Pelitinib

Accurate and efficient prediction of high energy ligand conformations is important in structure‐based drug discovery for the exclusion of unrealistic structures in docking‐based virtual screening and de novo design approaches. In this work, we constructed a database of 140 solution conformers from 20 druglike molecules of varying size and chemical complexity, with energetics evaluated at the DLPNO‐CCSD(T)/complete basis set (CBS) level. We then assessed a selection of machine learning potentials and semiempirical quantum mechanical models for their ability to predict conformational energetics. The GFN2‐xTB tight binding density functional method correlates with reference conformer energies, yielding a Kendall's τ of 0.63 and mean absolute error of 2.2 kcal/mol. As putative internal energy filters for screening, we find that the GFN2‐xTB, ANI‐2x and MACE‐OFF23(L) models perform well in identifying low energy conformer geometries, with sensitivities of 95 %, 89 % and 95 % respectively, but display a reduced ability to exclude high energy conformers, with respective specificities of 80 %, 61 % and 63 %. The GFN2‐xTB method therefore exhibited the best overall performance and appears currently the most suitable of the three methods to act as an internal energy filter for integration into drug discovery workflows. Enrichment of high energy conformers in the training of machine learning potentials could improve their performance as conformational filters.

The main protease (Mpro) of SARS‐CoV‐2 is an attractive drug target for antivirals, as this enzyme plays a key role in virus replication. Drug repurposing is a promising option for the treatment of coronavirus disease 2019 (COVID‐19). Recently, a number of FDA‐approved drugs have been identified as Mpro inhibitors, but stringent hit validation is lacking. In this study, we rigorously reevaluated the in vitro inhibition of the Mpro enzyme by repurposed drugs via combined experiments, including the fluorescence resonance energy transfer (FRET) assay, fluorescence polarization (FP) assay, and protease biosensor cleavage assay. Our results from a set of in vitro assays revealed that boceprevir is a potential Mpro inhibitor, but other repurposed drugs, including atazanavir, dipyridamole, entrectinib, ethacridine, glecaprevir, hydroxychloroquine, ivermectin, meisoindigo, pelitinib, raloxifene, roxatidine acetate, saquinavir, teicoplanin, thonzonium bromide, and valacyclovir, are not. Our research highlights that the use of candidate Mpro inhibitors from primary screening warrants further comprehensive studies before the reporting of new findings.