Investigating Potential Inhibitory Effect of Uncaria tomentosa (Cat's Claw) against the Main Protease 3CLpro of SARS-CoV-2 by Molecular Modeling.

COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2. Presently, there is no effective treatment for COVID-19. As part of the worldwide efforts to find efficient therapies and preventions, it has been reported the crystalline structure of the SARS-CoV-2 main protease Mpro (also called 3CLpro) bound to a synthetic inhibitor, which represents a major druggable target. The druggability of Mpro could be used for discovering drugs to treat COVID-19. A multilevel computational study was carried out to evaluate the potential antiviral properties of the components of the medicinal herb Uncaria tomentosa (Cat's claw), focusing on the inhibition of Mpro. The in silico approach starts with protein-ligand docking of 26 Cat's claw key components, followed by ligand pathway calculations, molecular dynamics simulations, and MM-GBSA calculation of the free energy of binding for the best docked candidates. The structural bioinformatics approaches led to identification of three bioactive compounds of Uncaria tomentosa (speciophylline, cadambine, and proanthocyanidin B2) with potential therapeutic effects by strong interaction with 3CLpro. Additionally, in silico drug-likeness indices for these components were calculated and showed good predicted therapeutic profiles of these phytochemicals. Our findings suggest the potential effectiveness of Cat's claw as complementary and/or alternative medicine for COVID-19 treatment.

Consensus modes, a robust description of protein collective motions from multiple-minima normal mode analysis--application to the HIV-1 protease.

Protein flexibility is essential for enzymatic function, ligand binding, and protein-protein or protein-nucleic acid interactions. Normal mode analysis has increasingly been shown to be well suited for studying such flexibility, as it can be used to identify favorable structural deformations that correspond to functional motions. However, normal modes are strictly relevant to a single structure, reflecting a particular minimum on a complex energy surface, and are thus susceptible to artifacts. We describe a new theoretical framework for determining "consensus" normal modes from a set of related structures, such as those issuing from a short molecular dynamics simulation. This approach is more robust than standard normal mode analysis, and provides higher collectivity and symmetry properties. In an application to HIV-1 protease, the low-frequency consensus modes describe biologically relevant motions including flap opening and closing that can be used in interpreting structural changes accompanying the binding of widely differing inhibitors.