Inhibitory effects of 190 compounds against SARS-CoV-2 Mpr o protein: Molecular docking interactions.

COVID-19 has caused many deaths since the first outbreak in 2019. The burden on healthcare systems around the world has been reduced by the success of vaccines. However, population adherence and the occurrence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are still challenging tasks to be affronted. In addition, the newly approved drug presents some limitations in terms of side effects and drug interference, highlighting the importance of searching for new antiviral agents against SARS-CoV-2. The SARS-CoV-2 main protease (Mpr o ) represents a versatile target to search for new drug candidates due to its essential role in proteolytic activities responsible for the virus replication. In this work, a series of 190 compounds, composed of 27 natural ones and 163 synthetic compounds, were screened in vitro for their inhibitory effects against SARS-CoV-2 Mpro . Twenty-five compounds inhibited Mpro with inhibitory constant values (Ki ) between 23.2 and 241 µM. Among them, a thiosemicarbazone derivative was the most active compound. Molecular docking studies using Protein Data Bank ID 5RG1, 5RG2, and 5RG3 crystal structures of Mpro revealed important interactions identified as hydrophobic, hydrogen bonding and steric interactions with amino acid residues in the active site cavity. Overall, our findings indicate the described thiosemicarbazones as good candidates to be further explored to develop antiviral leads against SARS-CoV-2. Moreover, the studies showed the importance of careful evaluation of test results to detect and exclude false-positive findings.

Studies of Cytotoxicity Effects, SARS-CoV-2 Main Protease Inhibition, and in Silico Interactions of Synthetic Chalcones.

SARS-CoV-2 main protease (Mpro ) plays an essential role in proteolysis cleavage that promotes coronavirus replication. Thus, attenuating the activity of this enzyme represents a strategy to develop antiviral agents. We report inhibitory effects against Mpro of 40 synthetic chalcones, and cytotoxicity activities, hemolysis, and in silico interactions of active compounds. Seven of them bearing a (E)-3-(furan-2-yl)-1-arylprop-2-en-1-one skeleton (10, 28, and 35-39) showed enzyme inhibition with IC50 ranging from 13.76 and 36.13 µM. Except for 35 and 36, other active compounds were not cytotoxic up to 150 µM against THP-1 and Vero cell lines. Compounds 10, and 35-39 showed no hemolysis while 28 was weakly hemotoxic at 150 µM. Moreover, molecular docking showed interactions between compound 10 and Mpro (PDBID 5RG2 and 5RG3) with proximity to cys145 and His41, suggesting a covalent binding. Products of the reaction between chalcones and cyclohexanethiol indicated that this binding could be a Michael addition type.

In Silico Drug Repurposing for Anti-Inflammatory Therapy: Virtual Search for Dual Inhibitors of Caspase-1 and TNF-Alpha.

Inflammation involves a complex biological response of the body tissues to damaging stimuli. When dysregulated, inflammation led by biomolecular mediators such as caspase-1 and tumor necrosis factor-alpha (TNF-alpha) can play a detrimental role in the progression of different medical conditions such as cancer, neurological disorders, autoimmune diseases, and cytokine storms caused by viral infections such as COVID-19. Computational approaches can accelerate the search for dual-target drugs able to simultaneously inhibit the aforementioned proteins, enabling the discovery of wide-spectrum anti-inflammatory agents. This work reports the first multicondition model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mtc-QSAR-MLP) for the virtual screening of agency-regulated chemicals as versatile anti-inflammatory therapeutics. The mtc-QSAR-MLP model displayed accuracy higher than 88%, and was interpreted from a physicochemical and structural point of view. When using the mtc-QSAR-MLP model as a virtual screening tool, we could identify several agency-regulated chemicals as dual inhibitors of caspase-1 and TNF-alpha, and the experimental information later retrieved from the scientific literature converged with our computational results. This study supports the capabilities of our mtc-QSAR-MLP model in anti-inflammatory therapy with direct applications to current health issues such as the COVID-19 pandemic.

Indirect-Acting Pan-Antivirals vs. Respiratory Viruses: A Fresh Perspective on Computational Multi-Target Drug Discovery.

Respiratory viruses continue to afflict mankind. Among them, pathogens such as coronaviruses [including the current pandemic agent known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] and the one causing influenza A (IAV) are highly contagious and deadly. These can evade the immune system defenses while causing a hyperinflammatory response that can damage different tissues/organs. Simultaneously targeting several immunomodulatory proteins is a plausible antiviral strategy since it could lead to the discovery of indirect-acting pan-antiviral (IAPA) agents for the treatment of diseases caused by respiratory viruses. In this context, computational approaches, which are an essential part of the modern drug discovery campaigns, could accelerate the identification of multi-target immunomodulators. This perspective discusses the usefulness of computational multi-target drug discovery for the virtual screening (drug repurposing) of IAPA agents capable of boosting the immune system through the activation of the toll-like receptor 7 (TLR7) and/or the stimulator of interferon genes (STING) while inhibiting key inflammation-related proteins such as caspase-1 and tumor necrosis factor-alpha (TNF-α).

A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers.

The main-protease (Mpro) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (MCoV2pro) with 12 mutations compared to SARS-CoV (MCoV1pro). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications. We use metadynamics simulations and a sort of computational analysis to probe the dynamic, pharmacophoric and catalytic environment differences between the monomers of both enzymes. So, we verify how much intrinsic distinctions are preserved in the functional dimer of MCoV2pro, as well as its implications for ligand accessibility and optimized drug screening. We find a significantly higher accessibility to open binding conformers in the MCoV2pro monomer compared to MCoV1pro. A higher hydration propensity for the MCoV2pro S2 loop with the A46S substitution seems to exercise a key role. Quantum calculations suggest that the wider conformations for MCoV2pro are less catalytically active in the monomer. However, the statistics for contacts involving the N-finger suggest higher maintenance of this activity at the dimer. Docking analyses suggest that the ability to vary the active site width can be important to improve the access of the ligand to the active site in different ways. So, we carry out a multiconformational virtual screening with different ligand bases. The results point to the importance of taking into account the protein conformational multiplicity for new promissors anti MCoV2pro ligands. We hope these results will be useful in prospecting, repurposing and/or designing new anti SARS-CoV-2 drugs.Communicated by Ramaswamy H. Sarma.