacological propert),. After that , it 's necessary to carry out the correspondent microbiological tests of th ese compounds to validate the obtained resu lts.

Conclusions Molecular topology has been used with success to

find QSAR models to pred ict the fungicide act ivity of 2,4-dihydroxythiobenzilanilides. Some structure­activity relat ions have been estahli shed.

On the other hand, we have built a virtual library with several hundreds of 2,4-d ihy roxybenzil ani lide analogous for the virtual screening and optimization of the antifungal activity . Interesting improvements in the activi ty have been obtained with the MicrosporulII gypseul11 strain.

GARCIA-DOMENECH et al.: QSAR BY MOLECU LAR TOPOLOGY OF 2,4-DIHYDROXYTHIOBENZAN ILlDES 2383

Table VI--Computati onal scrccning from Eqs 1,2 and 3 appli cd to virtual 2,4-dihydroxy­benzanilides derivativcs showing fungicide act ivity (MIC (j..lg/ml)).

Compd

IA

II A

IlI A

IVA

VA

VIA

VIlA

VillA

IXA

XA

XIA

X IlA

X IIlA

XIVA

XVA

XV IA

XVIlA

XV IIl A

X IXA

XXA

XXIA

XXllA

XXIllA

XXIVA

XXVA

XXVIA

XXVIlA

XXV[[IA

XX IXA

XXXA

XXXIA

XXX llA

XXXIIlA

XXX IVA

XXXVA

XXXV IA

XXX VIl A

XXXVIIl A

Substitucnts

R),R4 == -CH,l

R,l,Rs = -CH)

Rs = -sec-C4H~

Rs =-F

R),R4 =-F

R) = -Br

R.1 ,Rs = -Br

R) = -OCH,

R, = -OCH), Rs = -CH.1

R4 = -C(=O)-NH-CH,

R4 = -ter C4H~

R.1, Rs = -C(=O)-CH)

R~, Rs = -C(=O)OCH3

R.1 = -F, Rs = -C(=O)OCH3

R4 = -(CH2)rC(=O)-CHr NH2

R) = -secC4H9, Rs = -OH

R) = -OH, R4 = -secC4H9

Rs = -CN, R6 = - OCH)

R.1= -Br, Rs = -C(=O)-NH2

R4= -C(=O)-NH2' R6= -CH)

R2 = -CI , Rs = -Br

R2 = -CI , Rs = -CH)

R2 = -CI, Rs = -OCH2CH)

R4 = -CI, Rs = -C(=O)-CH)

R) = -C(=O)-OCH)

R.1 = -C(=O)-OCH2CH,

R" R4,Rs = -CH)

R.1 = -C(=O)-OCH(CH)h

R.1 ,R4 ,R6 = -CH)

R4 = -C(=O)-OCH(CH))2

R2,R.1, R4 = -CH,

R4 = -C(=O)-OCH2CH)

R4 = -C(=O)CH2CH2CH .1

R4 = -C(=O)-OCH)

R4 = -C(=O)-CH(CH))2

R4 = -C(=O)-C(CH)h

R4 = -C(=O)-CH2C(CH)h

R), R4 = -CH),Rs = -CI

(a)From Eq. I ; (b) From Eq. 2; (c) From Eq. 3.

Acknowledgement

This study has been supported by GYOI-47 (Generalitat Yalenciana, Spain) as we ll as for the Spani sh Mini stry of Science and Technology (SAF2000-C03-02).

M I COl Epili"r' MIChMicro,p' M I C\richoph.

7.0 24.7 9.0

7.0 18.8 17.4

5.5 2.2 5.5

7.8 18.0 13.9

7. 1 8.4 16.9

6.3 22.5 9.3

4.5 9.3 7.3

5.9 20.5 10.8

5.3 6.6 12.6

4.4 40.4 5.4

3.8 10.3 14.5

4.0 0.3 3. I

4.0 1.4 3.3

4.0 4.0 10.6

2.3 12.0 6.0

44.3 0.2 16.3

46.5 3.3 11.5

4.8 1.6 5.3

4.3 16.4 5.3

5.3 3.2 7.2

4.9 12.5 4.7

6.2 14.0 7.4

3.4 1.9 7.2

4.6 16.0 3.0

4.4 34.8 7.0

3.2 42.6 8.2

6.3 8.9 7.3

2.9 29.9 7.5

6.3 7.6 10.7

2.8 18.7 5.6

6.3 7.8 7.7

3.2 34.4 6.5

3.2 16.1 5.4

4.4 43.1 5.9

3.9 11.0 3. 1

4. 1 2.6 1.6

3.0 0.9 2.5

5.5 7.2 3.8

References I Randi c M , J Math Chel1l , 9, 1992,97. 2 Soler-Roca RM , Sipan-SiuTion MC, Garcia-Domcnech R &

G,llvcz J. Illdiall J Chelll, 33B, 1994,209. 3 Kicr L B & Hall L H, Moleclliar conecti vity ill stl'llclllre-

acti vity analysis (Reseach Studies Press : Letchworth, Eng-land), 1986.

2384 INDIAN J. CHEM., SEC B, NOVEMBER 2002

4 De Julian-Orti z J V, Garcia-Domenech R & Galvez J, J Chromatogr, 719, 1996,37.

5 Garcia-Domenech R, Villanueva A, Galvez J & Gozalbes R, J Chilli Phys. 96, 1999. 1172.

6 Pogliani L, Croatica Chemica Acta, 3, 1997, 803. 7 Devillcrs J, ClIrrent Opinion ill Drug Discovery & Develop­

ment. 3, 2000, 275 . 8 De Julian-Ortiz J V. Galvez J, Munoz-Collado C, Garcia­

Domenech R & Gimeno-Cardona C, J Med Chem. 42, 1999, 3308.

9 Galvez J, Garcia-Domenech R, Gomez-Lechon M J & Cas­tell J V, J Malec Struct (THEOCHEM), 504, 2000, 241.

10 Estrada E, Pena A & Garcia-Domenech R, Call/put Aid Mol Desigll, 12, 1998,583.

II Garcia-Domencch R, Garcia-March F J , Soler R, Galvez J, Anton-Fo G M & De Julian-Orti z J V, QlIallt StruCl -Act Relat, IS, 1996, 20 I.

12 Pastor L, Garda-Domenech R, Wolsky S, Garcia M D & Galvez J, Bioord Med Chell/ Lell, 8, 1998,2577.

13 Rios-Santamarina I, Galvez J, Garcia-Domcnech R, Cortijo J, Santamaria P & Morcillo E, Bioord Med Chern Lell, 8, 1998,477.

14 Casaban-Ros E, Anton-Fos G M, Galvez J, Duart M J & Gar­cia-Domenech R, Quant Strtlct -Act Helat, 18, 1999, 35.

15 Gozalbes R, Galvez J , Garcia-Dome nech R & Derouin F, SAR and QSAR Env Res, 10,1999,47 .

16 Shell Research Ltd Belg 612252, 1962. 17 Shell Research Ltd Brit 987253 , 1965.

18 Hoechst A G, Ger Offen DE 3802 175, 1989. 19 Kumai Chemical Industry Co Japan Kokai 80141404, 1980,

Chem AbsTr 94, 1981,97979. 20 Kumai Chemical Industry Co Japan Ko ai 8231658, 1981 ,

Chem Abstr 97,1982,6007. 21 Matysiak J, Niew iadomy A, Macik-N iewiadomy G & Korn-

illowicz T, ElIr J Med Chem, 35,2000, 393. 22 Mihalic Z & Trinajstic N, J Chem Education, 69,1992 , 701. 23 Randic M, JAm Chem Soc, 97, 1975, 6609. 24 Kier L B & Hall L H, Molecular connectiviTy in chell/istry

and drug research, (Academ ic Press, London), 1976 25 Galvez J, Garcia R, Salabert M T & Soler R, J Chell/ Inf

COII/PLlf Sci. 34, 1994, 520. 26 Kier L B, Quant Struct-Act Relcll , 4, 1985, 109. 27 Kier L B & Hall L M, Pharm Res , 7, 1990,801. 28 Todeschini R & Consonni V, Handbook of molecular de­

scriptors l SI Edition , (Wiley-VCH, Weinheim), 2000. 29 Kier L B & Hall L H, Molecular structure description: Th e

eiectrotopologicai state; (Academic Press: San Diego), 1999.

30 MOLCONN-Z software , version 3 SO (L H Hall Eastern Nazarene College, Quincy, Mass)

31 Etopoll software (Unidad de Investigacion de Diseno de Farmacos y Conectividad Mo lecul ar Departamento de Quimica Fisica Facultad de Farmacia Universitat de Valencia Spain)

32 Furnival G M, Technol1letrics, 13, 1971,403. 33 Hocking R R, Technometrics, 14, 1972. 967