Design and tests of prospective property predictions for novel antimalarial 2-aminopropylaminoquinolones

Abstract

There is a pressing need to improve the efficiency of drug development, and nowhere is that need more clear than in the case of neglected diseases like malaria. The peculiarities of pyrimidine metabolism in Plasmodium species make inhibition of dihydroorotate dehydrogenase (DHODH) an attractive target for antimalarial drug design. By applying a pair of complementary quantitative structure-activity relationships derived for inhibition of a truncated, soluble form of the enzyme from Plasmodium falciparum (s-PfDHODH) to data from a large-scale phenotypic screen against cultured parasites, we were able to identify a class of antimalarial leads that inhibit the enzyme and abolish parasite growth in blood culture. Novel analogs extending that class were designed and synthesized with a goal of improving potency as well as the general pharmacokinetic and toxicological profiles. Their synthesis also represented an opportunity to prospectively validate our in silico property predictions. The seven analogs synthesized exhibited physicochemical properties in good agreement with prediction, and five of them were more active against P. falciparum growing in blood culture than any of the compounds in the published lead series. The particular analogs prepared did not inhibit s-PfDHODH in vitro, but advanced biological assays indicated that other examples from the class did inhibit intact PfDHODH bound to the mitochondrial membrane. The new analogs, however, killed the parasites by acting through some other, unidentified mechanism 24-48 h before PfDHODH inhibition would be expected to do so.

Keywords: ADME; Antimalarial; Dihydroorotate dehydrogenase; Drug design; PBPK; QSAR.

Fig. 1

Performance plots for the ANNE regression models developed for in vitro PfDHODH inhibition built from literature data. The plot for Model A is on the left and the plot for Model B is on the right. Labeled points correspond to data from Supplementary Table S1: (a) Tz18; (b) P05; (c) G47; (d) D10; and (e) Tz11

Fig. 2

Comparing property distributions across three representative classes: triazolopyrimidines (Tzs), aminopropylaminoquinolones (APAQs) and diphenylureas (DPUs). The portion of each representative structure highlighted in blue corresponds to the class scaffold. Growth inhibition is shown as %inhibition vs. P. falciparum strains 3D7 and DD2, which are chloroquine-sensitive and -resistant, respectively. pKi_pred values are the negative log of the predicted K_i in µM, so a larger number indicates higher potency; their distribution for Models A and B are shown. ADMET Risk is a measure of likely development liabilities that can range from 0 to 24 [6]

Fig. 3

Scaffold and structures of compounds associated with the APAQ lead series

Fig. 4

Four of the 12 APAQ synthesis targets initially put out for bids

Fig. 5

Initial scaffold used for R-Group explosion versus the final, simplified scaffold shared by the analogs that were synthesized

Scheme 1

Syntheses of three variations on the free amino APAQ scaffold 7

Scheme 2

Synthesis of 2-chloro-4,6-dimethoxy quinoline

Scheme 3

Synthesis of targeted APAQs 8–11

Scheme 4

Synthesis of imidazolinone analogs 12a and 12b

Fig. 6

Human concentration–time profile expected for 9 based on PBPK simulation using GastroPlus. Pharmacokinetic parameters were taken from experimental values where available and estimated using the QSAR models in ADMET Predictor otherwise. Conc concentration, K_i predicted inhibition constant for PfDHODH when plasma protein binding is taken into account

Fig. 7

Active GSK APAQs from which P. falciparum grown in blood culture were rescued by transfection with ScDHODH

Fig. 8

Malarial methionyl t-RNA synthetase (PfMRS) inhibitors with antimalarial activity