In silico Design and Synthesis of Tetrahydropyrimidinones and Tetrahydropyrimidinethiones as Potential Thymidylate Kinase Inhibitors Exerting Anti-TB Activity Against Mycobacterium tuberculosis.

BACKGROUND AND PURPOSE: Tuberculosis has been reported to be the worldwide leading cause of death resulting from a sole infectious agent. The emergence of multidrug-resistant tuberculosis and extensively drug-resistant tuberculosis has made the battle against the infection more difficult since most currently available therapeutic options are ineffective against these resistant strains. Therefore, novel molecules need to be developed to effectively treat tuberculosis disease. Preliminary docking studies revealed that tetrahydropyrimidinone derivatives have favorable interactions with the thymidylate kinase receptor. In the present investigation, we report the synthesis and the mycobacterial activity of several pyrimidinones and pyrimidinethiones as potential thymidylate kinase inhibitors. METHODS: The title compounds (1a-d) and (2a-b) were synthesized by a one-pot three-component Biginelli reaction. They were subsequently characterized and used for whole-cell anti-TB screening against H37Rv and multidrug-resistant (MDR) strains of Mycobacterium tuberculosis (MTB) by the resazurin microplate assay (REMA) plate method. Molecular modeling was conducted using the Accelry's Discovery Studio 4.0 client program to explain the observed bioactivity of the compounds. The pharmacokinetic properties of the synthesized compounds were predicted and analyzed. RESULTS: Of the compounds tested for anti-TB activity, pyrimidinone 1a and pyrimidinethione 2a displayed moderate activity against susceptible MTB H37Rv strains at 16 and 32 µg/mL, respectively. Only compound 2a was observed to exert modest activity at 128 µg/mL against MTB strains with cross-resistance to rifampicin and isoniazid. The presence of the trifluoromethyl group was essential to retain the inhibitory activity of compounds 1a and 2a. Molecular modeling studies of these compounds against thymidylate kinase targets demonstrated a positive correlation between the bioactivity and structure of the compounds. The in-silico ADME (absorption, distribution, metabolism, and excretion) prediction indicated favorable pharmacokinetic and drug-like properties for most compounds. CONCLUSION: Pyrimidinone 1a and pyrimidinethione 2a were identified as the leading compounds and can serve as a starting point to develop novel anti-TB therapeutic agents.

2D- and 3D-QSAR Modeling of Imidazole-Based Glutaminyl Cyclase Inhibitors.

BACKGROUND: Glutaminyl Cyclase (QC) is a novel target in the battle against Alzheimer's disease, a highly prevalent neurodegenerative disorder. QC inhibitors have the potential to be developed as therapeutically useful anti-Alzheimer's disease agents. METHODS: Linear and non-linear 2D-Quantitative Structure-Activity Relationship (QSAR) models were developed using Stepwise Multiple Linear Regression (S-MLR) and neural networks. Partial least squares (PLS) method was used to develop a 3D-QSAR model. Also, the developed models were used in virtual screening of the ZINC database to identify potential QC inhibitors. RESULTS: The 2D neural network model showed superior predictive ability, as demonstrated by the validation parameters R2 = 0.933, Q2 = 0.886 and R2 pred = 0.911. The 3D-QSAR model's steric and electrostatic fields' isocontour maps were visualized and revealed important structural requirements associated with good activity. The virtual screening identified six compounds as potentially active QC inhibitors with improved pharmacokinetic profiles. CONCLUSION: The developed QSAR models can be used to predict the activity of compounds not yet synthesized and prioritized for their synthesis and biological evaluation. Also, potentially active QC inhibitors have been identified with attractive lead-like properties that can be used to develop anti- Alzheimer's disease agents.