Improved Inhibitors Targeting the Thymidylate Kinase of Multidrug-Resistant Mycobacterium tuberculosis with Favorable Pharmacokinetics

This study aims to design improved inhibitors targeting the thymidylate kinase (TMK) of Mycobacterium tuberculosis (Mtb), the causative agent of infectious disease tuberculosis that is associated with high morbidity and mortality in developing countries. TMK is an essential enzyme for the synthesis of bacterial DNA. We have performed computer-aided molecular design of MtbTMK inhibitors by modification of the reference crystal structures of the lead micromolar inhibitor TKI1 1-(1-((4-(3-Chlorophenoxy)quinolin-2-yl)methyl)piperidin-4-yl)-5-methylpyrimidine-2,4(1H,3H)-dione bound to TMK of Mtb strain H37Rv (PDB entries: 5NRN and 5NR7) using the computational approach MM-PBSA. A QSAR model was prepared for a training set of 31 MtbTMK inhibitors with published inhibitory potencies () and showed a significant correlation between the calculated relative Gibbs free energies of the MtbTMK–TKIx complex formation and the observed potencies. This model was able to explain approximately 95% of the variation in the in vitro inhibition data and validated our molecular model of MtbTMK inhibition for the subsequent design of new TKI analogs. Furthermore, we have confirmed the predictive capacity of this complexation QSAR model by generating a 3D QSAR PH4 pharmacophore-based model. A satisfactory correlation was also obtained for the validation PH4 model of MtbTMK inhibition (R² = 0.84). We have extended the hydrophobic m-chloro-phenoxyquinolin-2-yl group of TKI1 that can occupy the entry into the thymidine binding cleft of MtbTMK by alternative larger hydrophobic groups. Analysis of residue interactions at the enzyme binding site made it possible to select suitable building blocks to be used in the preparation of a virtual combinatorial library of 28,900 analogs of TKI1. Structural information derived from the complexation model and the PH4 pharmacophore guided the in silico screening of the library of analogs and led to the identification of new potential MtbTMK inhibitors that were predicted to be effective in the low nanomolar concentration range. The QSAR complexation model predicted an inhibitory concentration of 9.5 nM for the best new virtual inhibitor candidate TKI 13_1, which represents a significant improvement in estimated inhibitory potency compared to TKI1. Finally, the stability of the MtbTMK–inhibitor complexes and the flexibility of the active conformation of the inhibitors were assessed by molecular dynamics for five top-ranking analogs. This computational study resulted in the discovery of new MtbTMK inhibitors with predicted enhanced inhibitory potencies, which also showed favorable predicted pharmacokinetic profiles.