Tunable Cysteine-Targeting Electrophilic Heteroaromatic Warheads Induce Ferroptosis

Once considered potential liabilities, the modern era witnesses a renaissance of interest in covalent inhibitors in drug discovery. The available toolbox of electrophilic warheads is limited by constraints on tuning reactivity and selectivity. Following our work on a class of ferroptotic agents termed CETZOLEs, we discovered new tunable heterocyclic electrophiles which are capable of inducing ferroptosis. The biological evaluation demonstrated that thiazoles with an alkyne electrophile at the 2-position selectively induce ferroptosis with high potency. Density functional theory calculations and NMR kinetic studies demonstrated the ability of our heterocycles to undergo thiol addition, an apparent prerequisite for cytotoxicity. Chemoproteomic analysis indicated several potential targets, the most prominent among them being GPX4 protein. These results were further validated by western blot analysis and the cellular thermal shift assay. Incorporation of these heterocycles into appropriate pharmacophores generated highly cytotoxic agents such as the analogue BCP-T.A, with low nM IC50 values in ferroptosis-sensitive cell lines.

Hybrid Design of Isonicotinic Acid Hydrazide Derivatives: Machine Learning Studies, Synthesis and Biological Evaluation of their Antituberculosis Activity

BACKGROUND

Tuberculosis (TB) is an infection disease caused by Mycobacterium tuberculosis (Mtb) bacteria. One of the main causes of mortality from TB is the problem of Mtb resistance to known drugs.

OBJECTIVE

The goal of this work is to identify potent small molecule anti-TB agents by machine learning, synthesis and biological evaluation.

METHODS

The On-line Chemical Database and Modeling Environment (OCHEM) was used to build predictive machine learning models. Seven compounds were synthesized and tested in vitro for their antitubercular activity against H37Rv and resistant Mtb strains.

RESULTS

A set of predictive models was built with OCHEM based on a set of previously synthesized isoniazid (INH) derivatives containing a thiazole core and tested against Mtb. The predictive ability of the models was tested by a 5-fold cross-validation, and resulted in balanced accuracies (BA) of 61-78% for the binary classifiers. Test set validation showed that the models could be instrumental in predicting anti- TB activity with a reasonable accuracy (with BA = 67-79 %) within the applicability domain. Seven designed compounds were synthesized and demonstrated activity against both the H37Rv and multidrugresistant (MDR) Mtb strains resistant to rifampicin and isoniazid. According to the acute toxicity evaluation in Daphnia magna neonates, six compounds were classified as moderately toxic (LD50 in the range of 10-100 mg/L) and one as practically harmless (LD50 in the range of 100-1000 mg/L).

CONCLUSION

The newly identified compounds may represent a starting point for further development of therapies against Mtb. The developed models are available online at OCHEM http://ochem.eu/article/11 1066 and can be used to virtually screen for potential compounds with anti-TB activity.