One microsecond MD simulations of the SARS-CoV-2 main protease and hydroxychloroquine complex reveal the intricate nature of binding.

Currently, several vaccines and antivirals across the globe are in clinical trials. Hydroxychloroquine (HCQ) was reported to inhibit the SARS-CoV-2 virus in antiviral assays. Here, it raises the curiosity about the molecular target of HCQ inside the cell. It may inhibit some of the viral targets, or some other complex mechanisms must be at disposal towards action mechanisms. In some of the viruses, proteases are experimentally reported to be a potential target of HCQ. However, no in-depth investigations are available in the literature yet. Henceforth, we have carried out extensive, one-microsecond long molecular dynamics simulations of the bound complex of hydroxychloroquine with main protease (Mpro) of SARS-CoV-2. Our analysis found that HCQ binds within the catalytic pocket of Mpro and remains stable upto one-third of simulation time but further causes increased fluctuations in simulation parameters. In the end, the HCQ does not possess any pre-formed hydrogen bond, other non-covalent interactions with Mpro, ultimately showing the unsteadiness in binding at catalytic binding pocket and may suggest that HCQ may not inhibit the Mpro. In the future, this study would require experimental validation on enzyme assays against Mpro, and that may be the final say. Communicated by Ramaswamy H. Sarma.

Amyloidogenic proteins in the SARS-CoV and SARS-CoV-2 proteomes.

The phenomenon of protein aggregation is associated with a wide range of human diseases. Our knowledge of the aggregation behaviour of viral proteins, however, is still rather limited. Here, we investigated this behaviour in the SARS-CoV and SARS-CoV-2 proteomes. An initial analysis using a panel of sequence-based predictors suggested the presence of multiple aggregation-prone regions (APRs) in these proteomes and revealed a strong aggregation propensity in some SARS-CoV-2 proteins. We then studied the in vitro aggregation of predicted aggregation-prone SARS-CoV and SARS-CoV-2 proteins and protein regions, including the signal sequence peptide and fusion peptides 1 and 2 of the spike protein, a peptide from the NSP6 protein, and the ORF10 and NSP11 proteins. Our results show that these peptides and proteins can form amyloid aggregates. We used circular dichroism spectroscopy to reveal the presence of ß-sheet rich cores in aggregates and X-ray diffraction and Raman spectroscopy to confirm the formation of amyloid structures. Furthermore, we demonstrated that SARS-CoV-2 NSP11 aggregates are toxic to mammalian cell cultures. These results motivate further studies about the possible role of aggregation of SARS proteins in protein misfolding diseases and other human conditions.

Leveraging AI for advanced analytics to forecast altered tourism industry parameters: A COVID-19 motivated study.

COVID-19 pandemic has given a sudden shock to economy indices worldwide and especially to the tourism sector, which is already very sensitive to such crises as natural calamities, terrorist activities, virus outbreaks and unwanted conditions. The economic implications for a reduction in tourism demand, and the need to analyse post-COVID-19 tourism motivates our research. This study aims to forecast the future trends for foreign tourist arrivals and foreign exchange earnings for India and to formulate a model to predict the future trends based on the COVID-19 parameters, vaccinations and stringency index (Government travelling guidelines). In the study, we have developed artificial intelligence models (random forest, linear regression) using the stacked based ensemble learning method for the development of base models and meta models for the study of COVID-19 and its effect on the tourism industry. The architecture of a stacking model consists of two or more base models, often referred to as level-0 models, and a meta-model that combines the predictions of the base models, and is referred to as a level-1 model (Smyth & Wolpert, 1999). The results show that the projected losses require quick action on developing new practices to sustain and complement the resilience of tourism per se.

SARS-CoV-2 NSP1 C-terminal (residues 131-180) is an intrinsically disordered region in isolation.

The NSP1- C terminal structure in complex with ribosome using cryo-EM is available now, and the N-terminal region structure in isolation is also deciphered in literature. However, as a reductionist approach, the conformation of NSP1- C terminal region (NSP1-CTR; amino acids 131-180) has not been studied in isolation. We found that NSP1-CTR conformation is disordered in an aqueous solution. Further, we examined the conformational propensity towards alpha-helical structure using trifluoroethanol, we observed induction of helical structure conformation using CD spectroscopy. Additionally, in SDS, NSP1-CTR shows a conformational change from disordered to ordered, possibly gaining alpha-helix in part. But in the presence of neutral lipid DOPC, a slight change in conformation is observed, which implies the possible role of hydrophobic interaction and electrostatic interaction on the conformational changes of NSP1. Fluorescence-based studies have shown a blue shift and fluorescence quenching in the presence of SDS, TFE, and lipid vesicles. In agreement with these results, fluorescence lifetime and fluorescence anisotropy decay suggest a change in conformational dynamics. The zeta potential studies further validated that the conformational dynamics are primarily because of hydrophobic interaction. These experimental studies were complemented through Molecular Dynamics (MD) simulations, which have shown a good correlation and testifies our experiments. We believe that the intrinsically disordered nature of the NSP1-CTR will have implications for enhanced molecular recognition feature properties of this IDR, which may add disorder to order transition and disorder-based binding promiscuity with its interacting proteins.

Conformational dynamics of 13 amino acids long NSP11 of SARS-CoV-2 under membrane mimetics and different solvent conditions.

The intrinsically disordered proteins/regions (IDPs/IDPRs) are known to be responsible for multiple cellular processes and are associated with many chronic diseases. In viruses, the existence of a disordered proteome is also proven and is related to its conformational dynamics inside the host. The SARS-CoV-2 has a large proteome, in which, structure and functions of all proteins are not known yet, along with non-structural protein 11 (nsp11). In this study, we have performed extensive experimentation on nsp11. Our results based on the CD spectroscopy gives characteristic disordered spectrum for IDPs. Further, we investigated the conformational behavior of nsp11 in the presence of membrane mimetic environment, α-helix inducer, and natural osmolyte. In the presence of negatively charged and neutral liposomes, nsp11 remains disordered. However, with SDS micelle, it adopted an α-helical conformation, suggesting the helical propensity of nsp11. Finally, we again confirmed the IDP behavior of nsp11 using MD simulations. In future, this conformational dynamic study could help to clarify its functional importance in SARS-CoV-2 infection.

Reprofiling of approved drugs against SARS-CoV-2 main protease: an in-silico study.

Given the COVID-19 pandemic, currently, there are many drugs in clinical trials against this virus. Among the excellent drug targets of SARS-CoV-2 are its proteases (Nsp3 and Nsp5) that plays vital role in polyprotein processing giving rise to functional nonstructural proteins, essential for viral replication and survival. Nsp5 (also known as Mpro) hydrolyzes replicase polyprotein (1ab) at eleven different sites. For targeting Mpro, we have employed drug repurposing approach to identify potential inhibitors of SARS-CoV-2 in a shorter time span. Screening of approved drugs through docking reveals Hyaluronic acid and Acarbose among the top hits which are showing strong interactions with catalytic site residues of Mpro. We have also performed docking of drugs Lopinavir, Ribavirin, and Azithromycin on SARS-CoV-2 Mpro. Further, binding of these compounds (Hyaluronic acid, Acarbose, and Lopinavir) is validated by extensive molecular dynamics simulation of 500 ns where these drugs show stable binding with Mpro. We believe that the high-affinity binding of these compounds will help in designing novel strategies for structure-based drug discovery against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.