The main protease of SARS-CoV-2 is one of the important targets to design and develop antiviral drugs. In this study, we have selected 40 antiviral phytochemicals to find out the best candidates which can act as potent inhibitors against the main protease. Molecular docking is performed using AutoDock Vina and GOLD suite to determine the binding affinities and interactions between the phytochemicals and the main protease. The selected candidates strongly interact with the key Cys145 and His41 residues. To validate the docking interactions, 100 ns molecular dynamics (MD) simulations on the five top-ranked inhibitors including hypericin, cyanidin 3-glucoside, baicalin, glabridin, and α-ketoamide-11r were performed. Principal component analysis (PCA) of potential energy components of MD discloses that baicalin, cyanidin 3-glucoside, and α-ketoamide-11r have structural similarity with the apo-form of the main protease. These findings are also strongly supported by root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent accessible surface area (SASA) investigations. PCA is also used to find out the quantitative structure-activity relationship (QSAR) for pattern recognition of the best ligands. Multiple linear regression (MLR) of QSAR reveals the R² value of 0.842 for the training set and 0.753 for the test set. Our proposed MLR model can predict the favorable binding energy compared with the binding energy detected from molecular docking. ADMET analysis demonstrates that these candidates appear to be safer inhibitors. Our comprehensive computational and statistical analysis show that these selected phytochemicals can be used as potential inhibitors against the SARS-CoV-2. Graphical Abstract

Bridging the mass gap: Viruses and many large biomolecule complexes are in a mass range that is challenging to measure with conventional mass spectrometry methods. Nanomechanical resonators can determine masses of impacting molecules, but separation methods often lose too much of the sample to be efficient. Dominguez-Medina et al. used an aerodynamic lens that improved separation and focusing of nebulized molecules with increasing mass. The mass of both filled and empty viral capsids was determined with an array of 20 nanoresonators. Science , this issue p. 918

Okinawa propolis (OP) and its major ingredients were reported to have anti-cancer effects and lifespan-extending effects on Caenorhabditis elegans through inactivation of the oncogenic kinase, p21-activated kinase 1 (PAK1). Herein, five prenylated flavonoids from OP, nymphaeol-A (NA), nymphaeol-B (NB), nymphaeol-C (NC), isonymphaeol-B (INB), and 3′-geranyl-naringenin (GN), were evaluated for their anti-inflammatory, anti-diabetic, and anti-Alzheimer’s effects using in vitro techniques. They showed significant anti-inflammatory effects through inhibition of albumin denaturation (half maximal inhibitory concentration (IC₅₀) values of 0.26–1.02 µM), nitrite accumulation (IC₅₀ values of 2.4–7.0 µM), and cyclooxygenase-2 (COX-2) activity (IC₅₀ values of 11.74–24.03 µM). They also strongly suppressed in vitro α-glucosidase enzyme activity with IC₅₀ values of 3.77–5.66 µM. However, only INB and NA inhibited acetylcholinesterase significantly compared to the standard drug donepezil, with IC₅₀ values of 7.23 and 7.77 µM, respectively. Molecular docking results indicated that OP compounds have good binding affinity to the α-glucosidase and acetylcholinesterase proteins, making non-bonded interactions with their active residues and surrounding allosteric residues. In addition, none of the compounds violated Lipinski’s rule of five and showed notable toxicity parameters. Density functional theory (DFT)-based global reactivity descriptors demonstrated their high reactive nature along with the kinetic stability. In conclusion, this combined study suggests that OP components might be beneficial in the treatment of inflammation, type 2 diabetes mellitus, and Alzheimer’s disease.

Serine-threonine kinase11 (STK11) is a tumor suppressor gene which plays a key role in regulating cell growth and apoptosis. It is widely known as a multitasking kinase and engaged in cell polarity, cell cycle arrest, chromatin remodeling, energy metabolism, and Wnt signaling. The substitutions of single amino acids in highly conserved regions of the STK11 protein are associated with Peutz–Jeghers syndrome (PJS), which is an autosomal dominant inherited disorder. The abnormal function of the STK11 protein is still not well understood. In this study, we classified disease susceptible single nucleotide polymorphisms (SNPs) in STK11 by using different computational algorithms. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking and molecular dynamics analysis. Our results show that W239R and W308C variants are likely to be highly deleterious mutations found in the catalytic kinase domain, which may destabilize structure and disrupt the activation of the STK11 protein as well as reduce its catalytic efficiency. The W239R mutant is likely to have a greater impact on destabilizing the protein structure compared to the W308C mutant. In conclusion, these mutants can help to further realize the large pool of disease susceptibilities linked with catalytic kinase domain activation of STK11 and assist to develop an effective drug for associated diseases.

SARS-CoV-2 membrane (M) protein performs a variety of critical functions in virus infection cycle. However, the expression and purification of membrane protein structure is difficult despite tremendous progress. In this study, the 3 D structure is modeled followed by intensive validation and molecular dynamics simulation. The lack of suitable homologous templates (>30% sequence identities) leads us to construct the membrane protein models using template-free modeling (de novo or ab initio) approach with Robetta and trRosetta servers. Comparing with other model structures, it is evident that trRosetta (TM-score: 0.64; TM region RMSD: 2 Å) can provide the best model than Robetta (TM-score: 0.61; TM region RMSD: 3.3 Å) and I-TASSER (TM-score: 0.45; TM region RMSD: 6.5 Å). 100 ns molecular dynamics simulations are performed on the model structures by incorporating membrane environment. Moreover, secondary structure elements and principal component analysis (PCA) have also been performed on MD simulation data. Finally, trRosetta model is utilized for interpretation and visualization of interacting residues during protein-protein interactions. The common interacting residues including Phe103, Arg107, Met109, Trp110, Arg131, and Glu135 in the C-terminal domain of M protein are identified in membrane-spike and membrane-nucleocapsid protein complexes. The active site residues are also predicted for potential drug and peptide binding. Overall, this study might be helpful to design drugs and peptides against the modeled membrane protein of SARS-CoV-2 to accelerate further investigation. Communicated by Ramaswamy H. Sarma Graphical Abstract