Computer Automated Structure Evaluation of Quinolone Antibacterial Agents GILLES KLOPMAN,1* OREST T

Home , Oxolinic acid, Piromidic acid, Rosoxacin

ANTIMICROBIAL AGENTS AND CHEMOTHERAPY, Nov. 1987, p. 1831-1840 Vol. 31, No. 11 0066-4804/87/111831-10$02.00/0 Copyright C) 1987, American Society for Microbiology Computer Automated Structure Evaluation of Quinolone Antibacterial Agents GILLES KLOPMAN,1* OREST T. MACINA,1 MARK E. LEVINSON,' AND HERBERT S. ROSENKRANZ2 Departments of Chemistry' and Environmental Health Sciences,2 Case Western Reserve University, Cleveland, Ohio 44106 Received 30 March 1987/Accepted 17 August 1987

The Computer Automated Structure Evaluation (CASE) program was used to study a series of quinolone antibacterial agents for which experimental data pertaining to DNA gyrase inhibition as well as MICs against several strains of gram-positive and gram-negative bacteria are available. The result of the analysis was the automatic generation of molecular fragments relevant to the respective biological endpoints. The potential significance of these major activating-inactivating fragments to the biological activity is discussed.

The quinolone class of oral antibacterial agents has been these activities should be at their optima. Furthermore, the therapeutically effective in the treatment of urinary tract structural features necessary for enzyme inhibition may be infections. The early prototypes in this series, nalidixic and different from those needed for cell penetration. By deter- oxolinic acids, exhibited a limited spectrum of coverage. mining concentrations of drug required to inhibit DNA Renewed interest in this area of anti-infective chemo- gyrase and comparing these to the MICs, Domagala et al. (5) therapeutics has arisen with the advent of new agents qualitatively identified features needed for each of these (norfloxacin [25], enoxacin [26], CI-934 [6]) which are more activities. effectively absorbed in vivo and possess broad-spectrum We wish to report the results of the application of the activity. Computer Automated Structure Evaluation (CASE) pro- The general structures of two of the most studied classes gram (commercially licensed to Biofor Inc., Waverly, Pa., of quinolones are shown in Fig. 1. Molecular modifications who have the sole right for distribution) to a series of of the parent structures have been carried out (1, 5) for the quinolones for which data on both inhibition of DNA gyrase purpose of developing agents with higher potency and and MICs are available. Consequently, quantitative struc- broader bacterial coverage. Studies of the effects of varying ture-activity relationships (QSARs), utilizing molecular frag- substituents at the 1, 6, and 7 positions of 1,8-naphthyridines ments as descriptors, were obtained for each of the respec- (7, 26) as well as disubstituted 1-alkyl-1,4-dihydro-4-oxo- tive endpoints. Comparison of the QSAR equations and the quinoline-3-carboxylic acids (25) have yielded information fragments identified as being most relevant can help to beneficial to the ongoing development of new drugs. The differentiate between structural features necessary for inhi- qualitative results of structure-activity studies performed to bition of DNA gyrase and those necessary for cell entry. The date can be summarized as follows: maximum in vitro CASE approach differs from traditional QSAR methodolo- potency (expressed as MICs) as well as in vivo efficacy gies (8, 12) in that the predominant variables used are not occur with a fluorine substituent at C-6 with the concomitant physicochemical parameters, but represent molecular fea- presence of an amino functionality of optimal size at C-7. tures inherent within the chemical structures. Furthermore, Conventional thought had limited the N-1 substituent to we have the capability of performing regression analysis groups of similar steric bulk such as ethyl, vinyl, and (utilizing these topological descriptors) as well as discrimin- fluoroethyl. Recent studies (3, 28), however, have estab- ant analysis. The CASE methodology has been successfully lished that steric bulk alone does not determine biological applied to other classes of compounds with biological activ- activity. The possibility of the N-1 substituent exerting an ity (18, 19, 21, 22), and its unique features have been electronic influence has been suggested (3). Furthermore, discussed in relation to other QSAR approaches (9). data have been reported (28) which suggest that the chirality of N-1 substituents has little effect on antibacterial activity. MATERIALS AND METHODS The mechanism of action of the quinolone antibacterial agents involves the inhibition (specifically the A subunit) of A general introduction to the CASE methodology has DNA gyrase (2, 10, 15, 29, 30, 33, 34). This topoisomerase been published previously (17). The necessary input to the catalyzes the supercoiling of relaxed DNA (4). Inhibition of this enzyme prevents DNA replication and DNA-mediated 0 processes, subsequently leading to cell death (11, 32). Re- cently, Domagala and co-workers (5) postulated that the in vitro antibacterial activity of the quinolones can be sepa- rated into two components: (i) penetration through the ~~N bacterial envelope and (ii) inhibition of bacterial DNA RB R, gyrase. For a compound to be maximally effective, both of Quinolines 1, 8-Naphthyridines * Corresponding author. FIG. 1. General structures of quinolone antibacterial agents. 1831 1832 KLOPMAN ET AL. ANTIMICROB. AGENTS CHEMOTHER. program consists of the chemical structures of the biologi- dones. The chemical structures of the compounds analyzed cally active compounds as well as experimentally measured in this study are listed in Tables 1, 2, and 3. For each values of the expressed activity. Individual structures are molecular structure, the quantitative data consist of inhibi- coded in a manner appropriate for computer input by use of tion of Escherichia coli DNA gyrase and MICs (micrograms the Klopman Line Notation (23), a linear coding technique per milliliter) against gram-negative (E. coli, Klebsiella developed to provide easy entry of molecular structures into pneumoniae, and Pseudomonas aeruginosa) as well as a computer. The Klopman Line Notation code of the indi- gram-positive (Staphylococcus aureus and Streptococcus vidual molecules together with a quantitative representation pneumoniae) bacteria. The inhibition of gyrase activity was of their respective biological activities are stored within a measured by the minimum amount of drug required for the central data file. Submission of the data base to the program appearance of linear DNA after denaturation of the drug- initiates the CASE analysis. CASE automatically "frag- gyrase-DNA complex (gyrase cleavage values) (30). ments" each molecular structure into units of 3 to 10 heavy The purpose of the present study is to delineate the atoms together with their associated hydrogens. The pro- molecular features necessary for enzyme inhibition from gram can also accommodate fragments with branching at one features that allow effective cell penetration into repre- position along the linear atomic chain. Fragments arising sentative gram-negative and gram-positive bacteria. Accord- from biologically active compounds are labeled as activat- ingly, separate data bases were established for DNA gyrase ing, while inactive compounds give rise to inactivating inhibition and the others involving activity against K. fragments. pneumoniae MGH-2, P. aeruginosa UI-18, E. coli H560, E. Fragmentation of all of the compounds forming a data base coli (Vogel), S. aureus H228, and S. pneumoniae SV-2, generates thousands of molecular fragments. The program respectively. It should be noted that E. coli H560 carries a then performs a statistical analysis to identify those frag- polA mutation. This genotype is associated with increased ments that are relevant to the observed biological activity. A susceptibility to nalidixic acid and its derivatives (27, 32). binomial distribution is assumed, and any considerable de- Each of the seven data bases consisted of 53 compounds viation from a random distribution of a fragment among the which served as training sets. Six randomly chosen com- active and inactive classes of molecules is indicative of pounds were withheld from each training set and subse- potential significance to the biological activity. With this quently studied as test cases (unknowns). For the purposes reduced set of statistically relevant fragments, the program of deriving QSARs, the reported DNA gyrase inhibition (in can separate biologically active from inactive compounds. micrograms per milliliter) and MICs (in micrograms per Quantitative estimation of the potency or degree of bio- milliliter) for each agent were transformed into millimolar logical expression is achieved by a multivariate linear regres- concentrations. Cutoff values were established to separate sion analysis based on the stepwise selection of a subset of the inactive compounds from the active class. Selection of descriptors. Initially, a fragment (either activating or inacti- these values was guided by the clustering of the experimen- vating) is selected on the basis that it can discriminate the tal data to maximize the separation between the two classes. greatest number of active and inactive compounds. Subse- Table 4 lists the cutoff values selected as well as the number quent fragments are selected to account most effectively for of compounds within the activity classes. the activity of the remaining compounds. This procedure Submission of the training data bases to CASE version culminates in a set of largely uncorrelated fragments which 2.22 resulted in the automatic generation of fragments rele- serve as potential variables for the ensuing least-squares vant to the biological activity being investigated. Multi- regression. In addition, theoretically calculated values (24) variate linear regression gave rise to QSAR regression of the logarithm of the partition coefficient and the square of equations for each of the following respective endpoints. the logarithm of the partition coefficient are included as potential variables. Activating and inactivating fragments (i) Inhibition of DNA gyrase. are subsequently incorporated within the regression equa- -log BA = 1.05 + 0.80n1Fl + 1.34n2F2 - 0.48n3F3 tion in a forward stepwise manner until no significant im- - 0.06 (log p)2 provement is observed between calculated and actual values. The statistical validity of each of the variables is where R = 0.88, F(4,48) = 42.27, S = 0.35, N = 53. established by application of the F partial statistic at the 95% confidence level (20). The coefficient of each of the frag- (ii) E. coli H560. ments selected by the regression analysis is a measure of the activating-inactivating contribution made to the biological -log MIC = 1.27 + 0.53n1Fl + 1.04n2F2 + 0.33n3F3 activity by the presence of the fragment. = = = N = 53. Once the computer has been "trained" with a particular where R 0.77, F(349) 24.81, S 0.67, data base, test compounds which were not included in the original CASE analysis can be submitted for qualitative as (iii) E. coli (Vogel). well as quantitative predictions. Furthermore, the data base -log MIC = 1.87 + + 0.70n2F2 + 0.45n3F3 - can be continually updated with new compounds, leading to 0.55n1Fl 0.26n4F4 + 0.57n5F5 + 0.48n6F6 + 0.91n7F7 + increased predictive accuracy. 0.5On8F8 + 0.15 log P - 0.71ngFg RESULTS where R = 0.88, F(10o42) = 14.29, S = 0.44, N = 53. The data utilized for this CASE study were obtained from (iv) K. pneumoniae MGH-2. a recent paper by Domagala and co-workers (5) and consist of 59 quinolones of diverse structures. These include well- -log MIC = 1.48 + 0.70n1Fl + 0.76n2F2 + 0.72n3F3 + known compounds (such as enoxacin, norfloxacin, cipro- 1.30n4F4 + 0.18 log P + 1.27n5F5 - 0.88n6F6 floxacin, etc.) as well as newly synthesized quinolines, 1,8-naphthyridines, pyrido[2,3-dlpyrimidines, and 4-pyri- where R = 0.86, F(7,45) = 18.51, S = 0.51, N = 53. VOL. 31, 1987 STRUCTURE OF QUINOLONE ANTIBACTERIAL AGENTS 1833

TABLE 1. Quinolone derivatives analyzed by the CASE TABLE 1-Continued methodology

lu Et F CF3-\N- H

lv Et F H2NCO-AIN- H

lw Et F NH2CH2CH2N N- H

Caom d R1 R6 7 R8 H lx Et F NCCHN N- Oxolinic Acid Et H H ly Et H NCCH2N\JN- Miloxacin OCH3 H

Norfloxacin Et F HN N- H H lz Et F (CH3)2NH(CH2)3NN-

Pefloxacin Et F CH3N N- H la' Et F CH3N N N- H

Amifloxacin NHCH3 F CH3N N- H lb, F O N IKL- H r~~~.r Ciprofloxacin > F HN N- H NH 11 H Rosoxacin Et H NC2> lc' Et F CH 3CN3 \I- N-

N- F S N- H AW-833 CH2CH2F F CH3N ld' Et \J-

ii Et H HN N- H le' Et F S N- H

ij Et F H H 1k Et H H NO2 (v) P. aeruginosa UI-18. 11 Et F C1 H MIC = 0.76 + + + im Et F F F -log 1.26n1F, 0.57n2F2 0.56n3F3 ln Et F CH3 H where R = 0.79, F(3,49) = 27.34, S = 0.56, N = 53. lo Et F III H (vi) S. aureus H228. -log MIC = 1.00 + O.50n1F, + O.59n2F2 - 0.64n3F3 + lp Et F HN N- F 1.15n4F4 + 0.66n5F5 where R = 0.85, F(5 47) = 23.88, S = 0.61, N = 53.

CH N N- F lq Et F 3 \-- (vii) S. pneumoniae SV-1. -log MIC = 0.62 + + 0.45n2F2 lr Et F CH3NH- H 1.09n1F, is Et F NH2CI2CH2S- H where R = 0.72, F(2,50) = 27.63, S = 0.52, N = 53. naFa is the number of occurrences of the fragment within it Et F ! H a molecular structure. Tables 5, 6, and 7 contain the experimentally observed activities as well as those calculated by Continued utilization of the above regression equations. The molecular 1834 KLOPMAN ET AL. ANTIMICROB. AGENTS CHEMOTHER.

TABLE 2. 1,8-Naphthyridine derivatives analyzed by the CASE TABLE 3. Additional compounds analyzed by the CASE methodology methodology 0 x 0 0 R6 N 0H2 N IO2 ~~N R7 R .~ N N R N Et I Et Et 3: X-H 7 6: X-NH2 Coqpound R6 7 Cnopound R

Nalidixic Acid H CH0 Piromidic Acid N_ Enoxacin F HN1aN-

Pipemidic Acid H N- SN\- 2c H HN N- r-\J 6a N_ 2d F S N- \- 6b HN N- 2e F H2NCH2CH2Ns- 2f H 6c CH3N N- }-\ 3 2g H CH3N N-N-CH- 7a 013

2h F 7b (S§QCH-cH-S 2i F EtO2C-N N- 7c CH30f 2j F S N- 0

F NN- 2k NH2 2CH2 Ofloxacin CH3N N jO2H NH11F\ 21 F 01 C-N3\- N- 2m NO2 013 0 2n NH2 013 Cinoxacin C02H 2o F 013 O0 NE Et 2p F H014-CH-

2q F 01 N -\JN-N-cH- unknown. Predictions as to the overall probability of a compound being active, based on the presence of statisti- 2r H CH3N N-0C-- cally significant fragments, are tabulated within Tables 5, 6, and 7. Compounds found to contain none of the fragments believed to be relevant to activity are presumed to be inactive and are annotated NB, i.e., no basis found to fragments incorporated within the QSAR equations are support activity. The success rate for all of the training sets listed in Fig. 2 through 8. All of the regression equations are was over 80%, with that for the gram-positive bacteria being relevant according to the criteria set by Topliss and Edwards over 90%. Results of quantitative (based on the QSAR (31). equations) and qualitative (based on the presence of statis- To test the predictive capabilities of the CASE program, tically significant fragments) predictions on test compounds we submitted each compound in the training data bases as an (which were not included within the training sets) are tabu- VOL. 31, 1987 STRUCTURE OF QUINOLONE ANTIBACTERIAL AGENTS 1835

TABLE 4. Distribution of actives and inactives of the QSAR regression equations leads to some general Cutoff No. of No. of conclusions as to what substituents optimize penetration Endpoint (mM) actives inactives into the cell. DNA gyrase cleavage 0.10 31 22 For gram-negative species, a C-7 substituent consisting of P. aeruginosa UI-18 0.19 33 20 a piperazine or an N-substituted piperazine leads to greater S. aureus H228 0.05 30 23 antimicrobial activity (see fragments 2 and 3 of Fig. 3, 1 and E. coli H560 0.04 37 16 2 of Fig. 4, 1 and 2 of Fig. 5, 2 of Fig. 6, and the E. coli (Vogel) 0.01 28 25 corresponding QSAR equations). The beneficial nature of S. pneumoniae SV-1 0.15 27 26 K. pneumoniae MGH-2 0.03 33 20 TABLE 5. Inhibition of DNA gyrase lated in Tables 8 through 14. All of the test compounds for Compound Expt Calculated' (Po)b the P. aeruginosa endpoint were correctly classified, while a Oxolinic acid 1.40 1.05 NBC success rate of 83% was observed for gyrase inhibition and Miloxacin 1.40 0.99 NB S. pneumoniae activities. Two-thirds of the unknowns for K. Norfloxacin 2.50 1.79 97.4 pneumoniae, E. coli (Vogel), and S. aureus were correctly Pefloxacin 2.50 1.73 97.4 classified. The lowest level of predictive power (50%) was Amifloxacin 2.10 1.85 97.4 observed for E. coli H560, the "unnatural" strain which has Ciprofloxacin 2.80 1.73 85.0 an abnormal response to nalidixic acid and related congeners. Rosoxacin 2.05 2.05 67.0 AM-833 2.15 2.59 97.4 Enoxacin 1.80 1.85 97.4 DISCUSSION Piromidic acid 0.90 0.99 14.0 Analysis of the fragments incorporated within the respec- Pipemidir acid 0.80 0.88 14.0 Cinoxacin 0.80 0.94 NB tive QSAR equations leads to indications as to what molec- ii 1.20 0.94 NB ular features are needed for gyrase inhibition as well as cell lj 0.65 0.94 NB penetration. It is assumed that the gyrase cleavage assay lk 0.50 0.88 NB measures the ability of a compound to inhibit the enzyme, 11 0.85 0.83 NB while activity against whole bacteria (expressed as MICs) lm 0.85 0.99 NB reflects, in large part, the cell wall penetration phenomena. ln 1.00 Q.88 NB Optimization of both activities would lead to an agent with lp 2.50 2.59 97.4 greater efficacy. Comparing the molecular features which lq 2.15 2.53 97.4 give rise to low MICs within gram-positive and gram- lr 1.15 0.99 NB it 2.10 1.68 97.4 negative bacterial strains (which differ in their cell wall lu 1.90 1.57 97.4 composition and thus possibly in drug permeability) can lead lv 1.70 1.79 97.4 to the identification of potentially broad-spectrum antibacte- lw 1.55 1.79 97.4 rial agents. The assumption is implicit that DNA gyrases lx 1.55 1.85 97.4 isolated from various microbial sources exhibit identical ly 1.30 0.99 NB sensitivities to quinolones; the validity of this assumption is lz 0.90 1.57 97.4 not established (28). However, it is known that the nature of la' 0.90 1.45 97.4 the cell envelope does control sensitivity to quinolones (13, lb' 1.70 1.28 97.4 14, lc' 2.15 1.79 97.4 16). ld' 1.80 1.73 97.4 With respect to inhibition of DNA gyrase, fragment 1 (Fig. le' 1.85 1.62 97.4 2) of the QSAR equation indicates a beneficial substitution 2c 0.60 0.58 14.0 pattern. Specifically, a fluorine at C-6 in combination with an 2d 1.25 1.85 85.0 amino functionality at C-7 confers enhanced activity. This 2e 0.75 0.94 NB disubstitution pattern is equally beneficial for both quino- 2f -0.15 -0.15 14.0 lines and 1,8-naphthyridines. Previous investigations (25, 26) 2g 0.10 0.10 14.0 have established the effectiveness of a C-6 fluorine in anti- 2h 2.10 1.85 85.0 bacterial activity. Domagala and co-workers (5) concluded 2i 1.35 1.79 97.4 that both gyrase inhibition as well as cell penetration are 2j 1.80 1.85 97.4 2k 1.75 1.85 97.4 enhanced by the presence of a C-6 fluorine. Furthermore, 21 1.75 1.79 97.4 structural tolerance was observed for the C-7 substituent. 2m 0.80 1.05 NB Fragment 1 reflects this tolerance by indicating that an amino 2o 1.00 1.05 NB functionality in general leads to enhanced activity. A size 2q 0.50 0.52 14.0 optimum, however, is not indicated by our results. Fragment 2r 0.04 0.04 14.0 2 has one occurrence within the data base, being present 6a 0.50 0.88 14.0 within rosoxazin. Fragment 3 is an inactive fragment occur- 6b 0.50 0.60 14.0 ring within some 1,8-naphthyridines and reinforces the con- 6c 0.50 0.94 14.0 clusion that the previously mentioned 6,7-disubstitution is 7a 0.50 0.58 20.0 relevant. 7b 0.24 0.24 20.0 biologically 7c 0.36 0.35 20.0 It is interesting to note that five of the six subsequent QSAR equations correlating MICs do not incorporate a a Calculated with the corresponding QSAR equation, expressed as the fragment which specifically indicates a C-6 fluorine. This negative logarithm of the MIC. b overall probability of being active, based on the presence of biologically leads one to conclude that cell permeability is predominantly relevant fragments. controlled by the nature of the C-7 substituent. Comparison C NB, No basis found to support activity, presumed to be inactive. 1836 KLOPMAN ET AL. ANTIMICROB. AGENTS CHEMOTHER.

TABLE 6. MICs against gram-negative bacteria' E. coli K. pneumoniae MGH-2 P. aeruginosa UI-18 H560 Vogel Comoound_ -___ rob- Prob- Prob- Calcu- Prob- Expt Calcu-Cacu ability Expt Cac-Calcu- ability Expt Calcu- ability Expt ability lated Mlated (% lated (%) latedae (%) Oxolinic acid NA NA NAb 3.10 3.06 75.0 3.09 2.99 80.0 1.62 0.76 75.0 Miloxacin 2.85 1.27 NB 2.80 2.85 75.0 3.09 2.73 80.0 1.32 0.76 75.0 Norfloxacin 3.50 3.37 100 4.00 3.12 83.0 3.69 3.06 83.0 3.22 2.59 98.2 Pefloxacin 3.50 2.99 100 4.00 3.48 83.0 3.99 3.28 87.0 2.92 2.47 99.9 Amifloxacin 4.00 2.99 100 3.40 3.26 83.0 3.24 3.01 87.0 2.62 1.91 99.6 Ciprofloxacin 4.00 2.84 100 3.70 3.18 83.0 3.54 3.14 95.1 2.92 2.02 93.4 Rosoxacin 3.15 1.27 85.0 3.15 2.22 20.0 2.84 1.92 67.0 1.67 0.76 67.0 AM-833 3.50 3.66 99.8 NA NA NA 3.29 3.19 100 2.37 3.06 86.0 Nalidixic acid 1.55 1.27 NB 1.50 1.69 0.80 1.59 1.58 NB 0.37 0.76 12.0 Enoxacin 3.50 2.84 100 3.50 2.90 83.0 3.54 2.79 83.0 2.62 2.02 93.4 Piromidic acid 0.90 1.27 NB 1.50 1.76 NB NA NA NA NA NA NA Pipemidic acid 2.00 2.32 98.8 2.30 1.60 NB 1.69 1.16 NB 1.67 2.02 93.4 Ofloxacin 3.50 2.47 98.8 3.50 3.41 95.1 3.54 3.19 97.0 2.97 1.91 86.0 Cinoxacin 0.90 1.27 NB NA NA NA 2.24 2.69 80.0 0.42 0.76 NB li 1.70 2.32 98.8 1.70 2.06 4.90 1.69 1.72 NB 1.07 2.02 93.4 ij 1.00 1.27 NB 2.45 2.07 NB NA NA NA 0.37 0.76 NB lk 0.90 1.27 NB 1.50 2.12 NB 1.34 1.80 NB 0.42 0.76 NB 11 2.25 1.80 97.0 2.50 2.64 80.0 2.24 1.85 67.0 0.72 0.76 NB lm 1.65 2.33 99.3 2.25 2.00 NB 1.64 1.65 100 0.42 0.76 NB ln NA NA NA 3.10 2.61 80.0 3.09 3.09 67.0 1.32 0.76 67.0 lo 2.30 2.33 99.6 2.30 2.66 80.0 1.04 1.87 NB 0.47 0.76 NB lp 3.50 3.37 100 3.20 4.20 83.0 3.54 4.42 100 2.32 2.02 93.4 lq 3.50 3.66 99.8 NA NA NA 2.94 3.24 100 2.62 3.06 86.0 lr 1.95 1.80 97.0 1.95 1.99 NB 1.64 1.63 NB NA NA NA ls 2.00 1.80 97.0 2.60 2.51 86.0 2.29 1.72 83.0 2.02 0.76 83.0 it NA NA NA 2.30 2.13 NB 2.29 1.81 67.0 1.37 1.32 79.0 lu 1.80 2.33 99.6 1.80 2.21 NB 1.04 1.91 NB 0.57 1.32 64.9 lv 1.15 2.33 99.6 1.75 2.02 NB 1.14 1.67 NB 0.87 1.32 79.0 lw NA NA NA 1.50 2.00 NB 1.04 1.65 NB 0.87 1.32 99.3 lx 2.65 2.99 100 2.95 2.95 67.0 2.64 1.60 NB 1.77 1.32 99.3 ly 0.90 1.27 NB 1.50 2.00 4.90 1.04 1.65 NB 0.52 0.76 NB lz 2.10 2.99 100 1.80 2.21 NB 1.79 1.91 NB 1.52 1.32 99.3 la' 1.50 2.33 99.6 2.15 2.25 NB 1.54 1.96 80.0 0.92 1.32 79.0 lb' 3.50 2.33 99.6 NA NA NA 2.39 2.07 80.0 2.12 1.32 79.0 lc' 3.20 2.99 100 2.60 1.99 75.0 NA NA NA NA NA NA ld' 3.20 3.37 100 3.20 3.46 75.0 2.94 3.07 75.0 2.02 2.59 98.7 le' 3.50 3.37 100 3.50 3.06 86.0 NA NA NA 2.62 2.59 98.7 2c 2.00 2.32 98.8 1.70 1.57 0.70 NA NA NA NA NA NA 2d 2.35 2.84 99.9 2.35 2.84 86.0 2.04 1.58 83.0 NA NA NA 2e 1.05 1.27 NB 1.50 1.68 NB 1.04 1.25 NB 0.77 0.76 80.0 2f 0.90 1.27 NB 1.14 1.14 3.90 1.34 1.21 17.0 0.42 0.76 12.0 2g 1.45 1.27 NB 1.29 1.29 3.90 1.44 1.39 17.0 0.52 0.76 12.0 2h 2.90 1.80 98.3 2.00 1.96 NB 1.99 1.60 NB 1.67 0.76 67.0 2i NA NA NA 1.50 1.72 NB NA NA NA 0.22 0.76 NB 2j 2.90 2.84 99.9 3.50 3.24 75.0 2.94 2.80 75.0 2.32 2.02 95.1 2k 1.45 2.47 99.9 NA NA NA 1.14 1.38 NB 0.87 0.76 NB 21 2.65 2.47 99.9 2.05 1.75 75.0 1.74 1.34 NB 1.17 0.76 NB 2m NA NA NA 1.50 1.94 17.0 1.04 1.58 NB 0.42 0.76 NB 2n 0.90 1.27 NB 1.50 1.78 17.0 1.04 1.38 NB 0.37 0.76 NB 2o 1.90 1.27 NB 1.90 1.90 17.0 1.59 1.52 NB 0.72 0.76 NB 2p 0.90 1.27 NB NA NA NA 1.34 1.17 17.0 0.42 0.76 12.0 2q 0.90 1.27 NB 0.55 0.55 0.10 1.14 1.34 17.0 0.57 0.76 12.0 2r 0.90 1.27 NB 1.50 1.51 3.90 1.04 1.67 NB 0.52 0.76 12.0 6a 0.90 1.27 NB 1.50 1.60 NB 1.04 1.16 NB 0.47 0.76 NB 6b 2.00 2.32 98.8 1.70 1.45 NB 0.97 0.97 NB 1.12 2.02 93.4 6c 2.00 1.27 89.0 2.30 3.07 83.0 1.69 2.77 87.0 0.52 0.76 NB 7a 0.90 1.27 NB 1.28 1.28 0.90 0.75 0.75 20.0 NA NA NA 7b 0.90 1.27 NB 1.50 1.53 0.20 1.04 1.06 20.0 0.42 0.76 NB 7c 0.90 1.27 NB 1.49 1.49 0.90 1.01 1.01 20.0 0.42 0.76 NB a See Table 5, footnotes a, b, and c for explanations of calculated values, probabilities, and NB, respectively. b NA, Not applicable; compound was excluded from the training set and utilized as a test compound (unknown). VOL . 31, 1987 STRUCTURE OF QUINOLONE ANTIBACTERIAL AGENTS 1837

TABLE 7. MICs against gram-positive bacteria' S. aureus H228 S. pneumoniae SV-1 Compound Proba- Proba- ExpAt Calcu-Clu Pbility Expt CacuCal Pbrilibty ltd ('%) ltd (%) Fragment #1 Activating Fragment #2: Activating Fragnmnt #3: Inactivating FIG. 2. Fragments utilized in the QSAR equation for estimating Oxolinic acid 2.2(0 2.25 80.0 0.42 0.62 NB inhibition of DNA gyrase. 0, Nonhydrogen substituent. Miloxacin 1.640 1.62 80.0 0.42 0.62 NB Norfloxacin 2.640 2.66 100 2.32 1.71 100 Pefloxacin 3.2(0 2.66 100 2.62 1.71 100 the piperazine group has previously been reported (25, Amifloxacin 2.3(0 2.21 100 1.42 1.71 100 26), Ciprofloxacin 2.0'5 2.21 100 2.32 0.62 100 as well as the observation that alkylation of the basic NH Rosoxacin 2.8'5 1.44 80.0 1.37 0.62 67.0 moiety leads to decreased activity. The work of Domagala et AM-833 NA NA NA 1.77 1.71 86.0 al. (5), however, has indicated that five- or six-membered Nalidixic acid 0.840 0.99 22.0 0.32 0.62 11.0 rings alone or with small substituents (fewer than three Enoxacin 2.040 2.21 85.0 2.02 1.71 86.0 atoms) exhibit good DNA gyrase inhibition as well as good Piromidic acid 1.3'5 0.99 NB 0.47 0.62 NB growth inhibitory properties. The results of the present Pipemidic acid 0.840 0.99 NB 0.47 0.62 NB CASE analysis are inconclusive with respect to which struc- Ofloxacin 2.9'5 2.84 95.8 2.67 1.71 86.0 ture (substituted or unsubstituted piperazine) is better over- Cinoxacin NA NA NA 0.42 0.62 NB all. Surprisingly, there seems to be a dependence on the ii 0.840 0.99 NB 0.77 0.62 NB lj 0.840 0.99 NB 0.32 0.62 NB bacterial strain. In some cases (e.g., K. pneumoniae), the lk 0.8 0 0.99 NB 0.42 0.62 NB contribution of the unsubstituted versus substituted piper- 11 1.9'5 1.44 80.0 0.42 0.62 NB azine was comparable (based on QSAR regression coeffi- lm 0.8 0 0.99 NB 0.42 0.62 NB cients), greater (P. aeruginosa and E. coli H560), or less [E. ln 2.240 1.44 80.0 0.32 0.62 NB coli (Vogel)]. It must be noted that the absence of a general lo 2.640 2.66 100 1.37 0.62 100 trend may be an artifact of our chosen cutoff values for lp 2.0'5 2.50 75.0 3.02 1.71 86.0 separating actives from inactives within each biological lq 2.9'5 2.50 75.0 NA NA NA endpoint, or it could reflect differences in the composition of lr 1.3 0 1.44 80.0 0.42 0.62 NB the cell envelope. K. pneumoniae, for example, has an ls 1.140 1.44 66.3 1.07 0.62 NB it NA NA NA 1.37 1.71 100 additional polysaccharide capsule. Our results, however, do lu 3.540 2.66 100 1.77 1.71 100 indicate that both the unsubstituted and the substituted lv 2.0'5 2.66 100 1.77 1.71 100 piperazines lead to greater biological activity. Furthermore, lw 1.4'5 2.66 100 0.87 1.71 100 the NH functionality can be replaced by a thioether linkage, lx 2.3'5 2.66 100 1.77 1.71 100 as exemplified by expanded fragment 2 of Fig. 3 and frag- ly NA NA NA NA NA NA ment 1 of Fig. 6. Expanded fragments differ in one position lz 1.540 2.66 100 1.22 1.71 100 along the connectivity path from the parent fragment. la' 2.440 2.66 100 NA NA NA A fragment pertaining to the 6,7-dioxymethylene bridge, lb' 0 2.14 2.66 100 1.47 1.71 100 as exemplified by oxolinic occurs lc' 1.7'5 2.66 100 1.47 1.71 100 acid, within three QSAR ld' 3.240 3.68 100 1.42 1.71 100 equations (fragment 5 of Fig. 4, fragment 3 of Fig. 5, and le' 4.740 2.66 100 NA NA NA fragment 5 of Fig. 7). Analysis of the respective regression 2c 0.840 0.99 22.0 0.77 0.62 11.0 2d 3.240 2.21 85.0 0.82 0.62 NB

2e 0.840 0.99 NB 0.47 0.62 NB F F 2f 0.8 0 0.99 22.0 0.42 0.62 11.0 2g 1.4'5 0.99 22.0 0.52 0.62 11.0 2h 3.1'5 2.21 85.0 1.97 1.52 75.0 Expanded:I 2i NA NA NA 0.57 1.71 86.0 2j 3.740 3.23 75.0 2.32 1.71 86.0 2k 0.840 0.82 58.6 1.47 1.71 86.0 21 0.840 0.82 58.6 0.87 1.71 86.0 2m NA NA NA NA NA NA Fragment #1: Activating 2n 0.840 0.99 20.0 0.67 0.62 20.0 2o 1.040 0.99 20.0 0.32 0.62 20.0 2p 0.840 0.99 22.0 0.42 0.62 11.0 HN 2q 1.1'5 0.99 22.0 0.57 0.62 11.0 2r 0.840 0.99 22.0 0.52 0.62 11.0 6a 0.8(0 0.99 NB 1.07 1.52 75.0 Expanded: 6b 0.84) 0.99 NB 0.82 0.62 NB /N 6c -1.7'9 2.40 20.0 NA NA NA 7a N 0.84Q 0.99 20.0 0.32 0.62 20.0 S I. 7b 0.840 0.99 20.0 0.42 0.62 20.0 ' 7c 0.840 0.99 20.0 0.42 0.62 20.0 a See Table 5 and 6 for explanations of calculated values, probabilities, NB, and NA. Fragment #2 : Activating Fragment #3 : Activating FIG. 3. Fragments utilized in the QSAR equation for estimating MICs against E. coli H560. 0, Nonhydrogen stbstituent. 1838 KLOPMAN ET AL. ANTIMICROB. AGENTS CHEMOTHER.

IN rl-.II 0 I(N_ H3C,N, Exd:

N 'N s Fragment 1 : Activating Fragment 12 : Activating Fragment 13: Activating I 2

Fragment tl: Activating Fragment *2: Activating Fragwnt t3: Activating FIG. 6. Fragments utilized in the QSAR equation for estimating <°-< iH2F MICs against P. aeruginosa UI-18. 0, Nonhydrogen substituent.

Fragment *4 : Inactivating Fragnt *5 : Activating ragwent t6: Activating

N N 1 I ) N N S NA 11 or I 0 N 11 11 _. /cC-CH2 'tH2-* Fragmnt *1 : Activating Fragment #2 : Activating Fragent #3 : Inactivating

Fragwnt *7 : Activating Fragwnt *8 : Activating Fragwnt *9: Inactivating FIG. 4. Fragments utilized in the QSAR equation for estimating s <04 MICs against E. coli (Vogel). 0, Nonhydrogen substituent. \ -J equations indicates that the contribution of the fragment to Fragwnt *4 : Activating Fragment *5 : Activating activity is moderate. Furthermore, the presence of this FIG. 7. utilized in the QSAR equation for estimating fragment within a molecule does not result in increased Fragments MICs S. aureus H228. 0, substituent. inhibition of DNA gyrase. against Nonhydrogen The most potent fragment derived from the QSAR equations refers to a sulfur atom to nitrogen, as in a thiazolidine 0 ring system. Fragment 7 of Fig. 4 [E. coli (Vogel)], fragmnent 4 of Fig. 5 (K. pneumoniae), and fragment 4 of Fig. 7 (S. this feature. Analysis of the respective aureus) incorporate Ir N-N N N<) QSAR equations revealed that in each case the regression coefficient is the highest of all the active fragments incorporated. Taking the thiazolidine ring as a prototype, it may be seen that expanded versions of fragment 2 of Fig. 3 (E. coli : *2 : Activating H560) and fragment 1 of Fig. 6 (P. aeruginosa) are also Fragment *1 Activating Fragment imbedded within the structure. This is illustrated in Fig. 9. FIG. 8. Fragments utilized in the QSAR equation for estimating MICs S. pneumoniae SV-1. 0, Nonhydrogen substituent. These expanded fragments are assigned the value of the against regression coefficient of the primary fragment. The respec- TABLE 8. Predictions of inhibition of DNA gyrase' tive QSAR equations indicate that these values are the Probability highest among the variables. Thus, our results indicate that Compound Expt Calculated (%) Nalidixic acid 0.65 <1.00 14.0 Ofloxacin 1.85 1.80 97.4 lo 1.80 1.60 85.0 CH3-N N ls 1.80 <1.00 NB <0 T 2n 0.50 <1.00 NB N 2p 0.75 <1.00 14.0 H a See Table 5 for explanations of calculate4 values, probabilities, and NB.

Fragmnt t1 : Activating Fragrnt *2 : Activating Fragwnt *3 : Activkting TABLE 9. Predicted MICs against P. aeruginosa UI-18a

0 Compound Expt Calculated Probability

S NA Piromidic acid 0.47 <0.72 NB vI' lr 0.42 <0.72 NB lc' 2.37 1.32 99.3 2c 1.37 2.02 65.9 1.72 2.02 95.1 *4 : *5 : Activating Fragwnt #6 : Inactivating 2d Fragent Activating Frarmgnt 7a 0.22 <0.72 NB FIG. 5. Fragments utilized in the QSAR equation for estimating a MICs against K. pneumoniae MGH-2. 0, Nonhydrogen substituent. See Table 5 for explanations of calculated values, probabilities, and NB. VOL . 31, 1987 STRUCTURE OF QUlNOLONE ANTIBACTERIAL AGENTS 1839

TABLE 10. Predicted MICs against K. pneumoniae MGH-2" TABLE 14. Predictions of MICs against S. pneumoniae SV-1l Compound Expt Calculated Probability Compound Expt Calculated Probability Piromidic acid 1.04 <1.54 NB lq 2.07 1.27 86.0 lj 2.19 <1.54 NB ly 0.52 <0.82 87.0 lc' 2.34 <1.54 NB la' 1.82 1.72 100 le' 3.24 1.84 83.0 le' 1.42 1.72 100 2c 1.39 <1.54 NB 2m 0.42 <0.82 20.0 2i 1.04 <1.54 NB 6c 0.52 <0.82 NB a See Table 5 for explanations of calculated values, probabilities, and NB. a See Table 5 for explanations of calculated values, probabilities, and NB.

TABLE 11. Predictions MICs against E. coli H560' Probability Compound Expt Calculated (%) Oxolinic acid 3.10 <1.40 NB ln 2.80 1.80 97.0 it 2.30 2.35 99.6 FIG. 9. Imbedded fragment within the thiazolidine ring system. 1w 1.15 3.00 100 2i 0.90 2.45 99.9 2m 0.90 <1.40 NB TABLE 15. Predictions of biological activity on 1-ethyl-7- a See Table 5 for explanations of calculated values, probabilities, and NB. thiazolidine-6,8-difluoro-1,4-dihydro-4-oxo-3-quinoline carboxylic acid' 0 a C-7 substituent incorporating a sulfur ,B to nitrogen would F CO2H impart potent broad-spectrum antibacterial activity. Further work on these types of substituents is clearly indicated. The knowledge gained by this CASE study may be applied to the design and evaluation of novel antimicrobial agents. F For example, we believe that a quinoline incorporating the CH2CH3 thiazolidine ring at C-7 with fluorines at C-6 and C-8 will be Probability Calculated an interesting compound to study. This particular structure Endpoint does not exist within any of our training data bases. The Gyrase inhibition 97.4 2.55 proposal that 1-ethyl-7-thiazolidine-6,8-difluoro-1,4-dihydro- P. aeruginosa UI-18 95.1 2.02 4-oxo-3-quinolinecarboxylic acid would be a broad-spectrum S. aureus H228 90.0 4.55 antibacterial agent is based on fragments incorporated within E. coli H560 99.9 3.35 the QSAR equations. As discussed above, the thiazolidine E. coli (Vogel) 75.0 3.40 ring confers exceptional growth inhibitory properties (MICs), S. pneumoniae SV-1 86.0 1.72 while the fluorines ortho to an amino functionality contribute K. pneumoniae MGH-2 100.0 3.04 to gyrase inhibition (see fragment 1 of Fig. 2). The occur- a See Table 5 for explanation of calculated values and probabilities. rence of fragment 1 twice within the molecular structure leads to an extremely active gyrase inhibitor. The calculated potencies and overall probabilities for each biological endpoint are listed in Table 15. TABLE 12. Predictions of MICs against E. coli (Vogel)' In conclusion, the application of the CASE methodology Compound Expt Calculated Probability resulted in the automatic generation of molecular fragments useful in delineating features relevant to inhibition of DNA AM-833 3.30 3.40 83.0 gyrase from those necessary for bacterial penetration. Our Cinoxacin 1.95 2.80 75.0 conclusions with respect to structural features necessary for lq 3.20 3.45 83.0 activity against DNA gyrase agree with previous work (5). lb' 3.00 <2.00 NB The regression equations derived in our study indicate that 2k 1.50 <1.50 NB the structural requirements at C-7 for enzyme inhibition are 2p 1.65 <1.50 12.0 not rigid, while the requirements (at C-7) for enhanced cell a See Table 5 for explanations of calculated values, probabilities, and NB. permeability are specific. New aspects of the C-7 substituent have been deduced from this study which may lead to the design of broad-spectrum antibacterial agents with therapeu- TABLE 13. Predictions MICs against S. aureus H228a tic potential. Compound Expt Calculated Probability ACKNOWLEDGMENTS AM-833 2.65 2.50 75.0 Cinoxacin 0.80 2.10 80.0 Support by the Environmental Protection Agency and the Office it 2.90 <1.30 100 of Naval Research through its Selected Research Opportunities ly 1.15 <1.30 88.0 Program is highly appreciated. 2i 2.10 <1.30 58.6 LITERATURE CITED 2m 1.05 <1.30 20.0 1. Albrecht, R. 1977. Development of antibacterial agents of the a See Table 5 for explanations of calculated values and probabilities. nalidixic acid type. Prog. Drug Res. 21:9-104. 1840 KLOPMAN ET AL. ANTIMICROB. AGENTS CHEMOTHER.

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