Anthranilamides with quinoline and ß-carboline scaffolds: design, synthesis, and biological activity.

In the present study, we report the design and synthesis of novel amide-type hybrid molecules based on anthranilic acid and quinoline or ß-carboline heterocyclic scaffolds. Three types of biological screenings were performed: (i) in vitro antiproliferative screening against a panel of solid tumor and leukemia cell lines, (ii) antiviral screening against several RNA viruses, and (iii) anti-quorum sensing screening using gram-negative Chromobacterium violaceum as the reporter strain. Antiproliferative screening revealed a high activity of several compounds. Anthranilamides 12 and 13 with chloroquine core and halogenated anthranilic acid were the most active agents toward diverse cancer cell lines such as glioblastoma, pancreatic adenocarcinoma, colorectal carcinoma, lung carcinoma, acute lymphoblastic, acute myeloid, chronic myeloid leukemia, and non-Hodgkin lymphoma, but also against noncancerous cell lines. Boc-protected analogs 2 and 3 showed moderate activities against the tested cancer cells without toxic effects against noncancerous cells. A nonhalogenated quinoline derivative 10 with N-benzylanthranilic acid residue was equally active as 12 and 13 and selective toward tumor cells. Chloroquine and quinoline anthranilamides 10-13 exerted pronounced antiviral effect against human coronaviruses 229E and OC43, whereas 12 and 13 against coronavirus OC43 (EC50 values in low micromolar range; selectivity indices from 4.6 to > 10.4). Anthranilamides 14 and 16 with PQ core inhibited HIV-1 with EC50 values of 9.3 and 14.1 µM, respectively. Compound 13 displayed significant anti-quorum/biofilm effect against the quorum sensing reporter strain (IC50 of 3.7 µM) with no apparent bactericidal effect.

Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation.

The pharmacological arsenal against the COVID-19 pandemic is largely based on generic anti-inflammatory strategies or poorly scalable solutions. Moreover, as the ongoing vaccination campaign is rolling slower than wished, affordable and effective therapeutics are needed. To this end, there is increasing attention toward computational methods for drug repositioning and de novo drug design. Here, multiple data-driven computational approaches are systematically integrated to perform a virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the list of prioritized drugs, a subset of representative candidates to test in human cells is selected. Two compounds, 7-hydroxystaurosporine and bafetinib, show synergistic antiviral effects in vitro and strongly inhibit viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, the relevant chemical substructures of the identified drugs are extracted to provide a chemical vocabulary that may help to design new effective drugs.