[CANCER RESEARCH 52. 4121-4129. August 1. 1992]

Structure-Activity Study and Design of Multidrug-resistant Reversal Compounds

by a Computer Automated Structure Evaluation Methodology

Gilles Klopman, Sanjay Srivastava, Istvan Kolossvary, Raquel F. Epand, Nadeem Ahmed, and Richard M. EpandChemistry Department, Case Western Reserve University, Cleveland, Ohio 44106 ¡G.K., S. S., I. K.], and Department of Biochemistry, McMaster University,Hamilton, Ontario L8N 3Z5, Canada ¡R.F. E., N. A., R. M. E.]

ABSTRACT

We have studied the relation between the structure and the multidrugresistance-reversal activity of a set of diverse chemicals with the MUL-TICASE structure-activity program. A number of key structural features were identified as being related to multidrug resistance reversalactivity. Using these key features, we identified seven new compoundspredicted to have substantial activity. These were obtained and testedexperimentally on a CHO/CHRC5 cell line derived from the AB, Chi

nese hamster ovary line in the presence of vincristine and vinblastine. Ofthe seven compounds tested so far, four showed substantial reversalactivity, the most potent of them exhibiting activity at par with verap-

amil.

INTRODUCTION

Chemotherapy is often an effective treatment of human cancer. However, the tendency to relapse, which is a commonoccurrence in any kind of chemotherapy, has been known torestrict the effectiveness of a cancer cure and is often accompanied by a development of drug resistance ( 1, 2). This leads to analmost total lack of response to the cytotoxic drug. Furthermore, once cancer cells become resistant to one drug they oftenshow resistance to a large variety of other cytotoxic drugs aswell (3, 4). This phenomenon has come to be referred to asmultidrug resistance. Since its discovery, a number of cell lineshave been found to exhibit MDR1 (5-8). In most cases, thecross-resistance profile has been shown to accompany a concurrent decrease in the drug accumulation in the cancerous cell(5, 9). A number of factors could be responsible for the loweraccumulation of drug. It could be due to an enhancement of theactivity of an energy-dependent drug efflux mechanism such asthe P-glycoprotein (8, 10, 11). This increased efflux activitycould be due to increased expression of this protein, to analteration of the membrane environment of the protein, or tochanges in the degree of posttranslational modification of theprotein, such as phosphorylation. In addition, several MDR celllines have been shown to exhibit drug transport defects withoutoverexpressing the P-glycoprotein (12-20). The drugs to whichthese non-P-glycoprotein MDR cells are resistant are very similar to those to which MDR cells that overexpress the P-glycoprotein are resistant. There thus appears to be distinct paths bywhich cells can attain multidrug resistance.

A logical approach to designing reversers of MDR would beto elucidate the detailed conformation of the P-glycoprotein ina membrane and to determine the drug-binding site. Inhibitorswhich bind to this site could then be designed. However, thereare a number of problems in putting this approach into practice.There has been very limited success in obtaining detailed three-

Received1/24/92;accepted5/12/92.The costs of publication of this article were defrayed in part by the payment of

page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1The abbreviations used are: MDR, multidrug resistance; DMSO, dimethylsulfoxide; D,o, drug concentration which reduced cloning efficiency to approximately 10% of that in the absence of any drug; PBS, phosphate-buffered saline;QSAR, quantitative structure-activity relationship.

dimensional structural information of membrane-bound proteins by either X-ray diffraction or by nuclear magnetic resonance spectroscopy. Furthermore, it is often not a simple, directprocedure to design active site inhibitors even for proteinswhose crystallographic structure is known. In addition, theremay be mechanisms to reverse MDR which are independent ofthe P-glycoprotein expression. Thus, MDR is a complex phenomenon with many potential targets such as P-glycoproteinitself, processes which affect the membrane environment ofP-glycoprotein, enzymes such as protein kinases which causeposttranslational modification of the P-glycoprotein, vacuolarH+-ATPases (21) and others. An alternative to designing adrug for a specific molecular target is to take a systematic,empirical approach through computer analysis of drug structure-activity relationships. To evaluate the activity of the agentswhich reverse MDR, we have chosen a clonogenic assay whichshould be independent of the mechanism of action of the drugswhich are active reversers by measuring their effects on drugaccumulation in resistant cells. By selecting the common features of those compounds known to reverse MDR, one canbegin to predict new compounds which will act as reversers andto optimize their activity.

There have been a number of studies attempting to elucidatethe structural requirements for drugs that reverse MDR (22-26). These studies have focused on optimizing the activity of aparticular class of compounds in reversing MDR. No study hasattempted to integrate data on the large and diverse list of drugsthat act as sensitizers in reversing MDR. It is difficult to findstructural features which are common to a large number ofsensitizers because of their structural diversity. It has been suggested that reversers are hydrophobic, contain two or moreplanar aromatic rings, a tertiary nitrogen, and a positive chargeat physiological pH (22). A number of lipophilic drugs, chosenat random, have been shown to reverse MDR (27). Althoughmany lipophilic drugs of differing chemical structures are reversing agents, not all such compounds are active and there is alarge range of potency among the group of drugs which exhibitsome reversal activity. No computer-aided, systematic study ofthe structural features of reversers has been attempted. Thesuccess of such an analysis is demonstrated in the current workwhich required comparing the activity with the structural features of a large number of drugs, many of which may havedifferent mechanisms of action.

MATERIALS AND METHODS

Experimental Procedure

Materials. Drugs tested for MDR reversal activity as well as vinblastine sulfate were purchased from the Aldrich Chemical Co. (Milwaukee, WI). [3H(<7)]Vinblastine sulfate was purchased from Moravek

Biochemicals (Brea, CA). Other biochemicals were from Sigma Chemical Co. (St. Louis, MO).

Cell Lines and Culture Conditions. The CHRC5 cell line which is an

MDR cell line derived from the AB, Chinese hamster ovary line byselection for resistance to colchicine (28), was generously provided to us

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by Dr. Victor Ling of the Ontario Cancer Institute (Toronto, Ontario,Canada). The cells were grown in »-minimalessential medium supplemented with 7% fetal bovine serum at 37°C.The resistant cells do not

show any significant change upon growth in nonselective medium for3-4 weeks, and hence they were routinely grown in the absence of anyselecting agent.

Clonogenic Assay. The effect of various agents on the reversal of thedrug resistance was examined by determining the cloning efficiencies ofa parental and a resistant cell line. In these experiments, 0.5 ml of 11progressive dilutions of vinblastine were added to duplicate wells. Thesedilutions were chosen to cover a range of concentrations both above andbelow the cytotoxic level, either in the presence or absence of sensitizer.Approximately 500 cells, together with a fixed concentration of sensitizer, were then added to each of the wells of 24-well dishes. Theexperiments were carried out in parallel with and without the reversingagents. Less water-soluble reversing agents were dissolved in DMSOand vinblastine sulfate in 90% ethanol. Concentrated solutions of drugsin organic solvents were diluted into medium. The final concentrationof solvent present in the wells did not exceed 1% and in most cases wasbelow 0.2%. At these concentrations, the solvents had no significanteffect on cell viability or the number of colonies formed. At the concentrations used, the various reversing agents by themselves show<50% toxicity toward the cell lines. The effect of a reversing agent onthe cytotoxic action of vinblastine was always compared with a controlcontaining only the reversing agent. The dishes were incubated for 5-10days at 37°Cin 5% CO;-95% air in a humidified incubator to allow the

formation of visible colonies. Subsequently, the dishes were stained forabout 30 min with 0.5% méthylèneblue in 50% methanol and thenumber of colonies in each well was scored. From the average numberof colonies observed in the presence of different vinblastine concentrations, the D,o values in the absence and presence of various reversingagents were determined. Each clonogenic assay was repeated in at leasttwo independent experiments. Reproducibility of the D|0 values inindependent assays was within 25%.

In addition to this clonogenic assay, which indicated which compounds were reversing agents, we also compared their potency at aconstant concentration of vinblastine. The concentration of vinblastinechosen was 22 n\i. which is a concentration higher than the D)(i valuefor the parental AB, cell line but 5-fold lower than the DH>value for theresistant CHKC5 cell line. This concentration of vinblastine does notaffect the clonogenic efficiency of the CHKC5 line in the absence of

reversing agent but it is very cytotoxic for the AB, line. In a clonogenicassay similar to that described above. CHHC5 cells were grown with a

constant concentration of 22 n%ivinblastine and varying concentrationsof reversing agent. The D|0 value for the reversing agent was determined.

|'Il|\ ¡iilihisiiiii'Uptake. Monolayers of cells were grown in 10-cm

diameter Petri dishes. The numbers of cells in representative disheswere determined by trypsinizing the cells and counting them in aCoulter counter. Cells were washed with PBS, pH 7.4, at 37°C.Then 2ml pH 7.4 buffer at 37'C, containing 107 HIMNaCl. 10 HIMTris. 26.2

HIMNaHCO,. 5.3 imi KC1, 1.9 msi CaCU. 1 HIMMgCU. and 7 m\i

glucose were added. When required. 15 /AI concentration of a reverserdissolved in DMSO (final concentration of DMSO was always keptbelow 1%) was added. Then 0.25 ml of a 100 nM ['Hjvinblastine solu

tion in water (specific activity. 10 Ci/mmol) was added and the disheswere incubated in duplicate at 37'C in a 5% CO2 atmosphere, to allowthe cells to take up ['Hjvinblastine. The reaction was stopped aftervarious lengths of time by washing the dishes twice with ice-cold PBS:then the cells were scraped in PBS with a rubber policeman, transferredquantitatively to scintillation vials, and lyophilized. When dry, the powder was dissolved in 0.5 ml water and 9 ml of counting fluid (ACS) wereadded. Vials were vortexed well before counting in the scintillationcounter. The amount of vinblastine taken up per cell was then calculated.

Experimental Data

The ability of seven test drugs (Compounds A to G) to sensitize theAB, and CHRC5 cell lines was tested in a clonogenic assay. Compounds

B, C, F, and G (see below for their structures) were found to be active(Table 1). The relative potency of these four active compounds werecompared for their reversal of the resistant CHRC5 ceil line in the

presence of 22 nM vinblastine. By this criterion Compound G is themost potent, with an activity comparable to that of the known sensitizerverapamil (Table 2).

It is well established that CHKC5 cells take up less vinblastine than

does the AB, parental cell line. The time course for the accumulation ofvinblastine showed a rapid uptake over the first 15 min, followed bylittle further accumulation over the next 30 min. The general features ofthe time course were similar in the presence and absence of sensitizingagent. The sensitizing agents at a concentration of 15 MMhad little effecton drug uptake in the ABi cells (not shown). However, the sensitizersmarkedly increased the accumulation of vinblastine in the resistantCHRC5 cell line (Fig. I ). Compounds F and G brought the uptake to a

level comparable to that of the AB, cell line.

Modeling Methodology

Most of the QSAR methods are inapplicable to the study of noncon-generic databases such as the one described above. But the methodologydeveloped in our group has been designed specifically for nonconge-neric studies. This methodology, the Multiple Computer AutomatedStructure Evaluation (MULTICASE), is an artificial intelligence program which, as its predecessor, CASE (29, 30), automatically generatesparameters in the form of fragments from the molecules submitted tothe program. In this way it tries to delineate the common substructuralfeatures of the compounds which are significant for activity. It is hierarchical in nature and results in a number of fragments each of whichcan account for the activity (31). The program begins by breaking eachmolecule, entered in the program either graphically or encoded throughKLN rules (32), into smaller subfragments which are labeled as active ifthey originate from an active molecule or inactive if they belong to aparent inactive compound. These fragments are processed statisticallyby using the binomial distribution criteria and bayesian probability

Table 1 Clonogenic assays for the sensitizaron ofCIIO cells to vinhlastine

SensitizingagentNo

drugCompound

ABCI)

1F

GCytotoxic

concentration"

(*<M)9.3

11162

330330

7525Concentration

used forsensitization

(MM)2.3

14.11

169723714DIO

(HM)1111

114.4

11II2.22.2AB!Relative

resistance*11

10.410.2

0.2Fold

sensitization'1

12.51

155D,„

(nM)11011022

5.5110110

115.5CHRC5Relative

resistanceIOIO

20.5

10IO10.5Fold

sensitization1

5201

1IO20

" Determined in CHRC5 cells.* Relative resistance of AB, cells to vinhlastine in the absence of sensitizing agent is taken as 1. Ratios of the Dm values in the presence of sensitizing agent or for the

CHRC5 cell line to that of AB, in the absence of sensitizing agent gives the relative resistance.' Fold sensiti/ation is the ratio of the DH, values in the absence of sensitizer to that in the presence of sensitizer for the particular cell line in question. A fold sensilization

of I indicates a lack of effect.

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Table 2 Comparison of ¡hepotency of MDR sensiti:ers for the CHKC5 cell linein the presence of 22 n,w rinhlastine

Sensitizing agent DI,, (AIM)

CompoundBCFG

Verapamil

196

1542

0.30

0.25

0.20

0.15

0.10

0.05

0.00ABI CHRC5 B C F G

Fig. l. Accumulation of [%H|vinblastine after 45 min for the AB, cell line in theabsence of drug (ABI) or the C'HRC5 cell line in the absence of drug (CH"C5) or

in the presence of 15 UMof each one of the sensitizers (Compounds ß.C. f. andG). Compounds fi, C. F. and 6'have no effect on the uptake of drug in the AB, cell

line.

rules, and only the most significant fragments are retained. The program then proceeds to select that fragment which has the highest statistical occurrence in the active compounds. This fragment is called thebiophore and is considered responsible for causing the observed biological activity. The compounds containing this biophore are removedfrom the database and the program proceeds to select the next bestbiophore from among the fragments of the reduced datasct. In this waybiophores continue to be generated in a hierarchical fashion until nearlyall the active compounds have been found to contain one or more suchfragments. Subsequently, a stepwise multivariate linear regression analysis is performed separately for the compounds containing each of thebiophores. The significant fragments generated from those few compounds constitute the parameters which are considered for regressionalong with the partition coefficient, logP. The regression analysis yieldsa QSAR equation for each biophore which has the following form:

Activity = k + V; c,nj, + C-,logP + CA(logP)2

where k is the constant./ is the i"1 fragment, c¡and n, represent the

coefficient and the number of times the fragment appears in the molecule, respectively. The logP terms constitute the contribution due tothe hydrophobicity of the molecule.

The parameters (f¡)selected in each of these QSARs are called modulators, for they only serve to modulate the activ ity caused by the parentbiophore but cannot cause reversal of drug resistance by themselves.The constant in the QSAR equation represents the average activitycaused by the biophore alone, while the coefficients of the modulatingfragments in the same equation are indicative of the contribution of themodulators to the activity.

Once the program is trained with the original database (called thetraining set) it has the additional capability to predict the activity of newcompounds with the knowledge gained so far. These predictions arevalid as long as the program does not encounter any new functionalitiesin the new compounds. Along with the predicted activity, the probability of relevance is also listed for each prediction. This is representativeof the confidence level of the prediction. If the experimental activities ofthese new compounds are available they can be added to the database.

thereby enhancing the knowledge of the program. The more compounds submitted to the program the better its predictive power.

Training Set. We compiled a comprehensive database of 137 compounds from 17 different sources. These compounds were tested on awide range of MDR cell lines like those derived from CCRF-CEM

human lymphoblasts, CHO cells, or P388 cells, etc. The cytotoxic agentused also varied in each source. The activity of the compounds wasqualitatively evaluated on the basis of the concentration required (inng/ml or ng/ml) to sensitize the MDR cells.

RESULTS AND DISCUSSION

The MDR compounds in the database had been tested underdifferent conditions and on different cell lines. Moreover, insome cases the activities were reported in terms of ¿ig/mldosagefor a fixed percentage of reversal of MDR and in others aspercentage of reversability at fixed dosages. As a first step wetried to pool the activities into a common scale. This was noteasy since they cannot be converted directly from one scale toanother by any kind of mathematical transformation. So theywere classified into three categories instead. Those which wereeither inactive or weakly active were labeled as inactive, theactives and the very actives were called actives, while thosemolecules showing extremely high reversal activity were listedin a third category of very active molecules. Our observationthat most compounds showed similar reversibility on differentcell lines allowed us to neglect the effect of cell line variabilityamong the compounds.

Due to the noncongeneric nature of the database we found itimportant to validate our results before we begin to analyzethem. The following section describes the validation in detail.

Validation. In compliance with the validation concept, a testset of 20 compounds (13 actives, 7 inactives) of the 135 compounds in the database was selected randomly and taken outfrom the analysis. From the remaining compounds, 5 embedded training sets were formed. The smallest one contained only23 compounds, while 4 larger training sets were created bysuccessive addition of sets of 23 compounds to the first trainingset. Thus, the fifth training set included all of the 115 remainingcompounds in the database. The analysis was carried out oneach training set separately, and predictions of the test set of 20compounds were recorded. If the trend shows that the larger thetraining set the better the predictions, then the database isvalidated in terms of showing predictive power. Further confirmation was provided by predicting the activity of all the remaining compounds not used for training the program. This includes92 compounds for the first training set, 69 compounds for thesecond, etc. In other words, we evaluated the ability of thetraining set of 20% of the data to predict the activity of theremaining 80%, 40% to predict the remaining 60%, etc. Again,an increasing trend validates the data. The validation results aresummarized in Table 3. The table shows the active/inactivedistribution of the training sets and the x~ distance measures ofthe predictions. The x2 distance measure shows how much the

Table 3 Validation results ofmultidru/; resistance reversal tlatahaseColumns 2 and 3 represent the x2 distance.

Training set(active/inactive)1.

10/132.22/243.35/344.50/425.

64/51Predicts

test set of200.4690.1890.2220.2970.297Predictsremaining

compounds of the 1150.0340.1510.2110.231

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Table 4 Dataoase ofmultidrug resistant reversal compounds

Biophores" Biophobes

Compound Activity"1 2345 6789012 12345678901

1234 1234

I.Solanesol2.5-(/V^V-hexamethylene)amiloride3.Hydroxyzine4.NK-2165.

Retinylpalmitate6.Trypanblue7.

Colchicine8.5-a-Androsten-17-tf-ol-3-one9.

Amiodarone10.Monensin11.NK-20912.Nifedipine13.Solanesylacetone14.i-Diaminomethylene-4-benzyl-7-(4-chlorophenyl)-5-oxo-4-phenyl-5-hexenamide15.

Primaquine16.Chlorpromazine17.Acridine18.

Methyl benzoylreserpate19.Corynanthine20.3',4'-Dichlorobenzamil21.

Physostigmine22.Tamoxifen23.5-[A'-Methyl-/V-(amidinocarbonylmethyl)amiloride]24.

Isoniazid25.AHC-5226.

Atropine27.Cinchonidine28.

Oxolinicacid29.PAK-530.Quinacrine31.NK-18732.Hydrocortisone33.Methylamine34.Etomidoline35.Pirenzepine36.5-(jV-4-ChIorobenzyl)-2',4'-dimethylbenzamil37.4-Androstene-3,17-dione38.Triproloidine39.Syrosingopine40.Reserpine41.Corticosterone42.NK-10243.Decaprenol44.jV-jV'-bis-(3-Chloro-5-diaminomethyleneiminocarbonyl)-6-amino-ethylenediamine45.

Propranolol46.Rolitetracycline47.Verapamil48.Dimethindine49.PAK-950.5-[A'-Methyl-A'-(/frf-butyl)]-amiloride51.NK-10652.PAK-653.Chloroquine54.5/3-Fregnane-3o,20a-diol55.PAK-1056.NK-22057.NK-11758.

Retinylacetate59.Eprazinone60.(3-Estradiol61.

Pipemidicacid62.Arr/V'-(6-Chloro-3,5-diaminopyrazinecarbonyl-imino-aminomethylene)-1,4-xylenediamine63.

NK-16364.NK-19465.Progesterone66.Quinine67.

Decaprenylmethylether68.Equilin69.o-Equilenine70.Trifluoperazine71.Testosterone72.

jV-(p-Methylbenzyl)decaprenylamine73.PAK-2_I+

X++x-i—-

i++X+

.XXXXXX+XX

I—+

X++x.x+X—X

I+XI+

. ..XX—IX

I++X. . ..X.X+

X—+

xx+X XX++

X—+

X+X XX

I+X+

XX+X++X—

...XI-I+

XXII++

X+XXII+

X+XX+XX.XI—++

X+X++X+

XI.IIX

I++X++X+X++X—II++

XI+

X++X X

•¿�++, +, -.-indicate the experimental activity of the molecules (extremely active, active, and inactive, respectively). These values were all reproduced exactly by theprogram.

h Biophores in italics represent the expanded fragments of the preceding biophore. X and 1indicate the presence of an activating and inactivating fragment, respectively.

(Refer to Figs. 1, 5. and 2 for Biophores, Biophobes, and Expanded Fragments, respectively).

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Table 4 Continued

Biophores* Biophobes

Compound/74.

Benzoylyohimbine75.Simetride76.5-(/V-Methyl-A'-isobutyl)amiloride77.

Cortisone78.CyclosponnA79.

Trimethoxybenzoylyohimbine80.Catharanthine81.PAK-882.NK-14983.

Decaprenoicacid84.NK-12185.Vancomycin86.

Piromidicacid87.Prazosine88.Vindoline89.

Methylreserpate90.Dilazep91.

Acridineorange92.Tryptamine93.Vohimbinc94.NK-18095.Rescinnamine96.Zomepirac97.PAK-198.NK-11399.

Estriol100.Nafcillin101.NK-200102.Estrone103.5-(4-Methyl-4-aza-pentamethylene)amiloride104.Decaprenylamine105.PAK-3106.Phenamil107.NK-101108.

Sin;imiii109./V-A''-D¡inethyl-A'-A"-bis-[3-chloro-5-(diaminomethyleneiminocarbonyl)-6-aminoethylcne-diamine)110.

NK-139111.Di Itin/cm112.

Nicardipine113.NK-203114.Dehydro-/'.5o-androsterone115.

NK-196116.Carbinoxamin117.

PAK-4118. Reserpic acidlactonc119.

PAK-7120./V-(PMB)-decaprenylamme121.Fluphenazine122.Trimethoprin123.Tilorone124.NK-127125.NK-138126.NK-170127.Meclizine128.Trvptophan129.NK-118130. Reserpicacid131.

NK-140132.Epinephrine133.

Ethyldecaprenoate134.Amiloride135.

1,4-Cyclohexanedione bis(ethyleneketal)136.4-(2-Dinielhylamino)ethyl]morpholine137.

2-Oxazolidinoneictivity"

12341234++

X+xI++

X++X+X++

X+X+

XII. ..II++

X X. . ..X++

X+

X+

X+

X++XX++

XI++

XX+XI.II.

.1..++XII++

X++X+

XXIII

I.++X++X++

XX.X++XI+

X+X++

XXI. ..+

XX+

+X++XX-+

X+X++X+X+X++

XXI..++

XI-X

I.-

MULTICASE predictions are better than random. A x2 dis

tance value close to 0 corresponds to chance prediction,whereas a value of 1 corresponds to a perfect prediction (33).

Table 3 shows (with one exception) that the desired trend isindeed observed. The more compounds in the training set themore useful information is extracted by MULTICASE in termsof predicting the reversal potency of unknown compounds.However, the smallest dataset is an exception to this trend sinceit produces the best value of x2 distance for the test set. But it

also shows an uncharacteristically low value for the set of re

maining compounds. Hence it could be ignored. Based on thevalidation results, one can conclude that the database of the 135multidrug resistance reversal agents holds useful informationwhich enables our MULTICASE expert system to predict thereversal potency of reverser candidates.

MULTICASE Results. The MULTICASE analysis was carried out on the training set of 137 compounds which included76 actives and 61 inactives (two extra compounds were addedto our dataset). A total of 12 biophores and 11 biophobes(deactivating fragments) were generated which were able to

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reproduce all the experimental data. Table 4 lists the activitiesof the compounds along with the occurrence of biophores andbiophobes in each of those compounds, while Fig. 2 shows thebiophores. The program also recognizes and generates thosefragments which are similar in connectivity and heteroatomsubstitution to the biophores. These are termed "expanded biophores" and are believed to be bioisosteric in nature. Some of

these are shown in Fig. 3. The modulators of Biophores 1 and2 are included in Figs.4 and 5, respectively, and the biophobescan be seen in Fig.6.

As mentioned above, Biophore 1 was the most prevalentamong the actives. It was found to occur in 40 compounds ofwhich 35 were actives. It appears that this biophore could existin the general form of -C-X-C-C- where X = O,N. But

the activity is maximized when the heteroatom is nitrogen andthe chain is unsubstituted. Moreover, the activity is independent of the cis-trans geometry orientation of the fragment.Among the remaining biophores only 2, 3, 4, and 5 have largeoccurrences.

The modulators of Biophore 1 are shown in Fig. 4. Thepartition coefficient (logP) of the compounds was found to bethe most important descriptor modulating the activity causedby Biophore 1. This is not surprising, considering the fact thatthe process of drug resistance reversal probably involves anaccumulation of the drug in the plasma membrane of the cells.The importance of lipophilicity has been recognized previouslyin other biological systems by our methodology (34).

Biophore 2 occurs in 26 compounds of which 23 are active. Itactually represents the minimal skeleton required for activity

c-

10 11

Fig. 2. List of biophores generated by MULTICASE.

12

C'S'

Fig. 3. List of expanded biophores (refer to text). /. Biophore 1; //. Biophore 5.

LogP

1

CH

HO'V

8

Fig. 4. Modulators of Biophore 1.

,c=HO

CH

Vo

CH.

(k .CH,

56Fig. 5. Modulators of Biophore 2.

HO' N*CxNHC'

CH

¿HCH

8

HO

CH,

9 10 11Fig. 6. List of biophobes generated by MULTICASE.

among the congeneric series of compounds in the database (NKseries). Modulators of this biophore are shown in Fig. 5. Thefirst modulator simply adds a vinyl sulfide (C=C—S—) group

to the main skeleton. The second modulator occurs as part of aphenyl ring (in 2 compounds). The third modulator also occursin 2 active compounds and exists in a very delocalized 7r-envi-ronment with nitrogen at one end and an ester functionality inthe middle. An alkyl acidic group (—CH2COOH) is a deacti

vating modulator probably affecting the pH.The third biophore occurs in a total of 9 molecules. It was

also found to coexist with Biophore 1 in Compounds 35, 38,48,and 53. This fragment is actually a part of the pyridine 83 andquinoline rings. The quinoline generally contains a modulator(N=C—CH=CH—C=) which serves to increase the electron

density of the ring containing the biophore. An alkoxy group(CH3O—C=) exocyclic to the pyridine or quinoline rings also

serves as an activating modulator by perturbing the electronicenvironment in the ring. On the other hand, an amide group(—NH—CO—)when attached at one of the above rings de

creases the activity presumably by depleting the aromatic ringof its electrons.

The fourth biophore seems to be a very important fragment.It occurs in 12 compounds of which 10 are actives. The interesting fact about this biophore is that it appears in conjunctionwith the first biophore in 5 compounds. Moreover, in all thesecompounds the two biophores appear at the same location inthe molecule. This could mean that Biophore 4 may actually bea modulator for Biophore 1. On the other hand, they could eachbe responsible for reversal activity, independently of each other,either by the same mechanism or by different mechanisms. This

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A. Benzyldiethyl(2-(4-(1.1,3.3-tetramethylbutyl)phenoxy)etnyl ammonium chloride

B. 4-(Morpholinomethyl)-alpha(2-pyndyl) Benzhydrol

C. N-Benzyl-3-(4-phenyl-1,2.3.6-tetrahydro pyndino)-propionamide

Fig. 7. MULTICASE-designcd new MDR reversal compounds.

joint presence increases the probability of a compound beingactive. Except for the inactive Compound 62, Biophore 4 always occurs at the terminal end of the structure. This couldimply that the biophore is probably effective in providing asupport for the molecule by acting as an anchor as a resultof binding to some site in the cell membrane. The 2 compounds which are inactive (Compounds 36 and 62) contain ahighly deactivating fragment, Biophobe 4 (N=C—NH —¿�CH2).

Since this biophobe occurs in place of Biophore 1(—CH2—N—CH2—CH2) in these two compounds it is quiteclear that a 7r-rich fragment is detrimental to exerting reversalactivity.

Design of New MDR Reversals. With the information extracted from the program and presented in the preceding sections it is, of course, not possible to postulate a general mechanism of action, but with the knowledge about the significantfragments and their relationship to activity we are in a goodenough position to design a few new compounds. The first stepin the design process is to identify some basic skeletal structurespossessing MDR reversal potency. These structures could bethen optimized for optimum activity.

The following considerations were made while selecting newcompounds from the literature to act as reversals of multidrugresistance. Since Biophore 1 was found to be the most important fragment relevant to activity, its presence was consideredessential. Subsequently, as many modulators as possible were tobe included in order to maximize the activity caused by theprimary biophore. At the same time the deactivating modulators and the biophobes were to be excluded. The partition coefficient (logP) was to be optimized. Although it is likely thatthe other biophores act independently of each other, their inclusion could increase the probability of finding an active reversal agent, especially if there is evidence that they occurredalong with Biophore 1 in the compounds in the database. Onesuch example is Biophore 4 (as discussed earlier in the text).

The Fine Chemical Dictionary program in MACCS-II2 was

used for selecting active candidates from the literature. TheFine Chemical Dictionary program includes a database whichhas over 64,000 compounds available from commercial chemical suppliers. The entire database in the program was searchedfor compounds containing Biophore 1. From this large selection a further search was conducted to identify compoundswhich may contain one or more modulators of Biophore 1 oreven other biophores. Several combinations of the biophoresand modulators were evaluated and each time the structuresobtained through the search were saved and later tested byMULTICASE to determine their potential MDR reversal po

tency. In this way a total of 12 compounds were identifiedwhich were predicted to be either active or extremely active byMULTICASE. Three of these were subsequently procuredfrom Aldrich. The structures are shown in Fig. 7, while Table 5shows the predictions made by MULTICASE.

As can be seen the predicted activities are in the same rangeas the highest in the database. The first two compounds possesssubfragments which are not known to the program because theywere not present in any of the compounds in the training set(Compound/! contains a quaternary nitrogen and Compound Bpossesses a —¿�N=C—C— group). Hence the program gives a

warning (denoted by symbol W, in Table 5) that the resultscould be nullified by the presence of these foreign fragments.We still decided to include these two compounds since ourobjective is not only to design new compounds but also toaugment the knowledge of the program. The probability shownin the table is an indication of the confidence level of the prediction for that compound.

The three compounds were tested experimentally for theirreversal activity, as described earlier in the experimental section. Compound A was found to be inactive while CompoundsB and C showed high reversal activity.

Since Compound A turned out to be inactive we can infer thatthe nitrogen in Biophore 1 (-CH2 —¿�N—CH2—CH2—¿�)must

not be a quaternary nitrogen. We also know that the reversalaction increases with increase in logP (Modulator 1 to Biophore1). This could explain the adverse effect caused by a quaternarynitrogen since it tends to make a drug more hydrophilic. It isquite likely that the activity of Compound A would increase ifthe quaternary nitrogen were to be converted to tertiary. Theother foreign functionality (N=C—C—) does not seem to have

a deactivating action, although nothing can be said about itsactivating potential either. The fact that Compounds B and Cwere found to be as active as predicted by the program seems tovalidate the results obtained from the analysis. Biophore 1, eventhough a very small fragment, seems to relate very strongly tothe MDR reversal activity. Actually, some other workers, too,have found an alkyl group containing a secondary nitrogen to beresponsible for reversal action (35). In addition, other relatedtheoretical studies have found hydrophobicity and molecularweight of drugs to correlate with the multidrug resistance reversal action (36).

At this stage the three new compounds with their experimental activities were added to the database in order to increase thelearning potential of the program. In addition, three more compounds obtained from another source were also added to thetraining set (37). The augmented training set of 143 compoundswas used to run the MULTICASE program again. The following changes were observed from the previous analysis.

MULTICASE again generated 12 biophores to account forthe activity of all the 143 compounds. This time only the top

Table 5 MULTICASE-designed new MDR reversals

Sample set I.

ModulatorsPredicted of Probability Experimental

Compound activity Biophores Biophores 1 (%) activity"

ABC++ W*++W++1.41.3.41,42.

logP2,logP2.

logP93.896.791.5-

(inactive)+(6.9)++(1.9)

2 MACCS-II is a chemical information management software package distributed by Molecular Design. Ltd.

" The activity for the inactive, active and very active MDRRs is represented by-. +, ++, respectively, while the values in parentheses are the actual experimentalactivities (in up mil.

h \\ denotes presence of unknown functionalities in the compound.

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RELATIONSHIP BETWEEN STRUCTURE ANI) MDR REVERSAL ACTIVITY

51 (+)Fig. 8. MDR reversal compounds contain

ing the -y-heteroatom functionality.

107 (-)

81 (-)

three biophores were robust and had high statistical significance. The lower biophores were only selected to account forthe activity of the remaining active compounds. The benzylfragment (selected as Biophore 4 in the previous analysis) wasnot selected at all this time. Instead the program selected achloro-substituted chain [CH=C(CI)-CH] as the fourth bio-

phore.The QSAR for Biophore 1 also showed minor changes. The

logP parameter remained as the most significant for activity.The second and the fourth modulators were also unchanged,but the third modulator (CH=C(C)—CH=] was replacedby =C—N—C. This new modulator was selected apparently

because its statistical significance was increased by virtueof its presence in thioridazine, which was one of the additions for the second analysis. It also appears in two other compounds. Compounds 70 and 121. Both these compounds alsocontain the modulator selected in the previous analysis[CH=C(C) —¿�CH=]. An extra activating modulator was pickedup in the form of OH-CH-CH(O)-CH-CO-O which is

present in methyl reserpatc (Compound 89). Among the deactivating modulators a new fragment in the form of OH—C=

was selected. This also happens to be a strong biophobe,namely, its presence in any compound has a deleterious effecton the activity, irrespective of the biophores present. This fragment is found in 9 inactive molecules in the entire database.

Another trend was observed when the compounds containingBiophore 2 were examined more closely. The list of significant parameters consisted of two activating modulators(CH2-O-CH and CH2-O-CH2) which seem to occur at

similar positions in the active compounds. The oxygen atom inthese two fragments lies at the y position with respect to theester functionality which is part of the biophore (refer to Fig. 5).We examined all the 28 compounds in the NK series (containing Biophore 2) and others possessing similar backbones. Therewere three inactive compounds. Comparing the first inactiveCompound 107 with an active Compound 51 we find that theonly structural difference lies at the terminal end of the molecule (Fig. 8). Compound 107 has a —¿�COOHfunctionalitywhile Compound 51 possesses a —¿�COOCH2CH, group. Apparently an —¿�OHgroup next to the y-O (in this case a =O)

tends to diminish the activity. Similar changes exist in pairsconsisting of the inactive Compound 81 and active Compound

97. Biophore 7 (—CO—CH3) also possesses a similar 7-het-

eroatom functionality.At this stage it became interesting to design some more po

tential reversal agents with the revised results from the program. MACCS-II was again used for selecting some more compounds from the literature (shown in Fig. 9).

The following rationale was used in selecting these compounds. Compounds E and G were chosen for the presence ofBiophore 1 once again. In addition they included a new modulator ( —¿�CO—CH,).Compound G was selected especially be

cause it had a very different structural backbone and presenteda good possibility of designing a totally novel MDR reversalcompound. Compound D contained Biophore 7 and includedan oxygen atom at the y position to the —¿�O—CO—CH,func

tionality (as discussed above). It was also interesting to see if analiphatic compound could show reversal potential too, sincealmost all the compounds in the database are aromatic in nature. Finally, Compound /-"was designed by retaining the min

imal necessary skeleton of the compounds containing Biophore2, along with the most important modulator 1. Table 6 showsthe MULTICASE and the experimental results for these fourcompounds.

D. Methoxyethyl acetate E. N-acetylprocainamide

G. Coumarin 334F. Diethyl 1,4-dihydro-2,4,6-trimethyl3,5-pyridine dicarboxylate

Fig. 9. MULTICASE-designed new MDR reversal compounds. Set II.

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RELATIONSHIP BETWEEN STRUCTURE AND MDR REVERSAL ACTIVITY

Table 6 MULTICASE and experimental results for the theoretically designedmultidrug resistance reversa! compounds

Sample set II.

Predicted Probability ExperimentalCompound activity Biophores Modulators (%) activity"

D+-E+F+G

+-H

7h

11-2h

1l.logP11, logP75.080.486.480.4—

(inactive)—(inactive)++(4.0)++(1.0)

" The activity for the inactive, active and very active MDRRs is represented by—¿�,+, ++, respectively, while the values in parentheses are the actual experimentalactivities (in ng/ml).

Two of the four selected compounds were again found to beactive. The fact that Compound D was inactive could eithermean that our hypothesis about the 7-oxygen functionality wasincorrect or that linear chain compounds are not active. Compound £turns out to be inactive, presumably due to the presence of a —¿�CO—NHgroup. The high activity of Compound F

establishes the importance of Biophore 2. But Compound Gturned out to be extremely potent, actually as potent as some ofthe best reversal agents known like verapamil. Since this compound has a totally different skeleton, we believe this compound has the potential to develop into a totally new reversingagent.

Conclusion. The MULTICASE methodology was used successfully for identifying key substructural fragments related tothe multidrug resistance reversal activity. The program identified 7 new compounds from the literature, of which 4 turned outto be very active as MDR revertants when tested experimentallyon the CHRC5 cell line in presence of vinblastine. Some of

these compounds had high cytotoxicity side effects in additionto high MDR revenant potency. Hence they have been selectedas lead compounds for further development when attemptswould be made to study the relationship between cytotoxicityand structure of the compounds. In this way it is hoped that thecytotoxic side effects could be minimized while achieving overall optimization of their MDR revenant activity.

REFERENCES

1. Goldie, J. H., and Goldman. A. J. Genetic instability in the development ofdrug resistance. Semin. Oncol., 12: 222-230, 1985.

2. Goldie, J. H., and Goldman. A. J. The genetic origin of drug resistance inneoplasms: implications for systemic therapy. Cancer Res., 44: 3643-3653,1984.

3. Kessel, D.. Botterill. V.. and Wodinsky, I. Uptake and retention of dauno-mycin by mouse leukemic cells as factors in drug response. Cancer Res., 28:938-941, 1968.

4. Kessel, D., Hall, T. C., Roberts, D., and Wodinsky, I. Uptake as a determinant of methotrexate response in mouse leukemias. Science (WashingtonDC), 150: 752-754. 1965.

5. Ling. V.. and Thompson, L. H. Reduced permeability in CHO cells as amechanism of resistance to colchicine. J. Cell. Physio)., 83: 103-116, 1974.

6. Dalton, W. S., Cress, A. E., Alberts. D. S., and Trent. J. M. Cytogenetics andphenotypic analysis of a human colon carcinoma cell line resistant to mitox-antrone. Cancer Res., 48: 1882-1888, 1988.

7. Fojo, A. T., Whang-Peng, J., Gottesman, M. M., and Pastan, I. Amplification of DNA sequences in human multidrug-resistant KB carcinoma cells.Proc. Nati. Acad. Sci. USA. «2;7661-7665, 1985.

8. Endicott, J. A., and Ling, V. The biochemistry of P-glycoprotein-mediatedmultidrug resistance. Annu. Rev. Biochem., 58: 137-171. 1989.

9. Baker, R. M., and Ling, V. Membrane mutants of mammalian cells in culture. In: E. D. Korn (ed.). Methods in Membrane Biology, vol. 9, pp. 337-384. New York: Plenum Press, 1978.

10. Gottesman, M. M.. and Pastan, I. The multidrug transporter, a double-edgedsword. J. Bio). Chem., 263: 12163-12166. 1988.

11. Roninson, I. B. (ed.). Molecular and Cellular Biology of Multidrug Resistance in Tumor Cells. New York: Plenum Press, 1991.

12. Weber. J. M.. Sircar, S., Horvath, J., and Dion, P. Non-P-glycoprotein-mediated multidrug resistance in detransformed rat cells selected for resistance to methylglyoxal bis(guanylhydrazone). Cancer Res., 49: 5779-5783,1989.

13. Hindenburg, A. A., Gervasoni, J. E., Jr., Krishna, S.. Steward, V. J., Rosado,M., Lutzky, J., Bhalla, K., Baker, M. A., and Taub, R. N. Intracellulardistribution and pharmacokinetics of daunorubicin in anthracycline-sensitiveand -resistant HL-60 cells. Cancer Res., 49: 4607-4614, 1989.

14. McGrath, T., and Center, M. S. Mechanisms of multidrug-resistance inHL-60 cells: evidence that a surface membrane protein distinct from P-gly-coprotein contributes to reduced cellular accumulation of drug. Cancer Res.,48: 3959-3963, 1988.

15. McGrath, T., Latoud, C, Arnold, S. T., Safa, A. R., Felsted, R. L., andCenter, M. S. Mechanisms of multidrug resistance in HL-60 cells. Analysisof resistance associated membrane proteins and levels of mdr gene expression. Biochem. Pharmacol., 38: 3611-3619, 1989.

16. Mirski, S. E. L., Gerlach, J. H., and Cole, S. P. C. Multidrug resistance inhuman small cell lung cancer line selected in Adriamycin. Cancer Res., 47:2594-2598, 1987.

17. Slovak, M. L., Hoeltge, G. A., Dalton, W. S., and Trent, J. M. Pharmacological and biological evidence for differing mechanisms of doxorubicin resistance in two human tumor cell lines. Cancer Res., 48: 2793-2797, 1988.

18. Bass, F., Jongsma, A. P. M., Broxterman, H. J., Arceci. R. J., Housman, D.,Scheffer, G. L., Riethorst, A., van Groenigen, M., Nieuwint, A. W. M., andJoenje, H. Non-P-glycoprotein mediated mechanism for multidrug resistanceprecedes P-glycoprotein expression during in vitro selection for doxorubicinresistance in a human lung cancer cell line. Cancer Res., 50: 5392-5398.1990.

19. Slovak, M. L., Coccia. M., Meltzer, P. S.. and Trent, J. M. Molecularanalysis of two human doxorubicin-resistant cell lines: evidence for differingmultidrug resistance mechanisms. Anticancer Res., //: 423-428, 1991.

20. Coley. H. M., Workman. P., and Twentyman, P. R. Retention of activity byselected anthracyclines in a multidrug resistant human large cell lung carcinoma line without P-glycoprotein hyperexpression. Br. J. Cancer, 63: 351-357, 1991.

21. Marquardt, D., and Center, M. S. Involvement of vacuolar H+-adenosinetriphosphatase activity in multidrug resistance in HL 60 cells. J. Nati. CancerInst., 83: 1098-1102, 1991.

22. Zamora, J. M., Pearce, H. L., and Beck, W. T. Physical-chemical propertiesshared by compounds that modulate multidrug resistance in human leukemiccells. Mol. Pharmacol., 33: 454-462, 1988.

23. Pearce, H. L., Safa, A. R., Bach, N. J., Winter. M. A., Cirtain, M. C., andBeck, W. T. Essential features of the P-glycoprotein pharmacophore as defined by a series of reserpine analogs that modulate multidrug resistance.Proc. Nati. Acad. Sci. USA, «6:5128-5132, 1989.

24. Nogae, I., Kohno, K.. Kikuchi. J., Kuwano, M., Akiyama, S-L, Kiue, A.,Suzuki, K-I., Yoshida. Y., Cornwell, M. M., Pastan, I., and Gottesman, M.M. Analysis of structural features of dihydropyridine analogs needed to reverse multidrug resistance and to inhibit photoaffinity labeling of P-glycoprotein. Biochem. Pharmacol., 88: 519-527, 1989.

25. Shinoda, H., Inaba, M., and Tsuruo, T. In vivo circumvention of vincristineresistance in mice with P388 leukemia using a novel compound, AHC-52.Cancer Res., 49: 1722-1726, 1989.

26. Mickisch, G. H., Merlino, G. T., Aiken, P. M., Gottesman, M. M., andPastan, I. New potent verapamil derivatives that reverse multidrug resistancein human renal carcinoma cells and in transgenic mice expressing the humanMDR1 gene. J. Urol., 146: 447-453, 1991.

27. Hofsli, E., and Nissen-Meyer, J. Reversal of multidrug resistance by lipo-philic drugs. Cancer Res.. 50: 3997-4002, 1990.

28. Ling, V. Drug resistance and membrane alteration in mutants of mammaliancells. Can. J. Genet. Cytol.. 17: 503-515, 1975.

29. Klopman. G. Artificial intelligence approach to structure-activity studies.Computer automated structure evaluation of biological activity of organicmolecules. J. Am. Chem. Soc., 106: 7315-7320, 1984.

30. Klopman, G.. Frierson, M. R., and Rosenkranz, R. S. The structural basis ofthe mutagenicity of chemicals in Salmonella typhimurium: The Gene-Toxdata base. Mutât.Res., 228: 1-50, 1990.

31. Klopman, G. MULTICASE I. A hierarchical computer automated structureevaluation program. Quant. Struct. Act. Relat., in press, 1992.

32. Klopman. G.. and McGonigal, M. Computer simulation of physical-chemicalproperties of organic molecules. 1. Molecular system identification. Chem.Inf. Comput. Sci., 21: 48-52, 1981.

33. Klopman, G.. and Kolossvary, I. Evaluation of quantitative structure-activitypredictions. Comparison of the predictive power of an artificial intelligencesystem with human experts. J. Math. Chem., 5: 389-407, 1990.

34. Klopman, G., and Srivastava, S. Computer-automated structure evaluation ofgastric antiulcer compounds: study of cytoprotective and antisecretory imi-dazo[l,2-a]pyndines and -pyrazines. Mol. Pharmacol.. 87: 958-965. 1990.

35. Murphy, C. S., Parker, C. J.. McCague, R., and Jordan, V. C. Structure-activity relationships of nonisomerizable derivatives of tamoxifen: importance of hydroxyl group and side chain positioning for biological activity.Mol. Pharmacol., 39: 421-428, 1991.

36. Selassie. C. D.. Hanson, C., and Khwaja, T. A. Structure-activity relationshipof antineoplastic agents in multidrug resistance. J. Med. Chem., 33: 1914-1919, 1990.

37. Bellamy, W. T., Dalton. W. S., and Dorr, R. T. The clinical relevance ofmultidrug resistance. Cancer Invest., 8: 547-562, 1990.

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1992;52:4121-4129. Cancer Res   Gilles Klopman, Sanjay Srivastava, Istvan Kolossvary, et al.   Evaluation MethodologyReversal Compounds by a Computer Automated Structure Structure-Activity Study and Design of Multidrug-resistant

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