Identification of Dual Inhibitors Targeting Main Protease (Mpro) and Cathepsin L as Potential Anti-SARS-CoV-2 Agents.

In this structure-activity relationship (SAR) study, we report the development of dual inhibitors with antiviral properties targeting the SARS-CoV-2 main protease (Mpro) and human cathepsin L (hCatL). The novel molecules differ in the aliphatic amino acids at the P2 site and the fluorine position on the phenyl ring at the P3 site. The identified dual inhibitors showed Ki values within 1.61 and 10.72 µM against SARS-CoV-2 Mpro; meanwhile, Ki values ranging from 0.004 to 0.701 µM toward hCatL were observed. A great interdependency between the nature of the side chain at the P2 site and the position of the fluorine atom was found. Three dual-targeting inhibitors exhibited antiviral activity in the low micromolar range with CC50 values >100 µM. Docking simulations were executed to gain a deeper understanding of the SAR profile. The findings herein collected should be taken into consideration for the future development of dual SARS-CoV-2 Mpro/hCatL inhibitors.

Streamlining Large Chemical Library Docking with Artificial Intelligence: the PyRMD2Dock Approach.

The present contribution introduces a novel computational protocol called PyRMD2Dock, which combines the Ligand-Based Virtual Screening (LBVS) tool PyRMD with the popular docking software AutoDock-GPU (AD4-GPU) to enhance the throughput of virtual screening campaigns for drug discovery. By implementing PyRMD2Dock, we demonstrate that it is possible to rapidly screen massive chemical databases and identify those with the highest predicted binding affinity to a target protein. Our benchmarking and screening experiments illustrate the predictive power and speed of PyRMD2Dock and highlight its potential to accelerate the discovery of novel drug candidates. Overall, this study showcases the value of combining AI-powered LBVS tools with docking software to enable effective and high-throughput virtual screening of ultralarge molecular databases in drug discovery. PyRMD and the PyRMD2Dock protocol are freely available on GitHub (https://github.com/cosconatilab/PyRMD) as an open-source tool.

A cyanine-based NIR fluorescent Vemurafenib analog to probe BRAFV600E in cancer cells.

BRAF represents one of the most frequently mutated protein kinase genes and BRAFV600E mutation may be found in many types of cancer, including hairy cell leukemia (HCL), anaplastic thyroid cancer (ATC), colorectal cancer and melanoma. Herein, a fluorescent probe, based on the structure of the highly specific BRAFV600E inhibitor Vemurafenib (Vem, 1) and featuring the NIR fluorophore cyanine-5 (Cy5), was straightforwardly synthesized and characterized (Vem-L-Cy5, 3), showing promising spectroscopic properties. Biological validation in BRAFV600E-mutated cancer cells evidenced the ability of 3 to penetrate inside the cells, specifically binding to its elective target BRAFV600E with high affinity, and inhibiting MEK phosphorylation and cell growth with a potency comparable to that of native Vem 1. Taken together, these data highlight Vem-L-Cy5 3 as a useful tool to probe BRAFV600E mutation in cancer cells, and suitable to acquire precious insights for future developments of more informed BRAF inhibitors-centered therapeutic strategies.