QSAR of Antimalarial Cyclic Peroxy Ketals II: Exploration of Pharmacophoric Site Using AM1 Calculations

QSAR of Antimalarial Cyclic Peroxy Ketals II:Exploration of Pharmacophoric Site Using AM1 Calculations

Kunal Roy1*, A.U. De2 and Chandana Sengupta2

1Division of Pharmaceutical Chemistry, Seemanta Institute of Pharmaceutical Sciences, Jharpokharia, Mayurbhanj 757 086 (Orissa), India2Drug Theoretics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology,

Jadavpur University, Calcutta 700 032, India

Abstract

A series of antimalarial cyclic peroxy ketals (n¼ 20) have

been subjected to energy minimization using AM1 method,

andWang–Ford charges of the non-hydrogen common atoms

(Figure 1), obtained from molecular electrostatic potential

surface of the energy minimized geometries, have been used

to model the antimalarial activity against P. falciparum. It is

found that the difference in charges between the peroxy

oxygens contribute positively to the activity, and this is in

good agreement with the mode of antimalarial action of the

peroxy compounds involving breakage of the peroxy bridge

by the haem-iron within the parasite. It is hypothesized that

difference in charges between two peroxy oxygens may

facilitate the bond breakage. It is further found that the

activity increases with increase in negative charge of the

methoxy carbon of the common fragment of the molecule.

This is related with possible secondary electronic interaction

with the positively charged side chains of the histidine rich

protein of P. falciparum. Attempt was made to incorporate

steric and indicator parameters which emerged as important

contributors from previous Hansch analysis. The present

results support the previous observations that bulky phenyl

ring substituents and a seven-member carbocylic ring

attached to the peroxy bridge-containing ring are conducive

to the activity.

1 Introduction

In view of increasing problems of drug resistance acquired by

malaria parasites, there is an urgent need for new drugs and

treatment strategies to face the challenge [1]. According to

recent statistics, malaria affects worldwide more than 200

million people of which 1–2 million people die every year

[2]. In this context, artemisinin, an endoperoxide sesquiter-

pene lactone, originally obtained from leaves and inflore-

sences of chinese herb Artemisia annua L., has attracted

attention because of its potential value as antimalarial drug,

even against Plasmodium falciparum, the most pernicious

malarial parasite [3–6]. Artemisinin and its derivatives,

artesunate and artemether, meet the dual challenge posed

by drug-resistant parasites and rapid progression of malarial

illness [7, 8]. Artemisinin type compounds show excellent

efficacy in both severe and uncomplicated malaria with no

evidence to date of serious clinical toxicity [7, 9, 10].

Artemisinin derivatives have an unusual mode of action

involving free radicals, and the endoperoxide bridge is

essential for the biological activity [11, 12].Malaria parasites

digest haemoglobin and most of the haem, which is released

in the lysosomal digestive vacuole during haemoglobin

degradation, is incorporated into haemozoin (malaria pig-

ment) by haematin polymerization process [13–15]. Plasmo-

dium falciparum histidine rich protein 2 (PfHRP2), a 30 kDa

protein composed of several His-His-Ala-His-His-Ala-Ala-

Asp repeats and present in parasite food vacuole, binds with

haem and plays a key role in the formation of haemozoin

[16, 17]. Artemisinin has a very high affinity for haemozoin

present within the parasites leading to highly selective

accumulation of the drug in the parasites [18, 19]. Intra-

parasitic haem-iron catalyzes the cleavage of endoperoxide

bridge and generation of carbon-centered free radicals which

subsequently alkylate essential malarial proteins [2, 11–13,

20–22]. The importance of peroxide bridge is further con-

firmed by the observation that catalytic reduction of the

peroxide bridge, resulting in loss of one oxygen of the

peroxide bridge, causes loss of antimalarial activity [23].

The encouraging efficacy of the peroxidic artemisinin type

antimalarials and understanding of their mechanism of action

that occurs through free radical process have drawn attention

of the researchers to consider peroxy ketals as prospective

antimalarial compounds. Recently, Posner et al. have

*To receive all correspondence at address: Cyo Dr. A.G. Saha, Flat No. 2E,8, Dr. Ashutosh Sastry Road, Calcutta 700 010, India.

E-mail: [email protected]

Key words: QSAR, AM1 calculations, antimalarials, cyclic peroxy

ketals, Hansch analysis

Quant. Struct.-Act. Relat., 20 (2001) # WILEY-VCH Verlag GmbH, D-69469 Weinheim 0931-8771/01/0411-0319 $17.50+.50/0 319

QSAR of Antimalarial Cyclic Peroxy Ketals II QSAR

reported [24] a series of antimalarial peroxy ketals (Figure 1).

We have reported QSAR of the compounds using physico-

chemical and electrotopological parameters in a previous

communication [25]. Two of the equations obtained from the

study are given below

pC ¼ 0:597ð�0:223Þsþ 0:161ð�0:163ÞMR

þ 0:169ð�0:148ÞI � 2:335ð�0:154Þ

n ¼ 18;R2a ¼ 0:740; R ¼ 0:887; SEE ¼ 0:142;

F ¼ 17:1; AVRES ¼ 0:110 ð1Þ

pC ¼ 0:570ð�0:251Þsþ 0:416ð�0:545ÞVw

þ 0:168ð�0:154ÞI� 2:339ð�0:180Þ

n ¼ 18;R2a ¼ 0:713; R ¼ 0:874; SEE ¼ 0:149;

F ¼ 15:1; AVRES ¼ 0:113 ð2Þ

The physicochemical parameters included in the above

equations (Hammett s, molar refractivity MR and van der

Waals volume Vw) represent the parametric values of 4-

substituents on the phenyl ring. The indicator parameter I

represents presence of a seven membered alicyclic ring

attached to the peroxy bridge containing ring. The regression

coefficients of the above equations are significant at 95%

level except those of MR (significant at 90% level) and Vw

(significant at 80% level). The study [25] revealed that

electron withdrawing and bulkier phenyl ring substituents

and seven-member alicycle ring attached to peroxy bridge

containing ring are preferred for the activity. Further, QSAR

with electrotopological index suggested a pharmacophore

containing the peroxy bridge [25]. In the present commu-

nication, we have attempted to further explore QSAR of the

compounds using quantum mechanical method.

2 Materials and Methods

The biological activity values and structural features of the

compounds are presented in Table 1. Two compounds

(1 and 8) that could not be included in the previous study

because of unique structural features [25] were also included

in the present study. Quantum mechanical calculations were

done according to AM1 (Austin Model 1) [26–28] method

using Chem 3D Pro [29] package. The structure of the

compound 2 was drawn in Chem Draw Ultra ver 5.0 [29]

and it was copied to Chem 3D ver 5.0 [29] to create the 3-D

model which was saved as the template model. The non-

hydrogen common atoms of the compounds were given a

serial number in the template model so that these maintain

same serials in all the models. For every compound, the

template model was suitably changed considering its struc-

tural features, and finally the model was ‘cleaned up’. Next,

energy minimization was done under MOPAC module using

RHF (restricted Hartree–Fock: closed shell) wave function.

The energy minimized geometry was used for calculation of

Wang–Ford charges (obtained from molecular electrostatic

potential surface) of different atoms.

The charges (qx) of different atoms (x) were subjected to

intercorrelation study. The biological activity data of the

compounds were subjected to regression with the charges of

different atoms and also different combinations of them

to obtain best univariate, bivariate and trivariate relations

(involving one, two and three predictor variables respec-

tively) using the program AUTOREG [30] developed by one

of the authors. For the bivariate and trivariate relations, only

those predictor variables with less intercorrelation (r< 0.7)

were considered. Further, bivariate and trivariate relations

having correlation coefficients higher than those of the best

univariate and best bivariate equations respectively were

only recorded.

Finally, important physicochemical and indicator parameters

as emerged from the previous Hansch analysis [25] were

incorporated in the equations involving charge parameters.

The steric parameters of the aromatic substituents [31, 32] are

listed in Table 2.

The regression analyses were carried out using a GW-BASIC

program RRR98 [30]. The statistical quality of the equations

[33] was judged by the parameters like explained variance

(R2a ; i.e., adjusted R2), correlation coefficient (R), standard

error of estimate (SEE), average of absolute values of the

residuals (AVRES), variance ratio (F) at specified degree of

freedom (df) and ‘t’ values of the regression coefficients. Use

of more than one variable in a multivariate equation was

justified by intercorrelation study. All the accepted equations

have regression constants and F ratios significant at 95% and

99% levels respectively, if not stated otherwise. The stability

and predictive capacity of the best equation was cross-

validated from PRESS statistics (Q2, i.e., cross-validated

R2) using leave-one-out technique [34]

running KRPRES1 and KRPRES2 programs [30].

3 Results and Discussion

The Wang–Ford charges of different non-hydrogen common

atoms of cyclic peroxy ketals are given in Table 3 while the

intercorrelation among the charges is listed in Table 4.

Table 5 lists statistical parameters of univariate and selected

bivariate and trivariate relations of the antimalarial potency

with Wang–Ford charges of different atoms. The energy-

Figure 1. General structure of antimalarial cyclic peroxide ketals:the non-hydrogen common atoms are numbered 1 through 14.

QSAR Kunal Roy, A.U. De and Chandana Sengupta

320 Quant. Struct.-Act. Relat., 20 (2001)

minimized geometry of the most active compound of the

series (compound 13) is given in Figure 2.

The best univariate relation involves charge of atom 13 (one

oxygen of the peroxide bridge). The equation explains 55.5%

of the variance and regression coefficient of q13 is significant

at 95% level.

pC ¼ �16:850ð�7:125Þq13 � 6:409ð�1:822Þ

n ¼ 20;R2a ¼ 0:555; R ¼ 0:760; SEE ¼ 0:229; F ¼ 24:7

ð3Þ

The 95% confidence intervals of the regression coefficients

are given within parentheses. Eq. 3 suggests that the activity

increases with increase in negative charge of the atom 13.

On inclusion of the second parameter, charge (q8) of atom 8

(methoxy carbon of the common fragment), the best bivariate

relation, explaining 60% of total variance, was obtained:

pC ¼ �16:224ð�6:751Þq13 � 7:230ð�8:216Þq8

� 6:686ð�1:746Þ

n ¼ 20;R2a ¼ 0:608;R ¼ 0:806; SEE ¼ 0:215; F ¼ 15:7

ð4Þ

Table 1. Structural features, and observed, calculated and predicted antimalarial activity of cyclic peroxy ketals

1�20

In vitro antimalarial activity against P. falciparuma)

Structural features pCb)

Compd. No. R1 R, R IC50(nM) Obs. Calc. Res. Pred. Pres.

1 H Me, Me 1100 �3.041 �2.893 �0.148 �2.798 �0.243

2 H cyclopentyl 190 �2.279 �2.268 �0.011 �2.267 �0.012

3 H cyclohexyl 280 �2.447 �2.268 �0.179 �2.248 �0.199

4 H cycloheptyl 220 �2.342 �2.127 �0.215 �2.064 �0.278

5 4-MeO cyclobutyl 160 �2.204 �2.517 0.313 �2.572 0.368

6 4-MeO cyclohexyl 180 �2.255 �2.371 0.116 �2.385 0.131

7 4-MeO cycloheptyl 210 �2.322 �2.349 0.027 �2.359 0.037

8 3,4,5-(MeO)3 cycloheptyl 120 �2.079 �2.008 �0.071 �1.885 �0.195

9 4-CF3O cycloheptyl 61 �1.785 �1.886 0.101 �1.905 0.120

10 4-Cl cycloheptyl 58 �1.763 �1.741 �0.022 �1.736 �0.027

11 4-F cycloheptyl 85 �1.929 �1.961 0.032 �1.966 0.037

12 4-MeS cycloheptyl 78 �1.892 �2.091 0.199 �2.131 0.239

13 4-MeSO2 cycloheptyl 31 �1.491 �1.440 �0.051 �1.415 �0.076

14 4-Et cycloheptyl 180 �2.255 �2.254 �0.001 �2.254 �0.001

15 4-MeS cyclohexyl 160 �2.204 �2.228 0.024 �2.230 0.026

16 4-MeSO2 cyclohexyl 56 �1.748 �1.882 0.133 �1.925 0.177

17 4-O2N cyclohexyl 46 �1.663 �1.846 0.183 �1.891 0.228

18 4-Cl cyclohexyl 100 �2.000 �1.857 �0.143 �1.828 �0.172

19 4-F cyclohexyl 200 �2.301 �2.095 �0.206 �2.059 �0.242

20 4-CF3 cyclohexyl 140 �2.146 �2.064 �0.082 �2.055 �0.091

a) Taken from Ref. 24.b) pC¼ log (1yIC50).

Obs.¼Observed, Calc.¼Calculated according to Eq. 7, Res.¼Obs.–Calc., Pred.¼Predicted applying leave-one-out technique on Eq. 7,

Pres.¼Obs.7Pred.

Table 2. Steric parametersa) of the aromatic substituents (R1)

R1 MRb) Vw (102 A3)

H 0.103 0.056

MeO 0.787 0.304

CF3O 0.786 0.442

Cl 0.603 0.244

F 0.092 0.115

MeS 1.382 0.423

MeSO2 1.349 0.539

Et 1.030 0.399

NO2 0.736 0.276

CF3 0.502 0.383

a) Molar refractivity values are taken from Ref. 31 and van der Waals

volume values are calculated according to Ref. 32.b)Molar refractivity values are scaled to a factor of 0.1 as usual.


Quant. Struct.-Act. Relat., 20 (2001) 321

The parameters, q8 and q13 are not much intercorrelated (r¼

0.11, Table 4). However, the coefficient of the parameter q8was significant only at 90% level. Eq. 4 suggests that, for

better activity, charges of both atoms, 8 and 13, should be

more negative.

The best trivariate relations involve atom 14 (the

other oxygen of the peroxy bridge) in addition to

atoms 13 and 8. There is tangible increase in statistical

quality in the equation in comparison to the best bivariate

Eq. 4.

Table 3a. Wang–Ford charges (qx) of the non-hydrogen common atoms of antimalarial cyclic peroxy ketals obtained from molecularelectrostatic potential surface of energy minimized geometry (Part I)

Atoms (x)

Compd. No. 1 2 3 4 5 6 7

1 �0.09787 �0.07966 �0.16193 0.06331 �0.05851 �0.13046 �0.30214

2 �0.11088 �0.06860 �0.19492 0.14191 �0.08913 �0.11933 �0.28223

3 �0.10776 �0.07163 �0.18153 0.10714 �0.08927 �0.11674 �0.29933

4 �0.10354 �0.07438 �0.17758 0.09727 �0.08095 �0.12242 �0.30039

5 0.33592 �0.27524 �0.03122 �0.08864 �0.04993 �0.21786 �0.32830

6 0.34080 �0.27884 �0.02646 �0.0994 �0.05076 �0.22146 �0.33471

7 0.34035 �0.27922 �0.02272 �0.10591 �0.04849 �0.22189 �0.33959

8 �0.06234 0.37010 �0.32774 �0.04878 �0.18909 0.23059 �0.31932

9 0.25954 �0.16235 �0.12699 0.02689 �0.05481 �0.19770 �0.31327

10 �0.20273 0.07362 �0.25889 0.21196 �0.16355 0.02890 �0.28571

11 0.24144 �0.18195 �0.12495 0.02179 �0.04734 �0.21594 �0.30761

12 �0.00694 �0.12938 �0.14832 0.08189 �0.19246 �0.00568 �0.32320

13 �0.58792 0.03674 �0.19017 0.17980 �0.10447 �0.00203 �0.29325

14 0.04244 �0.12433 �0.14727 0.04069 �0.07101 �0.14454 �0.30577

15 �0.00676 �0.12834 �0.15710 0.10087 �0.19573 �0.00918 �0.32154

16 �0.58324 0.03164 �0.18845 0.18522 �0.1025 �0.00840 �0.29562

17 �0.16325 0.00003 �0.20622 0.19518 �0.11475 �0.04562 �0.28624

18 �0.20385 0.07377 �0.26310 0.22751 �0.17109 0.03040 �0.28354

19 0.23608 �0.17803 �0.13119 0.03633 �0.05939 �0.20872 �0.30717

20 �0.18402 0.01037 �0.21999 0.18714 �0.13168 �0.03062 �0.29318

Table 3b. Wang–Ford charges (qx) of the non-hydrogen common atoms of antimalarial cyclic peroxy ketals obtained from molecularelectrostatic potential surface of energy minimized geometry (Part II)

Atoms (x)

Compd. No. 8 9 10 11 12 13 14

1 �0.04644 0.14831 �0.10391 �0.16484 0.20435 �0.20778 �0.15378

2 �0.06190 0.04162 �0.10042 �0.17197 0.28197 �0.23415 �0.13165

3 �0.05092 0.10868 �0.10199 �0.19100 0.28804 �0.25597 �0.13971

4 �0.04821 0.11363 �0.08817 �0.20029 0.28423 �0.25451 �0.14055

5 �0.05672 0.26759 �0.13060 �0.16363 0.26334 �0.23886 �0.15690

6 �0.06076 0.29879 �0.14174 �0.16255 0.26475 �0.25756 �0.16482

7 �0.04908 0.30710 �0.13850 �0.15855 0.24985 �0.25441 �0.16565

8 �0.10032 0.39182 �0.11438 �0.19945 0.28252 �0.25772 �0.19621

9 �0.07421 0.19057 �0.11449 �0.17381 0.26032 �0.25334 �0.14583

10 �0.06173 0.02259 �0.10906 �0.16391 0.27929 �0.25819 �0.11929

11 �0.06931 0.17960 �0.13485 �0.15130 0.25808 �0.25191 �0.14644

12 �0.05451 0.20697 �0.12928 �0.17040 0.26708 �0.25795 �0.14801

13 �0.06155 0.02261 �0.04868 �0.22113 0.34167 �0.28504 �0.11328

14 �0.04716 0.15316 �0.08848 �0.20608 0.29635 �0.26561 �0.14312

15 �0.05611 0.19173 �0.14838 �0.15602 0.28240 �0.26021 �0.14613

16 �0.04663 0.01353 �0.05410 �0.20867 0.32097 �0.27605 �0.11248

17 �0.07019 0.04918 �0.13938 �0.14257 0.28576 �0.26099 �0.12307

18 �0.06275 0.00794 �0.12397 �0.15523 0.29479 �0.26280 �0.11672

19 �0.07104 0.17281 �0.14696 �0.14601 0.27115 �0.25532 �0.14549

20 �0.05915 0.07131 �0.13264 �0.15342 0.28319 �0.25771 �0.12962



pC¼ 7:040ð�5:174Þq14 �12:319ð�6:356Þq13

�12:042ð�7:755Þq8 �4:981ð�2:116Þ

n¼ 20;R2a ¼ 0:726; R ¼ 0:877; SEE¼ 0:180; F¼ 17:8

ð5Þ

All the coefficients of Eq. 5 are significant at 95% level and

the parameters show acceptable intercorrelation (Table 6).

Interestingly, coefficient of the variable q14 is positive while

those of q8 and q13 are negative. This suggests that the atom

14 should have less negative charge, while higher negative

charges on the other two atoms (8 and 13) are desired. This

implies that there should be a charge separation between the

two oxygens (atoms 13 and 14) of the peroxy bridge.

Accordingly, a new equation was constructed involving a

parameter q13–14 that denotes difference in charge of the two

peroxy oxygens:

pC ¼ �9:308ð�2:993Þq13�14 � 13:818ð�7:040Þq8

� 3:998ð�0:602Þ

n ¼ 20; R2a ¼ 0:721; R ¼ 0:866; SEE ¼ 0:181;

F ¼ 25:6;AVRES ¼ 0:141 ð6Þ

The statistical quality of the above equation is comparable to

that of Eq. 5. This confirms that charge separation across the

peroxy bridge may play an important role for the biological

activity. This may also be correlated with the mechanism of

action of the peroxy antimalarials that the peroxy bridge is

broken by the intraparasitic iron generating free radicals that

alkylate essential malarial proteins [2, 11–13, 20–22]. The

difference in charges between two oxygens may facilitate the

attack by haem iron and subsequent bond breakage leading to

the antimalarial activity.

The negative coefficient of the parameter q8 suggests that

there may be involvement of secondary electronic force with

some electron deficient centre on the parasitic protein surface

that may help the compounds to anchor with the parasitic

protein. Considering the presence of histidine rich protein

that is bound with haem inside malaria pigment (haemozoin)

[16, 17], and histidine side chain being positively charged at

pH 6.0 [35–37], it may be hypothesized that there is possi-

bility of ion–dipole interaction between the positively

charged imidazole ring of histidine side chain of haemozoin

and electron rich methoxy group on the peroxy bridge

containing ring of the compounds.

In the next step, attempt was made to incorporate the

parameters that emerged as important contributors from

the previous Hansch analysis [vide supra; Eqs. 1 and 2] [25].

On inclusion of the parameter I, denoting presence or absence

of seven membered alicyclic ring attached to the peroxy

bridge containing ring, following relation was obtained:

pC ¼ �9:213ð�2:603Þq13�14 � 11:540ð�6:398Þq8

þ 0:194ð�0:159ÞI � 3:927ð�0:495Þ

n ¼ 20;R2a ¼ 0:791; R ¼ 0:908; SEE ¼ 0:157;

F ¼ 25:0;AVRES ¼ 0:113 ð7Þ

Table 4. Intercorrelation among Wang–Ford charges of different non-hydrogen common atoms of antimalarial cyclic peroxy ketals

atom no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1 1.00 0.67 0.68 0.81 0.45 0.65 0.71 0.14 0.73 0.73 0.52 0.66 0.41 0.67

2 1.00 0.94 0.49 0.65 0.92 0.51 0.50 0.24 0.37 0.37 0.42 0.26 0.10

3 1.00 0.67 0.69 0.86 0.69 0.42 0.43 0.31 0.24 0.39 0.20 0.27

4 1.00 0.47 0.47 0.89 0.15 0.93 0.38 0.08 0.51 0.30 0.87

5 1.00 0.87 0.20 0.27 0.14 0.06 0.02 0.33 0.32 0.11

6 1.00 0.33 0.41 0.16 0.25 0.31 0.44 0.34 0.08

7 1.00 0.02 0.90 0.44 0.10 0.41 0.09 0.77

8 1.00 0.34 0.27 0.13 0.05 0.11 0.38

9 1.00 0.48 0.10 0.48 0.23 0.96

10 1.00 0.88 0.56 0.30 0.43

11 1.00 0.57 0.40 0.07

12 1.00 0.86 0.55

13 1.00 0.37

14 1.00

Figure 2. Energy minimized geometry of compound 13 (the mostactive compound of the series).



Positive coefficient of the parameter I in Eq. 7 suggests that

presence of a seven membered alicyclic ring is conducive to

the activity.

When steric parameter,P

MR (sum of molar refractivity of

the phenyl ring substituents including hydrogen), was used

instead of I in Eq. 7, the following relation was obtained:

pC ¼ �8:856ð�2:813Þq13�14 � 11:380ð�7:013Þq8

þ 0:145ð�0:153ÞP

MR � 3:966ð�0:547Þ

n ¼ 20;R2a ¼ 0:763; R ¼ 0:895; SEE ¼ 0:167;

F ¼ 21:4;AVRES ¼ 0:128 ð8Þ

Eq. 8 was, statistically, slightly inferior to Eq. 7. The

coefficient ofP

MR is significant at 90% level.

When other steric parameterP

Vw (sum of van der Waals

volume of the phenyl ring substituents including hydrogen)

was used instead ofP

MR; statistical quality further

deteriorated, though marginally.

pC ¼ �8:797ð�2:907Þq13�14 � 10:599ð�7:738Þq8

þ 0:378ð�0:458ÞP

Vw � 3:946ð�0:599Þ

n ¼ 20;R2a ¼ 0:751; R ¼ 0:889; SEE ¼ 0:171;

F ¼ 20:2;AVRES ¼ 0:132 ð9Þ

The coefficient ofP

Vw is significant at 90% level. Positive

contributions of the termsP

MR andP

Vw in Eqs. 8 and 9

respectively imply that size of the phenyl ring substituents

contribute positively to the activity suggesting possibility of

dispersion interaction. These observations are in good agree-

ment with the results of previously reported Hansch analysis

[25]. It may be mentioned here that Kim et al., also observed

remarkable influence of steric and electronic effects of the

substituents attached to the peroxide ring on the antimalarial

activity of some cyclic peroxides, 1,2,4,5,7-pentoxocanes

and 1,2,4,5-tetroxanes [38].

Knowing that a twenty-member data set is not regressable

with four predictor variables, a preliminary attempt was

made to include steric term in Eq. 7 and the following

relations were obtained:

Table 5. Statistical quality of univariate, selecteda) bivariate and trivariate relations of the antimalarial activity of the cyclic peroxy ketalswith Wang–Ford charges of different non-hydrogen common atoms

Atom no(s).b) R Ra2 FH SEE Atom no(s).b) R Ra

2 Fc) SEE

1 0.364 0.084 2.8 0.328 2 0.288 0.032 1.6 0.338

3 0.252 0.012 1.2 0.341 4 0.383 0.099 3.1 0.326

5 0.324 0.056 2.1 0.334 6 0.348 0.072 2.5 0.331

7 0.237 0.004 1.1 0.343 8 0.345 0.070 2.4 0.331

9 0.313 0.048 2.0 0.335 10 0.214 �0.007 0.9 0.344

11 0.160 �0.029 0.5 0.348 12 0.668 0.416 14.5 0.262

13 0.760 0.555 24.7 0.229 14 0.458 0.166 4.8 0.313

1, 13 0.763 0.533 11.8 0.235 2, 13 0.766 0.539 12.1 0.233

3, 13 0.768 0.541 12.2 0.233 4, 13 0.778 0.559 13.0 0.228

5, 13 0.766 0.537 12.0 0.233 6, 13 0.766 0.538 12.1 0.233

7, 13 0.778 0.560 13.1 0.228 8, 13 0.806 0.608 15.7 0.215

9, 13 0.774 0.552 12.7 0.230 10, 13 0.761 0.529 11.7 0.236

11, 13 0.777 0.557 13.0 0.229 13, 14 0.783 0.568 13.5 0.226

1, 8, 13 0.814 0.600 10.5 0.217 2, 8, 13 0.807 0.586 10.0 0.221

3, 8, 13 0.806 0.584 9.9 0.221 4, 8, 13 0.835 0.640 12.2 0.206

5, 8, 13 0.806 0.584 9.9 0.221 6, 8, 13 0.806 0.584 9.9 0.221

7, 8, 13 0.824 0.619 11.3 0.212 8, 9, 13 0.848 0.666 13.6 0.198

8, 10, 13 0.809 0.590 10.1 0.220 8, 11, 13 0.813 0.600 10.4 0.218

8, 13, 14 0.877 0.726 17.8 0.180

a) Selected bivariate and trivariate relations involving charges of the atoms that are not much intercorrelated (r< 0.7) and having correlation coefficients

higher than those of the best univariate and bivariate equations respectively are shown.b) Wang–Ford charges of the atoms or combination of atoms shown are used to derive univariate, bivariate and trivariate relations.c) df¼ np, n7 np7 1; n¼ no. of data points (¼ 20); np¼ no. of predictor variables.

Table 6. Intercorrelation (r) among antimalarial activity andimportant charge, physicochemical, and indicator parameters

parameter pC q8 q13 q14 q13–14P

MRP

Vw I

pC 1.00 0.35 0.76 0.46 0.71 0.45 0.48 0.38

q8 1.00 0.11 0.38 0.21 0.34 0.47 0.29

q13 1.00 0.37 0.77 0.51 0.52 0.21

q14 1.00 0.88 0.26 0.26 0.20

q13–14 1.00 0.09 0.09 0.03P

MR 1.00 0.95 0.24P

Vw 1.00 0.27

I 1.00



pC ¼ �8:847ð�2:465Þq13�14 � 9:757ð�6:303Þq8

þ 0:173ð�0:150ÞI þ 0:120ð�0:136ÞP

MR

� 3:908ð�0:503Þ

n ¼ 20; R2a ¼ 0:820; R ¼ 0:926; SEE ¼ 0:146;

F ¼ 22:7; AVRES ¼ 0:109 ð10Þ

pC ¼ �8:809ð�2:556Þq13�14 � 9:151ð�6:921Þq8

þ 0:176ð�0:154ÞI þ 0:305ð�0:408ÞP

Vw

� 3:892ð�0:558Þ

n ¼ 20; R2a ¼ 0:810; R ¼ 0:922; SEE ¼ 0:150;

F ¼ 21:2; AVRES ¼ 0:111 ð11Þ

The coefficients ofP

MR andP

Vw in Eqs. 10 and 11

respectively are significant at 90% and 80% levels in that

order.

Using the parameterP

MR instead of q8 in Eq. 7, the

following relation was obtained:

pC ¼ �7:911ð�3:023Þq13�14 � 0:188ð�0:163ÞP

MR

þ 0:225ð�0:185ÞI � 3:310ð�0:399Þ

n ¼ 20; R2a ¼ 0:709;R ¼ 0:869; SEE ¼ 0:185;

F ¼ 16:4; AVRES ¼ 0:137 ð12Þ

Considering all statistical parameters, Eq. 7 appears to be the

most acceptable equation for the series and calculated bio-

logical activity values according to Eq. 7 along with corre-

sponding residuals are given in Table 1. The statistical

quality of Eq. 7 is slightly better than the equations involving

only physicochemical parameters reported earlier [25]. The

intercorrelation among the physicochemical, indicator and

important charge parameters are given in Table 6. The

stability of the equation is also checked by PRESS statistics

as listed in Table 7. The predicted residual (Pres) value for

each compound is given in Table 1. The PRESS statistics

suggest that the Eq. 7 is of sound statistical quality and

stability. However, more compounds need be incorporated in

the data set to include the steric parameter of the phenyl ring

substituents and to get a robust equation for the series of

compounds.

References

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Table 7. PRESS statistics of Eq. (7)

Model equation: pC ¼ b1q13�14 þ b2q8 þ b3I þ a

Averagea) regression coefficients (standard deviation) PRESS statistics

b1 b2 b3 a Q2

(sd) (sd) (sd) (sd) (Average Pres)b)

�9.187 �11.580 0.194 �3.926 0.720

(2.637) (3.910) (0.066) (1.211) (0.145)

a)n¼ 20b)Q2 denotes cross-validated R2. Pres means predicted residuals.



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Received on July 16, 2001; accepted on September 11, 2001



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QSAR of Antimalarial Cyclic Peroxy Ketals II: Exploration of Pharmacophoric Site Using AM1 Calculations