Search

Structure- and ligand-based virtual-screening methods (docking, 2D- and 3D-similarity searching) were analyzed for their effectiveness in virtual screening against FFAR2. To evaluate the performance of these methods, retrospective virtual screening was performed. Statistical quality of the methods was evaluated by BEDROC and RIE. The results revealed that electrostatic similarity search protocol using EON (ET combo) outperformed all other protocols with outstanding enrichment of >95% in top 1% and 2% of the dataset with an AUC of 0.958. Interestingly, the hit lists that are obtained from different virtual-screening methods are generally highly complementary to hits found from electrostatic similarity searching. These results suggest that considering electrostatic similarity searching first increases the chance of identifying more (and more diverse) active compounds from a virtual-screening campaign. Accordingly, prospective virtual screening using electrostatic similarity searching was used to identify novel FFAR2 ligands. The discovered compounds provide new chemical matter starting points for the initiation of a medicinal chemistry campaign., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

We report herein the generation and validation of a 3D-QSAR model based on a set of antimalarials previously described by us and characterized by a clotrimazole-based pharmacophore. A novel series of derivatives was synthesized and showed activity against Plasmodium falciparum chloroquine-sensitive (CQ-S) and chloroquine-resistant (CQ-R) strains. Gratifyingly, compounds 35a-c showed interesting activity against P. falciparum CQ-R strains with improved predicted physico-chemical properties., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Computer-aided drug design scaffold hopping strategies were utilized to identify new classes of CB2 agonists when compounds of an established series with low nanomolar potency were challenging to optimize for good drug-like properties. Use of ligand-based design strategies through BI Builder (a tool for de novo design) and PharmShape (a virtual screening software package) approaches led to the discovery of new chemotypes. Specifically, compounds containing azetidine-, proline-, and piperidine-based cores were found to have low nanomolar and picomolar CB2 agonist activities with drug-like properties considered appropriate for early profiling., (Copyright © 2014 Elsevier Ltd. All rights reserved.)