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Butyrylcholinesterase (BChE) inhibitors were identified from a collection containing cinchonine, cinchonidine and synthetic derivatives, and further characterized using cytotoxicity and molecular docking studies. The most active ones were: (10≡)-10,11-dibromo-10,11-dihydrocinchonidine (11), a competitive inhibitor with K i = 3.45±0.39 µM, and IC 50 BChE = 9.83±0.30 µM / human (h)BChE = 34.47±4.63 and O-(trimethylsilyl)cinchonine (15), a mixed inhibitor with K iuc = 1.73±0.46 µM and K ic = 0.85±0.26 µM, and IC 50 BChE = 0.56±0.14 µM / hBChE = 0.24±0.04. In cytotoxicity experiments, ≥80% of the cells remained viable when exposed to concentrations of up to 80 µM of both inhibitors in four different cell lines, including neurons. Due to the bulkier trimethylsilyl side group of 15, it covered the active site of hBChE better than 11 with an OH-group while not being able to fit into the active site gorge of hAChE, thus explaining the selectivity of 15 towards hBChE.

The bacterial ribosome is an established target for anti-bacterial therapy since decades. Several inhibitors have already been developed targeting both defined subunits (50S and 30S) of the ribosome. Aminoglycosides and tetracyclines are two classes of antibiotics that bind to the 30S ribosomal subunit. These inhibitors can target multiple active sites on ribosome that have a complex structure. To screen putative inhibitors against 30S subunit of the ribosome, the crystal structures in complex with various known inhibitors were analyzed using pharmacophore modeling approach. Multiple active sites were considered for building energy-based three-dimensional (3D) pharmacophore models. The generated models were validated using enrichment factor on decoy data-set. Virtual screening was performed using the developed 3D pharmacophore models and molecular interaction towards the 30S ribosomal unit was analyzed using the hits obtained for each pharmacophore model. The hits that were common to both streptomycin and paromomycin binding sites were identified. Further, to predict the activity of these hits a robust 2D-QSAR model with good predictive ability was developed using 16 streptomycin analogs. Hence, the developed models were able to identify novel inhibitors that are capable of binding to multiple active sites present on 30S ribosomal subunit.