N-acylbenzimidazoles as selective Acylators of the catalytic cystein of the coronavirus 3CL protease.

The 3CL protease (3CL, M) plays a key role in the replication of the SARS-CoV-2 and was validated as therapeutic target by the development and approval of specific antiviral drugs (nirmatrelvir, ensitrelvir), inhibitors of this protease. Moreover, its high conservation within the coronavirus family renders it an attractive therapeutic target for the development of anti-coronavirus compounds with broad spectrum activity to control COVID-19 and future coronavirus diseases. Here we report on the design, synthesis and structure-activity relationships of a new series of small covalent reversible inhibitors of the SARS-CoV-2 3CL.

Novel dithiocarbamates selectively inhibit 3CL protease of SARS-CoV-2 and other coronaviruses.

Since end of 2019, the global and unprecedented outbreak caused by the coronavirus SARS-CoV-2 led to dramatic numbers of infections and deaths worldwide. SARS-CoV-2 produces two large viral polyproteins which are cleaved by two cysteine proteases encoded by the virus, the 3CL protease (3CL) and the papain-like protease, to generate non-structural proteins essential for the virus life cycle. Both proteases are recognized as promising drug targets for the development of anti-coronavirus chemotherapy.

Tricyclic SpiroLactams Kill Mycobacteria In Vitro and In Vivo by Inhibiting Type II NADH Dehydrogenases.

It is critical that novel classes of antituberculosis drugs are developed to combat the increasing burden of infections by multidrug-resistant strains. To identify such a novel class of antibiotics, a chemical library of unique 3-D bioinspired molecules was explored revealing a promising, mycobacterium specific Tricyclic SpiroLactam (TriSLa) hit. Chemical optimization of the TriSLa scaffold delivered potent analogues with nanomolar activity against replicating and nonreplicating .

A new blind color watermarking based on a psychovisual model.

In this paper, we address the problem of the use of a human visual system (HVS) model to improve watermark invisibility. We propose a new color watermarking algorithm based on the minimization of the perception of color differences. This algorithm is based on a psychovisual model of the dynamics of cone photoreceptors.