Analysis of natural compounds against the activity of SARS-CoV-2 NSP15 protein towards an effective treatment against COVID-19: a theoretical and computational biology approach

Phytocompounds as potential inhibitors of mycobacterial multidrug efflux pump Rv1258c: an in silico approach

The number of infections and deaths caused by multidrug resistant (MDR) tuberculosis is increasing globally. One of the efflux pumps, that makes Mycobacterium tuberculosis resistant to a number of antibiotics and results in unfavourable treatment results is Tap or Rv1258c. In our study, we tried to utilize a rational drug design technique using in silico approach to look for an efficient and secure efflux pump inhibitor (EPI) against Rv1258c. The structure of Rv1258c was built using the homology modeling tool MODELLER 9.24. 210 phytocompounds were used for blind and site-specific ligand docking against the modelled structure of Rv1258c using AutoDock Vina software. The best docked plant compounds were further analysed for druglikeness and toxicity. In addition to having excellent docking scores, two plant compounds-ellagic acid and baicalein-also exhibited highly desirable drug-like qualities. These substances outperform more well-known EPIs like piperine and verapamil in terms of effectiveness. This data shows that these two compounds might be further investigated for their potential as Rv1258c inhibitors.

Inhibition of nonstructural protein 15 of SARS-CoV-2 by golden spice: A computational insight

The quick widespread of the coronavirus and speedy upsurge in the tally of cases demand the fast development of effective drugs. The uridine-directed endoribonuclease activity of nonstructural protein 15 (Nsp15) of the coronavirus is responsible for the invasion of the host immune system. Therefore, developing potential inhibitors against Nsp15 is a promising strategy. In this concern, the in silico approach can play a significant role, as it is fast and cost-effective in comparison to the trial and error approaches of experimental investigations. In this study, six turmeric derivatives (curcuminoids) were chosen for in silico analysis. The molecular interactions, pharmacokinetics, and drug-likeness of all the curcuminoids were measured. Further, the stability of Nsp15-curcuminoids complexes was appraised by employing molecular dynamics (MD) simulations and MM-PBSA approaches. All the molecules were affirmed to have strong interactions and pharmacokinetic profile. The MD simulations data stated that the Nsp15-curcuminoids complexes were stable during simulations. All the curcuminoids showed stable and high binding affinity, and these curcuminoids could be admitted as potential modulators for Nsp15 inhibition.

The Impact of COVID-19 Pandemic on Seafood Safety and Human Health

The coronavirus disease (COVID-19) pandemic caused several negative impacts on global human health and the world's economy. Food and seafood safety and security were among the principal challenges and causes of concern for the food industry and consumers during the spread of this global pandemic. This article focused on the effects of COVID-19 pandemic on potential safety issues with seafood products and their processing methods. Moreover, the potential impacts of coronavirus transmission through seafood on human health were evaluated. The role of authenticity, traceability, and antimicrobials from natural sources to preserve seafood and the possible interaction of functional foods on the human immune system are also discussed. Although seafood is not considered a principal vector of SARS-CoV-2 transmission, the possible infections through contaminated surfaces of such food products cannot be neglected. The positive effects of seafood consumption on possible immunity built up, and COVID-19 are also summarized.

Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2

COVID-19 (Corona Virus Disease of 2019) caused by the novel 'Severe Acute Respiratory Syndrome Coronavirus-2' (SARS-CoV-2) has wreaked havoc on human health and the global economy. As a result, for new medication development, it's critical to investigate possible therapeutic targets against the novel virus. 'Non-structural protein 15' (Nsp15) endonuclease is one of the crucial targets which helps in the replication of virus and virulence in the host immune system. Here, in the current study, we developed the structure-based pharmacophore model based on Nsp15-UMP interactions and virtually screened several databases against the selected model. To validate the screening process, we docked the top hits obtained after secondary filtering (Lipinski's rule of five, ADMET & Topkat) followed by 100 ns molecular dynamics (MD) simulations. Next, to revalidate the MD simulation studies, we have calculated the binding free energy of each complex using the MM-PBSA procedure. The discovered repurposed drugs can aid the rational design of novel inhibitors for Nsp15 of the SARS-CoV-2 enzyme and may be considered for immediate drug development.

Antiviral activities of natural compounds and ionic liquids to inhibit the Mpro of SARS-CoV-2: a computational approach

The recalcitrant spread of the COVID-19 pandemic produced by the novel coronavirus SARS-CoV-2 is one of the most destructive occurrences in history. Despite the availability of several effective vaccinations and their widespread use, this line of immunization often faces questions about its long-term efficacy. Since coronaviruses rapidly change, and multiple SARS-CoV-2 variants have emerged around the world. Therefore, finding a new target-based medication became a priority to prevent and control COVID-19 infections. The main protease (Mpro) is a salient enzyme in coronaviruses that plays a vital role in viral replication, making it a fascinating therapeutic target for SARS-CoV-2. We screened 0.2 million natural products against the Mpro of SARS-CoV-2 using the Universal Natural Product Database (UNPD). As well, we studied the role of ionic liquids (ILs) on the structural stabilization of Mpro. Cholinium-based ILs are biocompatible and used for a variety of biomedical applications. Molecular docking was employed for the initial screening of natural products and ILs against Mpro. To predict the drug-likeness features of lead compounds, we calculated the ADMET properties. We performed MD simulations for the selected complexes based on the docking outcomes. Using MM/PBSA approaches, we conclude that compounds NP-Hit2 (-25.6 kcal mol-1) and NP-Hit3 (-25.3 kcal mol-1) show stronger binding affinity with Mpro. The hotspot residues of Thr25, Leu27, His41, Met49, Cys145, Met165, and Gln189 strongly interacted with the natural compounds. Furthermore, naproxenate, ketoprofenate, and geranate, cholinium-based ILs strongly interact with Mpro and these ILs have antimicrobial properties. Our findings will aid in the development of effective Mpro inhibitors.

Evaluating cepharanthine analogues as natural drugs against SARS-CoV-2

Cepharanthine (CEP) is a natural biscoclaurine alkaloid of plant origin and was recently demonstrated to have anti‐severe acute respiratory syndrome coronavirus 2 (anti‐SARS‐CoV‐2) activity. In this study, we evaluated whether natural analogues of CEP may act as potential anti‐coronavirus disease 2019 drugs. A total of 24 compounds resembling CEP were extracted from the KNApSAcK database, and their binding affinities to target proteins, including the spike protein and main protease of SARS‐CoV‐2, NPC1 and TPC2 in humans, were predicted via molecular docking simulations. Selected analogues were further evaluated by a cell‐based SARS‐CoV‐2 infection assay. In addition, the efficacies of CEP and its analogue tetrandrine were assessed. A comparison of the docking conformations of these compounds suggested that the diphenyl ester moiety of the molecules was a putative pharmacophore of the CEP analogues.

A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19. Although many computational methods to predict protein inhibitors have been developed [ 1– 5], few systematic reviews on these methods have been published. Here, we provide a comprehensive overview of the existing methods to discover potential inhibitors of COVID-19 virus, so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First, we briefly categorize and describe computational approaches by the basic algorithms involved in. Then we review the related biological datasets used in such predictions. Furthermore, we emphatically discuss current knowledge on SARS-CoV-2 inhibitors with the latest findings and development of computational methods in uncovering protein inhibitors against COVID-19.