Quantitative structure-mutagenic activity relationships of triazino indole derivatives

Mutation Research, 268 (1992) 1-9

i

© 1992 Elsevier Science Publishers B.V. All rights reserved 0027-5107/92/$05.00

MUT05091

Quantitative structure-mutagenic activity relationships of triazino indole derivatives Estrella Garcia

a, A d e l a

L o p e z - d e - C e r a i n a, V i c t o r M a r t i n e z - M e r i n o b and Antonio Monge c

a C.I.F.A., Uniuersidad de Navarra, b Departamento de Qu[mica, Universidad Pdblica de Navarra and c Departamento de Qubnica, Orgdnica y Farmacet~tica, Um'versidad de Navarra, Pamplona (Spain)

(Received 18 June 1991) (Revision received 29 October 1991) (Accepted 26 November 1991)

Keywords: Mutagenesis; Triazino indole derivatives; Ames test; Quantitative structure-activity relationship

Summary

The mutagenicity of 3-(4'-benzylidenamino)-SH-1,2,3-triazin[5,4-b]-indol-4-onederivatives, new compounds with considerable platelet antiaggregating activity, was assayed with the Ames test using the Salmonella typhimurium strains TA97, TA98, TA100 and TA102. The adaptive least-squares method (ALS method) was used to carry out a quantitative structure-activity relationship (QSAR) analysis. Three equations, based on 10 congeners, were found for strains TA97, TA98 and TA100. The results suggest that lipophilicity of the substituent decreases the mutagenicity of the series.

The structure of the triazinoindole skeleton is of particular interest in connection with its possible relationship as an inhibitor of induced platelet aggregation (Arraras, 1990). In a previous paper, we have reported the mutagenic activities of some 3-(4'-benzylidenamino)-5H-1,2,3-triazin[5,4-b]indol-4-one derivatives using the Ames test (Garcia et al., 1991). When a structure-activity relationship of the derivatives was considered, mutagenicity seemed to be modulated by a radical occupying the 4' position of the benzylidenamino group. Compounds with substituents C6H 5 and OC6H5

Correspondence: Dr. Estrella Garc[a, Toxicologla Gen~tica, C.I.F.A., Universidad de Navarra, Apartado 273, 31080 Pam-

plona (Spain).

were not mutagenic, compounds with substituents NO 2, COOH, C O O C H 3 and C! were S9-dependent mutagens and compounds with H, OH, OCH 3 and NHCOCH 3 were sg-independent mutagens. These results prompted us to attempt a quantitative structure-activity relationship (OSAR) analysis. If any quantitative relationship were detected, this would permit us to develop compounds with the same activity as platelet antiaggregating agents, but without mutagenic activity detected in the Ames test. Although the Ames test cannot give a definitive answer concerning the mutagenicity of a given compound in humans, we have chosen it because it is, most likely, the best validated and most accepted short-term test for predicting carcinogenicity (Brusick and Auletta, 1985).

Analysis of structure-activity relationships (SAR) and the potential for predicting mutagenicity from structure have evolved gradually (Tute, 1990). In the last 30 years, a number of methods for the study of SAR have been developed (Fujita, 1990; Craig, 1990). Although the majority of them arc aimed at producing pharmaceutical drugs, they can also bc applied to mutagenicity (Benigni et al., 1989). This paper describes the analysis of the QSARs of these derivatives for mutagenic activity using the adaptive least-squares (ALS) method (Moriguchi and Komatsu, 1977; Kawashima et al., 1986). In the parametrization of structural features for the ALS study, we examined physicochemical parameters of 4' substituents in the 3-(4'-benzylidenamino)-SH-1,2,3-triazin[5,4-b]indol-4-one derivatives. The ALS method does not assume any particular distribution of the data and can be considered to be a technique of pattern recognition. This system has been devised (a) to formulate a QSAR in a single mathematical equation, irrespective of the number of activity classes and (b) to categorize multidimensional structural patterns into multiple ordered classes by means of the equation. It has been demonstrated that the ALS method is superior and more stable in recognition and prediction of ordered categorical data

than linear discriminant analysis (LDA), the Knearest-neighbor method (KNN) and nonelementary discriminant analysis (NDA) (Moriguchi et al., 1980). Material and methods

Chemistry T e n c o m p o u n d s were prepared in the Organic Chemistry Department of the University of Navarra (Arrarfis, 1990). T h e purity of the synthesized c o m p o u n d s was tested by elemental analysis (CHN). IR was recorded on a Perkin Elmer 681 instrument, and I H - N M R and 13CNMR spectra wcrc recorded on a Bruker A C 200E at 200 and 50 M H z respectively. M a s s spectra wcrc obtained on a Hcwlett-Packard spectrometer model 5 9 8 8 A by direct insertion probe (DIP). Ionization was performed by electron impact at 70 cV. T h e general structure of the compounds is shown in Table 1.

Mutation tests Mutagenicity was evaluated in a reversion test, using the histidine-requiring Salmonella typhimurium strains TA97, TA98, TA100 and TA102, which were kindly provided by Dr. B.N. Ames (University of California, Berkeley, CA, U.S.A.). Assays were performed according to the

TABLF I STRUCTURAL TIVES N=N

FEATURES

F O R T E N 3-(4'-BENZYLIDENAMINO).5H.I,2.3.TRIAZIN[5,4.b]INDOL.4.ONE

~N--CH v

-~ I H

R

R

O

tr

F

R

~-

Wmax

CI NO2 OH NHCOCH 3 COOH COOCH 3

0,23 0,78 - 0,37 0 0.45 0.45

0.41 0.67 0.29 0.28 0.33 0.33

-0.15 0.16 - 0.64 - 0.26 0.15 0.15'

0.71 - 0,27 - 0.67 - 0.97 - 0.32 - 0.01

3,11 3.11 3.11 3.11 3,61 3.11 3.36

OC6H5 C6H5 OCH3

- 0.03 - 0.01 - 0.26

0.34 0.08 0.26

- 0.35 - 0.08 - 0.51

2.08 1.96 - 0.02

5.89 3.11 3.11

H

DERIVA-

0

0

0

0

L

DH

AH

6.28 7.74 7.66 6.96 9.37 8.13 9.07

0

0

0 0 1 1 1 0

0 I 1 1 1 I

8.73 10.50 8.20

0 0 0

1 0 1

3 TABLE 2 C R O S S - C O R R E L A T I O N M A T R I X O F T H E P H Y S I C O C H E M I C A L P A R A M E T E R S A N A L Y Z E D BY T H E A L S M E T H O D

F R ~r Wma x

L DH AH

o"

F

R

¢r

Wm~

L

DH

0.624 0.884 a - 0.102 - 0.148 0.045 -- 0.191 0.099

1 0.186 - 0.209 0.080 - 0.074 0.004 0.519

1 0.004 - 0.237 0.103 -- 0.236 -- 0.186

1 0.546 0.439 -- 0.602 -- 0.428

1 0.215 -0.148 0.280

1 -0.063 0.051

1 0.429

a ~ , F a n d R are not analyzed simultaneously.

preincubation procedure (Maron and Ames, 1983), under strict standard operating procedures and GLP control. The influence of metabolic activation was tested under conditions of a standard Ames protocol with 0.5 ml of a $9 mix containing 50 t~i (10% $9) of $9 fraction. The $9 liver microsome fraction was prepare~! [rom male Wistar rats pretreated with an Lp. dose of Aroclor 1254 (500 mg/kg) in corn oil. $9 fraction and $9 mix were prepared as described by Maron and Ames (1983). The 10 chemicals were tested in a preliminary toxicity test. The experiments were set up twice, in two different experiments, with five different concentrations per compound, three plates per concentration and the corresponding negative and positive control in each case. The positive control compounds were: NPD (20 /zg/plate) in TA97 0% $9 and TA98 0% $9; NAAZ (2/~g/plate) in TA100 0% $9; MMS (1 ~l/plate) in TA102 0% $9; 2AF (10 /~g/plate) with $9 mix in TA97, TA98 and TA100, and 2AA (4 ~g/plate) in TA102 10% $9. Calculations Observed activity. The mutagenic activity was measured as the number of His + revertants per dose. Compounds were classified in two categories (see Table 3): (a) activity class 1 or positive result, when the number of spontaneous revertants was at least doubled and a dose-response relationship was confirmed with a regression test (p < 0.05); (b) activity class 0 or negative result, when either one or both of the former conditions were not achieved.

Substituents parameters. Electronic (~r, F and R), hydrophobic (It) and steric (Wmax and L) substituent constants serve as descriptors for the molecular properties of 3-(4'-benzylidenamino)5H- 1,2,3-triazin[5,4-b]indol-4-one. Additionally, hydrogen bond acceptor (A H) and hydrogen bond donor (D H) affinities of the substituents were analyzed. Wmax represents in ,~ (10 -I nm) the maximum width of the 4'-benzyliden substituents (aryl group) from the bond axis connecting the exocyclic carbon atom with its a-carbon atom in the direction towards which ortho- or meta-substituents extend. L is the length of the 4'-benzyliden substituents along the bond axis that connects them to the exocyclic carbon atom. Wmax and L were calculated using Verloop's B4 and L parameters for phenyi and its 4' substituents (Monge et ai., 1989). HammeR's constant (tr), Swain and Lupton's field and resonance factors (F, R), hydrophobic character (~r) and Verloop's B4 and L parameters (Vm~ and L) of the substituents are compiled by Hansch and Leo (1979) (Table 1). All the combinations of these 8 independent variables were tried in order to obtain the best possible correlation. The data processing was done on a Macintosh Plus machine using the stepwise regression test. Subsequently the ALS iteration was performed, and the best discriminant function was selected according to the Spearman rank correlation coefficient, as will be detailed below. ALS method. The ALS method includes an error-correcting feedback algorithm, and the details have been described elsewhere (Moriguchi

0 0.003 0.01 0.00 0.1 0.3 Positive control Probability Activity class

0 0.01 0.03 0.1 0.3 0.9 Positive control Probability Activity class

0 0.006 0.02 0.06 0.2 0.6 Positive control Probability Activity class

-CI

-NO 2

-OH

194-+ 40.0 287_+ 13.3 887+ 33.3 1355+ 67.7 3579_+271.5 5018_+ 73.7 862_+ 7 5 . 5 0.0001 ** 1

85_+ 2.4 532_+ 33.9 736+ 39.6 697-+ 7.5 843_+ 68.7 855_+ 9.3 919_+ 29.9 0.0002 ** 1

126_+ 11.3 163+ 9.9 179_+ 14.5 194+ 4.2 194+ 8.3 188_+ 5.5 862_+ 70.5 0.0001 ** 1

173_+ 4.0 169_+ 2.4 238_+ 12.7 803_+ 65.2 2551_+ 92.3 3062_+208.9 799-+100.0 0.0001 ** 1

145+ 3.6 401_+ 37.2 1038+ 65.6 2071_+108.8 2220+ 69.8 2064-1-121.8 156-+ 30.3 0.0001 ** 1

275-+ 2A 276_+ 8.9 434_+ 5.0 1231+ 44.3 1472_+ 22.3 1340-+ 23.6 1442_+ 52.1 0.0001 ** 1

25_+ 0.9 126_+ 4.8 459_+ 17.4 1050_+ 88.1 2339_+ 27.7 3052-+ 56.3 853_+ 7 6 . 1 0.0001 ** i

24_+ 1.8 1805+ 30.0 2558.+187.5 2506.+ 79.2 2049_+ 93.7 2116_+i01.3 1044+ 97.6 0.845 1

20_+ 1.5 151-+ 15.2 201_+ 8.4 199.+ 1.7 195_+ 13.2 173-+ 10.3 947.+ 1 6 . 2 0.4445 0

23_+ 2.2 1222_+!32.1 1811_+ 36.3 3787_+139.6 4744+ 85.9 4754_+119.7 635_+ 9.7 0.0001 ** 1

0% $9

154_+ 9.8 179_+ 1 8 . 8 372.+ 1 7 . 8 1832_+ 5Z9 2251_+117.3 3262+_114.7 725+ 48.2 0.0001 ** !

10% $9

0% $9 142+ 10.6 942+_ 12.3 1196+ 29.4 2910_+ 93.0 3562_+!65.6 4586_+140.5 819_+ 54.4 0.0001 ** !

TA97

Qzmol/plate)

0 0.006 0.02 0,06 0.2 0.6 Positive control Probability Activity class

TA98

Strain

Dose

-H

-R

MUTAGENIC ACTIVITY OF THE 10 TRIAZlblOINDOLE DERIVATIVES

TABLE 3

24_+ 2.0 20_+ 2.1 47_+ 4.6 176_+ 11.7 1610_+ 44.6 2317_+ 43.7 1254-+ 69.2 0.0001 ** 1

41-+ 6.4 582.+ 14.0 990+ 91.5 1857_+ 91.3 4272-+317.5 5476_+ 98.2 4416_+112.9 0.0001 ** 1

29-+ 2.6 46_+ 5.5 66_+ 4.1 569+ 56.2 626_+ 55.0 737_+ 23.9 3307+ 92.4 0.0001 ** 1

29_+ 4.9 23_+ 3.6 126.+ 8.4 2255-+ 5 1 . 5 5172_+ 88.8 6155_+ 8 7 . 5 1528-+ 41.3 0.0001 ** 1

10% $9

149_+ 8.9 234_+ 7.6 442_+ 15.3 531_+ 11.4 1646_+131.8 1884+105.8 2195+ 27,2 0.0001 ** 1

210_+ 14.3 440_+ 16.6 608-+ 13.7 608+ 3 5 . 1 705-+ 1 9 . 5 844_+ 2 4 . 3 1287_+ 3 3 . 3 0.0001 ** 1

161-+ 5.7 200+ 3.7 217+ 12.4 233-+ 9.4 197_+ 6.2 204+ 3.9 1346_+143.0 0.7711 0

19D+_ 12.9 634-+ 29.5 1049_+ 12.2 1892-+141.2 2143+ 29.2 2538+ 5 7 . 3 2432+ 89.4 0.0001 ** 1

0% $9

TAI00

244_+ 5.2 249_+ 2.5 281_+ 2.5 542+ 12.7 1 7 0 3 - + 2.6 1924_+100.6 1235_+ 96.7 0.0001 ** 1

231-+ 3.8 353+ 0.7 681-+ 21.4 1227_+139.7 1919-+383.6 2038_+ 53.0 2230+135.5 0.0001 ** 1

202+ 11.8 217_+ 9.9 302+ 1 4 . 9 508-+ 35.2 628_+ 44.7 618+ 45.5 1174-+ 98.7 0.0001 ** 1

185_+ 10.7 250-+ 8.3 582-+ 13.7 1341+_ 25.3 2863+ 47.8 2150-+ 72.0 667_+ 2 1 . 0 0.0001 ** 1

10% $9

370_+ 16.9 393_+ 8.7 555+ 41.8 565+ 2 8 . 5 760+ 5 1 . 5 845+ 5.8 3257+234.6 0.0001 ** 1

410+ 10.8 586+ 18.8 604-+ 52.4 604+ 2 9 . 9 597_+ 2 3 . 6 499+ 1 8 . 5 2525-+154.6 0.5502 0

961-+ 23.2 1040+ 2 9 . 3 1008+ 1 4 . 8 965-+ 1 8 . 7 1052+ 24.4 995+ 2 3 . 3 4026_+207.5 0.7259 0

231_+ 6.9 283-+ 33.3 294_+ 7.9 335_+ 9.7 437+ 1 5 . 0 599-+ 3 8 . 2 3033-+124.6 0.0001 ** 1

0% $9

TA102

578-+ 36.4 640_+ 35.6 640_+ 3.6 913_+111.0 1321+163.7 1446+136.6 761_+ 52.4 0,0001 ** 1

738-+ 38.4 845+ 37.7 998_+ 26.6 1073_+ 57.1 1442_+ 60.7 1301_+ 59.9 667+ 13.1 0.0001 ** 0

991+ 2.7 1121_+ 7.0 1208-+ 27.2 1378_+ 29.8 1388-+ 30.9 1528-+ 10.1 851-+ 27.7 0.0001 ** 0

448+ 26,4 622-+ 41.6 735_+ 44.6 874_+ 14.1 1041+ 16,5 1269+ 15.2 669+ 32.3 0.0001 ** 1

10% $9

0 0.006 0.02 0.06 0.2 0.6 Positive control Probability Activity class

0 0.015 0.05 0.15 0.5 1.5 Positive control Probability Activity class

0 0.01 0.03 0.1 0.3 0.9 Positive control Probability Activity class

0 0.001 0.003 0.01 0.03 0.09 Positive control Probability Activity class

-NHCOCH 3

-COOH

-COOCH 3

-OC6H 5

118± 4.8 126± 5.8 119+_ 2.5 111_+ 3.3 130± 20.9 135± 7.3 839± 38.6 0.1328 0

183+_ 10.7 422± 11.3 4894- 7.5 546± 8.5 535+_ 53.9 519+_ 5.6 980± 38.5 0.0184 1

181± 4.5 304± 24.9 818± 91.2 1469± 70.4 1616+ 24.0 2324+-111.4 1108+_ 29.8 0.0001 ** 1

94+ 7.8 236+ 23.8 364± 43.8 386+ 62.5 404+ 59.5 864+_ 27.0 825+_ 53.7 0.0001 ** 1

282+_ 12.1 273± 18.3 288+- 8.6 297± 8.7 351+_ 3.5 363_+ 14.6 1587+_ 2 0 . 5 0.0001 ** 0

130+_ 7.8 373± 14.4 734+_ 33.6 !141_+ 62.4 973± 34.8 1050-+ 25.4 307_+ 1 8 . 9 0.0003 ** !

281+ 14.1 707+- 46.5 1497± 35.6 2676_+ 39.4 3226±!01.3 3276± 44.6 1074_+ 92.5 0.0001 ** I

172+ 5.0 274+ 4.5 301± 5.6 340+- 9.0 422+ 8.1 446+_ 21A 761_+ 44.9 0.0001 ** 1

26+_ 5.2 33+- 1.5 31_+ 1.5 33_+ 0.3 36± 1.5 47± 2.1 1426±134.8 0.0001 ** 0

22+_ 3.5 163+_ 8.3 160± 8.0 170± 6.2 189± 1.5 190± 7.7 1557+_ 2 1 . 5 0.0027 * !

16± 1.0 41-1- 4.0 109_+ 0.6 :'72± 5.8 290_+ 6.2 419+- 14.7 1391+- 1 9 . 2 0.0001 ** !

17± 1.2 36± 2.6 106+_ 9.7 115+- 3.3 165+_ 5.5 337+ 3.1 916+ 8.6 0.0001 ** i

35± 1.0 35± 3.8 46+ 7.3 50± 6.4 56± !.2 63± 9.1 2021±142.4 0.0023 ** 0

38± 1.0 62+_ 7.5 121+_ 6.9 299± 17.7 491+ 48.1 606+_ 23.2 3591_+ 70.2 0.0004 * * 1

39 4. 2.3 86+ 4.6 244± 12.2 352___ 23.4 396± 5.9 903± 6.2 31184- 57.3 0.0O01 ** 1

47+ 4A 76± 4.9 84± 5.8 82± 9.8 105+_ 5.9 153+ 5.5 1735+ 6 5 . 5 0.0001 ** 1

146-1- 7.7 1564- 4.7 165± 5.2 177± 4.6 183± 0.9 190± 2.2 1508± 7 7 . 9 0.0001 ** 0

171± 6.1 309+_ 12.8 281± 6.9 283+_ 1.2 310± 8.5 284± 9.5 2108±290.7 0.3289 0

1464- 4.9 189± 11.3 300± 1 2 . 7 523+ 47.8 620___ 9.5 575± 3.6 2082± 90.6 0.0001 ** 1

167+ 4.2 198+ 4.4 225± 19.1 251± 20.3 338± 16.3 439± 23.3 1750±111.2 0.0001 ** 1

200+_ 2.3 180± 5.9 196± 2.9 216± 6.2 245± 9.2 285± 15.1 1385+115.0 0.0001 ** 0

224± 9.0 445± 12.1 1073_+ 36.1 1963+_ 75.9 1883+-101.2 2010±187.7 1841± 58.6 0.0001 * * 1

185± 4.2 619± 9.8 1220± 37.4 15474- 22.6 1215± 86.4 1563± 71.1 1584_+ 33.7 0.0001 ** 1

173± 4.2 237± 24.1 353+ 2.6 313± 11.9 334± 15.6 478± 49.7 1246± 59.0 0.0001 ** 1

476+ 15.6 663+ 28.0 678+ 21.1 680+ 22.1 666+ 20.0 793+ 15.2 817+ 28.9 0.0180 * 0 810+ 17.3 1610± 54.5 2718± 30.3 41604" 47.2 5 875 + 288.2 5999± 112.8 974± 36.7 0.0001 * * 1 864± 13.5 1070± 55.6 1447± 19.8 1800 ± 19.0 2353± 33.4 2415± 26.7 719± 31.8 0.0001 * * 1 1204 ± 36.7 1226 ± 35.4 1259± 57,6 1270 4- 34,4 1265 ± 22.3 1274± 79,6 1 168± i0.5 0,4228 0

349± 26.0 390± 10.7 487± 23.6 480± 29.2 535 ± 44.6 493 ± 8.6 3143 ± 245.6 0.0184 * 0 6024- 29.8 5944- 48.6 568-1- 18,2 624+ 24.8 6894. 10,9 747-1- 20.5 3 567 ± 283.1 0.0001 ** 0 3704. 22.0 607+ 10.8 575 ± 12.9 543 ± 11,5 427± 8.2 415 ± 4.4 5 494 4. 432.2 0.5512 0 980± 27.3 1001 ± 15.2 965 4. 25.4 971 ± 29.2 1016+ 31.1 977± 50.1 3 271 ± 482.3 0.9299 0

0 0.003 0.01 0.03 0.1 0.3 Positive control Probability Activity class

-OCH 3

205± 1 6 . 5 488-+ 24.0 696± 20.5 886-+ 1 2 . 3 1083-+ 52A 1616+ 79.1 1052_+ 22.3 0.0081 ** I

315+_ 5.2 2 9 6 - + 3_5 464+_ 21.6 903_+ 28.2 1092_+ 71.5 1326+ 53.1 743_+ 26.6 0.0081 ** 1

22_+ 1.2 138_+ 10.1 115_+ 6.9 149+ 11.0 201-+ 5.8 270_+ 7.9 1346_+ 30_5 0.0801 ** 1

21 _+ 1_5 24-+ 3.2 23_+ 2.1 21-+ 2.1 25-+ 1.8 26_+ 1.7 693-+ 1 1 . 2 0.0518 0

0% $9

10% $9 269_+ 2.9 283_+ 1.2 3 1 6 - + 3.5 3 2 7 - + 12.7 3 6 1 - + 4,3 393_+ ll,O 782_+ 27.2 0.0001 ** 0

0% $9

154_+ 7.3 149_+ 2.9 157-+ 1.5 157_+ 2.6 163_+ 6.4 154+ 6.6 941_+ 53.7 0.8314 0

TA97

(/zmol/plate)

0 0.006 0.02 0,06 0.2 0.6 Positive control Probability Activity class

TA98

Strain

Dose

-C6H 5

-R

TABLE 3 (continued)

45_+ 2.9 49_+ 6.2 98_+ 6.2 225-+ 8.9 338_+ 17.2 357_+ 9.5 1096+ 78.9 0.0001 ** !

24_+ 1.3 31_+ 4.7 28-+ 1.5 24-+ 1.7 34-+ 5.2 31_+ 7.2 1335-+ 34.5 0.3692 0

10% $9

148_+ 5.1 213+_ 2 0 . 5 281_+ 21.4 370-+ 6.5 475+ 1 1 . 3 456_+ 1 1 . 5 1069_+ 98.7 0.0001 ** 1

190+ 8.8 339_+ 21.9 239_+ 29.7 226_+ 7.9 264_+ 32.7 266_+ 7.4 1776_+ 65.7 0.6570 0

0% $9

TAI00 10% $9

174+ 4.9 174+ 9.5 264_+ 9.1 366+ 14.9 443_+ 4.7 529+ 24.7 1159± 1 4 . 7 0.0001 ** 1

266+ 4.9 268± 19.5 253± 21.0 255_+ 13.3 3204- 2.7 350± 18.2 838+112.2 0.0001 * * 0

624+ 16.7 675± 19.6 672_+ 22.9 629-+ 19.9 637_+ 23.7 633_+ 36.4 4351±543.9 0.1255 0

226-+ 19.2 216+ 10.1 249_+ 12.8 208_+ 23.8 277_+ 17.1 303_+ 10.1 6678±532.8 0.0009 * * 0

0% $9

TA102

905 + 19.0 977+ 12.5 975+ 35.9 1040 + 33.6 1285 + 4.7 1275 + 29.5 870± 24.2 0.0001 ** 0

839:t: 32.6 1010+ 22.3 1262 + 29.7 1 120+ 22.6 1208 + 18.2 1342+ 15.5 815+ 65.7 0.0002 * * 0

10% $9

7 and Komatsu, 1977; Moriguchi et al., 1980; Kawashima et al., 1986). T h e equation (discriminant function) is formulated by a feedback adaptation procedure in a linear form as Eq. 1, L

=

w o

+ w~xl + w2x 2 +

...

-I-WpXp

(1)

where L is the discriminant score for the classification, Xk (k ffi 1, 2 . . . p ) is the k th descriptor for the structure, and w k (k = 0, 1 . . . p) is the weight coefficient. The value of w~ is determined by the least-squares adaptation using the starting score aj ( j - - 1 , 2 . . . m in the m group case) and the correction term Ci(t). In this study the algorithm derived from ALS 81 was carried out using the computer program Data Desk ® (1988). Moriguchi (1980) proposed a modified 'ridit' as a standard numerical score for ordered categories. It is defined in Eq. 2, where a i is the ridit for group 'j', and n i and n i are the size of groups T and 'j', respectively. From Eq. 2, the mean value of a s over 'n' compounds becomes zero, and a~ --- - 1 and a2 = + 1 for two groups of the same size.

)]

ajffi 2 2 i ~ l n ~ + n j / n

-2

(2)

The choice of ridit as the numerical score is based on the assumption that only the potency order of groups is reliable, i.e., quantitative differences in potency between the different groups and between the different compounds within a group are uncertain in the data to be analyzed. In this study, for Eq. 4 (see Table 4), a I (assigned to class 0 ) = - 1 . 5 , a 2 (assigned to class 1) = 0.6 and the cutting point between classes bt2 ffi (a s + a 2 ) / 2 ffi - 0 . 4 5 ; for Eq. 5, al ffi - 1 . 6 , a , ffi 0.4 and bl2 ffi - 0 . 6 ; and for Eq. 6, a~ ffi - 1.2, a 2 ffi 0.8 and bx2 = - 0 . 2 . T h e procedure begins with the setting of forcing factors S i, which are taken to be S i ffi aj. By use of Si in place of L in Eq. 1 the ordinary least-squares estimate w k (k ffi 0, 1, 2 . . . p) to be used as the initial weight vector. Then L i for each substance is calculated from Eq. 1. All substances are classified on the basis of the values of

L i and the cutting point as follows: if L i _ b~2 then assign the i th substance to class 1. At iteration 2 and thereafter, the forcing factor ~i is adapted as S i = L i (when the i th substance is correctly classified) or Si = L i _ C~ (when misclassified), where sign ' _ ' is chosen to correspond with S i - L i. The correction term C i for the misclassified compound T at each iteration is given as Eq. 3 (Kawashima et ai., 1986).

Ci = 0.1/[0.1 + (0.45 + I L i - b12 I) 2]

(3)

From the new adapted Si, the least-squares estimate of w k is computed and the new Li is calculated from Eq. 1. The adaptation is repeated untill all substances are correctly classified or repeated a maximum of 40 times, and the best discriminant function is selected. The results of the ALS calculation were validated by the leave-one-out prediction (Stuper et al., 1978). The measure of the predictive ability is obtained by leaving out one compound and using the remaining compounds as the training set. The discriminant function developed from the training set is used to predict the potency class of the compound left out. This procedure is continued until each compound of the data set has been left out of the training set once. The predictive results were given as the misclassified number and the Spearman rank correlation coefficient for the overall leave-one-out classification. Results and discussion

The activities found for each one of the compounds tested with every strain, 0% $9 and 10% $9, the associate probability and the activity class assigned are shown in Table 3 (see Observed activity). The compounds and descriptors analyzed are listed in Table 1. The cross-correlation matrix of the descriptors analyzed by the ALS method is shown in Table 2. o-, F and R were not analyzed simultaneously, because they are related among themselves.

We only found discriminant fanctions with or. Three different equations were f o u n d in the analysis of the data, Eqs. 4, 5 and 6 (Table 4). Eq. 4 was obtained with strains TA97 0% $9 and TA98 0% $9, Eq. 5 with TA97 10% $9, TA98 10% $9 and TA100 10% $9, and Eq. 6 with TA100 0% $9. We could not find any quantitative relationship with strain TA102. In Eqs. 4 - 6 the figure in parentheses u n d e r the coefficient is the contribution index ( = [coef] x SD of descriptor), which is a measure of the contribution of the descriptor to the discriminant score (Moriguchi et al., 1980). In Table 4, below the equations, the mutagenic activities observed, recognized and predicted for every c o m p o u n d are listed. T h e 'observed' values were obtained from the mutagenicity results in Table 3 in every particular case. T h e 'recognised' values were calculated using Eqs. 4, 5 and 6. Finally, the 'predicted' value for each compound was calculated leaving the corresponding compound out and using the other 9 to obtain a new equation and predict the activity for the one left

out (see ALS method). Nmis is the n u m b e r of compounds misclassified and R s the Spearman rank correlation coefficient. As can be seen in the table, the resulting recognition and leave-one-out prediction in Eqs. 4 and 5 were excellent in terms of Rs. The recognition of Eq. 6 is reasonably good (Rs = 0.816, indicated by the significance level of 1%), but the prediction of Eq. 6 is poor (Rs = 0.583 with a significance level o f 8%). In all the equations found, the mutagenic activity is expected to be larger when the character of the substituent in 4' is less lipophilic (,r < 0). We could not find any quantitative relationship with the rest of the physicochemical parameters. Therefore, we could think about having the same kind of compounds with similar biological activity but with smaller or nonmutagenic activity, using a very lipophilic radical. The 1,2,3 triazin ring is probably the part of the molecule responsible for the mutagenicity of these compounds, as suggested by o u r previous results (Lopez-de-Cerain et al., 1990). A lipophilic

TABLE 4 RESULTS OF THE ALS RECOGNITION AND PREDICTION OF 10 DERIVATIVES WITH THE THREE DIFFERENT EQUATIONS OBTAINED

Eq. 4 Eq. 5 Eq, 6

L m 0.160 -0.889 ~" (0.916) * L - 0.183 -0.737 ~" (0.759) * L = -0.208-0.676 ~"

TA97 0% $9

TA98 0% $9

TA9710% $9

TA9810% S9 TAIO0 10% $9 TAI00 0% 59

(0.696) * R

H CI NOa OH NHCOCH3 COOH COOCH ~ OC~H 5 Coil5 OCH ~ Nmjs Rs

¢r

0 0.71 - 0.27 -0,67 - 0.97 - 0.32 - 0.01 2.08 1.96 - 0.02

Eq. 4

Eq. 5

Eq. 6

obs a

rec b

pre c

obs

rec

pre

obs

rec

pr¢

1 0 1 1 1 1 1 0 0 I

I 0 1 1 1 1 1 0 0 1

1 0 1 1 1 ! 1 0 0 1

1 1 1 1 1 1 1 0 0 1

1 1 1 1 1 1 1 0 0 1

1 1 1 1 1 1 1 0 0 1

1 0 1 1 1 1 0 0 0 1

0 0 l 1 1 1 0 0 0 1

0 0 1 1 1 1 l 0 0 1

0 I

0 1

0 1

0 1

l 0.82

2 0.58

* Contribution index (CI). a Observed values, b recognised values and c predicted values (see ALS method and Results and discussion).

substituent in 4' could make the wrapping of the 1,2,3-triazin ring feasible, preventing its mutagenic action. When a QSAR is applied, it is very important to be sure of the purity of the compounds because mutagenic contaminants can give falsepositive results. Also, tests must be performed using adequate procedures with appropriate controls and safety measures for quality control in the laboratory (Shahin, 1987). Both factors have been kept in mind when carrying out this study. QSARs are of great value in the design of less mutagenic compounds. In our case, the mutagenicity of the series tested, 3-(4-R-benzylidenamino)-SH-1,2,3-triazin[5,4-b ]indol-4-one, can be varied by manipulation of the lipophilic properties of the substituent in the 4' position. However, we should not forget that we are only considering how to modify the mutagenicity of the whole molecule with the character of the radical in the position 4', without taking into consideration the general environment of the compounds. References Arrar~s, J.A. (1990) Dissertation, Oniversidad de Nava,,a. Benigni. R.. C. Andreoli and A. Giuliani (1989) Quantitative structure-activity relationships: principles, and applications to mutagenicity and carcinogenicity, Mutation Res., 221, 197-216. Brosick, D., and A, Auletta (1985) Developmental status of bioassays in genetic toxicology. A report of Phase I! of the U.S. Environmental Protection Agency Gene-Tox Pro. gram, Mutation Res., 153, 1-10. Craig, P,N. (1990) Substructural analysis and compound selection, in: C. Hansch (Ed.), Comprehensive Medicinal Chemistry, Vol. 4, Pergamon, Oxford. Data Desk ~ Professional 2.0 (1988) Odesta Corporation, Northbrook, IL.

Fujita, T. (1990) the extrathermodynamic approach to drug design, in: C. Hansch (Ed.), Comprehensive Medicinal Chemistry, Vol. 4, Pergamon, Oxford. Garc~a, E., A. Lopez de Cerain, A. Gull6n, J.A. Arrarfis and A. Monge (1991) Submitted for publication. Hansch, C., and T. Fujita (1964) ro-cr-,rr Analysis. A method for the correlation of biological activity and chemical structure, J. Am. Chem. Soc., 86, 1616-1626. Hansch, C., and A. Leo (1979) Substituents Cons: .nts for Correlation Analysis in Chemistry and Biology, Wiley, New York. Kawashima, Y., F. Amaruma, M. Sato, S. Okuyama, Y. Nakashima, K. Sota and i. Muriguchi (1986) Structure-activity studies of 4,6-disubstituted 2-(morpholinocarbonyl) furo[3,2-b]indole derivatives with analgesic and antiinflammatory activities, J. Med. Chem., 29, 2284-2290. Lopez-de-Cerain, A., E. Garc[a, A. Gull6n, .Li. Recalde and A. Monge (1990) Mutagenic evaluation of some triazino indoles using the Salmonella/mammalian microsome assay, Mutagenesis, 5, 307-311. Maron, D.M., and B.N. Ames (1983) Revised methods for the Salmonella mutagenicity test, Mutation Res., 113, 173-215. Monge, A., V. Martinez-Merino, C. Sanmartin, F.J. Fern:~ndez, M.C. Ochoa, C. Bellver, P. Artigas and E. Feruandez-Alvarez (1989) 2-Arylamino-4-oxo-3,4-dihydropyrido[2,3-d]pyrymidines: synthesis and diuretic activity, Eur. J. Med. Chem., 24, 209-216. Moriguchi, !., and K. Komatsu (1977) Adaptive least-squares classification applied to structure-activity correlation of antitumor mitomycin derivatives, Chem. Pharm. Bull., 25, 2800-2802. Moriguchi, I., K. Komatsu and Y. Matsushita (1980) Adaptatire least-squares method applied to struc',ure activity correlation of hypotensive N-alkyI-N'-cyano-N'-pyridyl guanidines, J. Med. Chem., 23, 20-26. Shahin, M.M. (1987) Relationships between structure and mutagenic activity of environmental chemicals, Mutation Res., 181,243-256. Stuper, AJ., and P.C. Jurs (1978) Stru~ ture-activity studies of barbiturates using pattern recognition techniques, J, Pharm. Sci., 67, 745. Tute, M.S. (1990) History and objectives of quantitative drug design, in: C. Hansch, Comprehensive Medicinal Chemistry, Vol. 4, Pergamon, Oxford.