Lymecycline for COVID-19

<ns4:p><ns4:bold>Background:</ns4:bold> The protein interaction between the viral surface S-glycoprotein and the host angiotensin converting enzyme-2 receptor (ACE2) is key to the virulent nature of SARS-CoV-2. The potential role that effective drug repurposing strategies may have to help stem the impact of future outbreaks has been brought to light in the recent COVID-19 pandemic. This study outlines a comprehensive approach towards <ns4:italic>in-silico</ns4:italic> drug discovery which aims to identify hit agents that can be suitably translated into a clinical setting. <ns4:bold>Methods:</ns4:bold> We use two different computational platforms to analyze the viral S-glycoprotein in its bound conformational state to the ACE2 receptor. We employed a comprehensive screening approach to shortlist compounds capable of binding to the viral target interface and corroborated these findings using both Schrödinger’s Glide and AutoDock Vina. Molecular dynamic simulation studies further verified the stability of the interaction at the viral-host protein interface. <ns4:bold>Results:</ns4:bold> Lymecycline, pentagalloylglucose, polydatin, and hexoprenaline were identified as prime candidates for further studies given the robust and stable nature of their interaction at the viral-host interface and relevance for clinical testing. These agents were shown in a 100-nanosecond simulation trajectory to favorably disrupt key binding interactions at the viral-host interface and may potentially inhibit viral entry into host cells. In all hit molecules it was observed that inhibiting the interaction with the following key viral binding residues: Lys17, Gly496, Tyr 505, and key host residues: His34, Asp38, Lys353, played a critical role toward the inhibition of the viral-host protein interaction. <ns4:bold>Conclusions:</ns4:bold> Our study is unique in its comprehensive approach to identify agents that can bind to the S-glycoprotein-ACE2 interface using multiple computational platforms. Among the hit compounds shortlisted in this study, both lymecycline and hexoprenaline may be considered as candidates for preliminarily clinical studies to assess their therapeutic potential in the management of COVID-19 infections.</ns4:p>

AbstractTo attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.

Abstract Using as a template the crystal structure of the SARS-CoV-2 main protease, we developed a pharmacophore model of functional centers of the protease inhibitor-binding pocket. With this model, we conducted data mining of the conformational database of FDA-approved drugs. This search brought 64 compounds that can be potential inhibitors of the SARS-CoV-2 protease. The conformations of these compounds undergone 3D fingerprint similarity clusterization. Then we conducted docking of possible conformers of these drugs to the binding pocket of the protease. We also conducted the same docking of random compounds. Free energies of the docking interaction for the selected compounds were clearly lower than random compounds. Three of the selected compounds were carfilzomib, cyclosporine A, and azithromycin—the drugs that already are tested for COVID-19 treatment. Among the selected compounds are two HIV protease inhibitors and two hepatitis C protease inhibitors. We recommend testing of the selected compounds for treatment of COVID-19.