The infection by the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes major public health concern and economic burden. Although clinically approved drugs have been repurposed to treat individuals with 2019 Coronavirus disease (COVID-19), the lack of safety studies and limited efficiency as well jeopardize clinical benefits. Daclatasvir and sofosbuvir (SFV) are clinically approved direct-acting antivirals (DAA) against hepatitis C virus (HCV), with satisfactory safety profile. In the HCV replicative cycle, daclatasvir and SFV target the viral enzymes NS5A and NS5B, respectively. NS5A is endowed with pleotropic activities, which overlap with several proteins from SARS-CoV-2. HCV NS5B and SARS-CoV-2 nsp12 are RNA polymerases that share homology in the nucleotide uptake channel. These characteristics of the HCV and SARS-CoV-2 motivated us to further study the activity of daclatasvir and SFV against the new coronavirus. Daclatasvir consistently inhibited the production of infectious SARS-CoV-2 virus particles in Vero cells, in the hepatoma cell line HuH-7 and in type II pneumocytes (Calu-3), with potencies of 0.8, 0.6 and 1.1 μM, respectively. Daclatasvir targeted early events during SARS-CoV-2 replication cycle and prevented the induction of IL-6 and TNF-α, inflammatory mediators associated with the cytokine storm typical of SARS-CoV-2 infection. Sofosbuvir, although inactive in Vero cells, displayed EC50 values of 6.2 and 9.5 μM in HuH-7 and Calu-3 cells, respectively. Our data point to additional antiviral candidates, in especial daclatasvir, among drugs overlooked for COVID-19, that could immediately enter clinical trials.

Background Current approaches of drug repurposing against COVID-19 have not proven overwhelmingly successful and the SARS-CoV-2 pandemic continues to cause major global mortality. SARS-CoV-2 nsp12, its RNA polymerase, shares homology in the nucleotide uptake channel with the HCV orthologue enzyme NS5B. Besides, HCV enzyme NS5A has pleiotropic activities, such as RNA binding, that are shared with various SARS-CoV-2 proteins. Thus, anti-HCV NS5B and NS5A inhibitors, like sofosbuvir and daclatasvir, respectively, could be endowed with anti-SARS-CoV-2 activity. Methods SARS-CoV-2-infected Vero cells, HuH-7 cells, Calu-3 cells, neural stem cells and monocytes were used to investigate the effects of daclatasvir and sofosbuvir. In silico and cell-free based assays were performed with SARS-CoV-2 RNA and nsp12 to better comprehend the mechanism of inhibition of the investigated compounds. A physiologically based pharmacokinetic model was generated to estimate daclatasvir’s dose and schedule to maximize the probability of success for COVID-19. Results Daclatasvir inhibited SARS-CoV-2 replication in Vero, HuH-7 and Calu-3 cells, with potencies of 0.8, 0.6 and 1.1 μM, respectively. Although less potent than daclatasvir, sofosbuvir alone and combined with daclatasvir inhibited replication in Calu-3 cells. Sofosbuvir and daclatasvir prevented virus-induced neuronal apoptosis and release of cytokine storm-related inflammatory mediators, respectively. Sofosbuvir inhibited RNA synthesis by chain termination and daclatasvir targeted the folding of secondary RNA structures in the SARS-CoV-2 genome. Concentrations required for partial daclatasvir in vitro activity are achieved in plasma at Cmax after administration of the approved dose to humans. Conclusions Daclatasvir, alone or in combination with sofosbuvir, at higher doses than used against HCV, may be further fostered as an anti-COVID-19 therapy.

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Glycoconjugates play a central role in several cellular processes, and alteration in their composition is associated with numerous human pathologies. Substrates for cellular glycosylation are synthesized in the hexosamine biosynthetic pathway, which is controlled by the glutamine:fructose-6-phosphate amidotransfera-se (GFAT). Human isoform 2 GFAT (hGFAT2) has been implicated in diabetes and cancer; however, there is no information about structural and enzymatic properties of this enzyme. Here, we report a successful expression and purification of a catalytically active recombinant hGFAT2 (rhGFAT2) in Escherichia coli cells fused or not to a HisTag at the C-terminal end. Our enzyme kinetics data suggest that hGFAT2 does not follow the expected ordered bi–bi mechanism, and performs the glucosamine-6-phosphate synthesis much more slowly than previously reported for other GFATs. In addition, hGFAT2 is able to isomerize fructose-6-phosphate into glucose-6-phosphate even in the presence of equimolar amounts of glutamine, which results in unproductive glutamine hydrolysis. Structural analysis of a three-dimensional model of rhGFAT2, corroborated by circular dichroism data, indicated the presence of a partially structured loop in the glutaminase domain, whose sequence is present in eukaryotic enzymes but absent in the E. coli homolog. Molecular dynamics simulations suggest that this loop is the most flexible portion of the protein and plays a key role on conformational states of hGFAT2. Thus, our study provides the first comprehensive set of data on the structure, kinetics, and mechanics of hGFAT2, which will certainly contribute to further studies on the (patho)physiology of hGFAT2.

The folding process defines three-dimensional protein structures from their amino acid chains. A protein's structure determines its activity and properties; thus knowing such conformation on an atomic level is essential for both basic and applied studies of protein function and dynamics. However, the acquisition of such structures by experimental methods is slow and expensive, and current computational methods mostly depend on previously known structures to determine new ones. Here we present a new software called GSAFold that applies the generalized simulated annealing (GSA) algorithm on ab initio protein structure prediction. The GSA is a stochastic search algorithm employed in energy minimization and used in global optimization problems, especially those that depend on long-range interactions, such as gravity models and conformation optimization of small molecules. This new implementation applies, for the first time in ab initio protein structure prediction, an analytical inverse for the Visitation function of GSA. It also employs the broadly used NAMD Molecular Dynamics package to carry out energy calculations, allowing the user to select different force fields and parameterizations. Moreover, the software also allows the execution of several simulations simultaneously. Applications that depend on protein structures include rational drug design and structure-based protein function prediction. Applying GSAFold in a test peptide, it was possible to predict the structure of mastoparan-X to a root mean square deviation of 3.00 Å.

Since the middle 70s, the main molecular docking problem consists in limitations to treat adequately the degrees of freedom of protein (or a receptor) due to the energy landscape roughness and the high computational cost. Until recently, only few algorithms considering flexible simultaneously both ligand and receptor at low computational cost were developed. As a recent proposed Statistical Mechanics, generalized simulated annealing (GSA) has been employed at diverse works concerning global optimization problems. In this work, we used this method exploring the molecular docking problem taking into account the FGF-2 and heparin complex. Since the requirements of an efficient docking algorithm are accuracy and velocity, we tested the influence of GSA parameters q A (new configuration acceptance index), q V (energy surface visiting index), and q T (temperature decreasing control) on the performance of GSADOCK program. Our simulations showed that as temperature parameter q T increases, q A parameter follows this behavior in the interval ranging from 1.1 to 2.3. We found that the GSA parameters have the best performance for the q A values ranging from 1.1 to 1.3, q V values from 1.3 to 1.5, and q T values from 1.1 to 1.7. Most of good q V values were equal or next the good q T values. Finally, the implemented algorithm is trustworthy and can be employed as a tool of molecular modeling methods.

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