Anticancer activity features of imidazole-based ionic liquids and lysosomotropic detergents: in silico and in vitro studies.

Long-chain imidazole-based ionic liquids (compounds 2, 4, 9) and lysosomotropic detergents (compounds 7, 3, 8) with potent anticancer activity were synthesized. Their inhibitory activities against neuroblastoma and leukaemia cell lines were predicted by the new in silico QSAR models. The cytotoxic activities of the synthesized imidazole derivatives were investigated on the SK-N-DZ (human neuroblastoma) and K-562 (human chronic myeloid leukaemia) cell lines. Compounds 2 and 7 showed the highest in vitro cytotoxic effect on both cancer cell lines. The docking procedure of compounds 2 and 7 into the NAD+ coenzyme binding site of deacetylase Sirtuin-1 (SIRT-1) showed the formation of protein-ligand complexes with calculated binding energies of - 8.0 and - 8.1 kcal/mol, respectively. The interaction of SIRT1 with compounds 2, 7 and 9 and the interaction of Bromodomain-containing protein 4 (BRD4) with compounds 7 and 9 were also demonstrated by thermal shift assay. Compounds 2, 4, 7 and 9 inhibited SIRT1 deacetylase activity in the SIRT-Glo assay. Compounds 7 and 9 showed a moderate inhibitory activity against Aurora kinase A. In addition, compounds 3, 4, 8 and 9 inhibited the Janus kinase 2 activity. The results obtained showed that long-chain imidazole derivatives exhibited cytotoxic activities on K562 leukaemia and SK-N-DZ neuroblastoma cell lines. Furthermore, these compounds inhibited a panel of molecular targets involved in leukaemia and neuroblastoma tumorigenesis. All these results suggest that both long-chain imidazole-based ionic liquids and lysosomotropic detergents may be an effective alternative for the treatment of neuroblastoma and chronic myeloid leukemia and merit further investigation.

In Vitro Evaluation of In Silico Screening Approaches in Search for Selective ACE2 Binding Chemical Probes.

New models for ACE2 receptor binding, based on QSAR and docking algorithms were developed, using XRD structural data and ChEMBL 26 database hits as training sets. The selectivity of the potential ACE2-binding ligands towards Neprilysin (NEP) and ACE was evaluated. The Enamine screening collection (3.2 million compounds) was virtually screened according to the above models, in order to find possible ACE2-chemical probes, useful for the study of SARS-CoV2-induced neurological disorders. An enzymology inhibition assay for ACE2 was optimized, and the combined diversified set of predicted selective ACE2-binding molecules from QSAR modeling, docking, and ultrafast docking was screened in vitro. The in vitro hits included two novel chemotypes suitable for further optimization.

AI-Powered Virtual Screening of Large Compound Libraries Leads to the Discovery of Novel Inhibitors of Sirtuin-1.

The discovery of new scaffolds and chemotypes via high-throughput screening is tedious and resource intensive. Yet, there are millions of small molecules commercially available, rendering comprehensive in vitro tests intractable. We show how smart algorithms reduce large screening collections to target-specific sets of just a few hundred small molecules, allowing for a much faster and more cost-effective hit discovery process. We showcase the application of this virtual screening strategy by preselecting 434 compounds for Sirtuin-1 inhibition from a library of 2.6 million compounds, corresponding to 0.02% of the original library. Multistage in vitro validation ultimately confirmed nine chemically novel inhibitors. When compared to a competitive benchmark study for Sirtuin-1, our method shows a 12-fold higher hit rate. The results demonstrate how AI-driven preselection from large screening libraries allows for a massive reduction in the number of small molecules to be tested in vitro while still retaining a large number of hits.