Post-acute sequelae of SARS-CoV-2 Delta variant infection: a report of three cases in a single family

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that has resulted in global pandemic and crisis in health care system. Several studies have focused only on hospitalized patients with 30 to 90 days after one cycle of illness but post-acute sequelae of COVID-19 existing even after a year remains unclear. Moreover, long-term sequelae in outpatients have not been documented and henceforth myriad clinical sequelae in long haulers continue to evolve. In this study, we report three cases represents a single family presenting several post-acute sequelae one after the other extending beyond one year of recovery. To our knowledge such a case series has not been reported in earlier studies. Herein, we present the sequelae in various organs namely neuropsychiatric (tinnitus, anxiety, depression, insomnia, and posttraumatic stress disorder, cognitive decline), cardiovascular (tachycardia, bradycardia), gastrointestinal (appendicitis) and Dermatologic (erythematous rash and acne) besides ophthalmic manifestations (conjunctivitis and dry eyes) in Long-COVID-19 and recommend management strategies.

Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7.

New variants of SARS-CoV-2 are being reported worldwide. The World Health Organization has reported Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2) and Omicron (B.1.1.529) as the variants of concern. There are speculations that the variants might evade the host immune responses induced by currently available vaccines and develop resistance to drugs under consideration. The first step of viral infection in COVID-19 occurs through the interaction of the spike protein's receptor-binding domain (RBD) with the peptidase domain of the human ACE-2 (hACE-2) receptor. This study aims to get a molecular-level understanding of the mechanism behind the increased infection rate in the alpha variant. We have computationally studied the spike protein interaction in both the wild-type and B.1.1.7 variant with the hACE-2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The binding free energy difference shows that the mutant variant of the spike protein has increased binding affinity for the hACE-2 receptor (i.e. ΔG(N501Y,A570D) is in the range -7.2 to -7.6 kcal mol-1) and the results were validated using Density functional theory. We demonstrate that with the use of state-of-the-art computational approaches, we can, in advance, predict the virulent nature of variants of SARS-CoV-2 and alert the world healthcare system.

In silico Screening of Natural Phytocompounds Towards Identification of Potential Lead Compounds to Treat COVID-19.

COVID-19 is one of the members of the coronavirus family that can easily assail humans. As of now, 10 million people are infected and above two million people have died from COVID-19 globally. Over the past year, several researchers have made essential advances in discovering potential drugs. Up to now, no efficient drugs are available on the market. The present study aims to identify the potent phytocompounds from different medicinal plants (Zingiber officinale, Cuminum cyminum, Piper nigrum, Curcuma longa, and Allium sativum). In total, 227 phytocompounds were identified and screened against the proteins S-ACE2 and M pro through structure-based virtual screening approaches. Based on the binding affinity score, 30 active phytocompounds were selected. Amongst, the binding affinity for beta-sitosterol and beta-elemene against S-ACE2 showed -12.0 and -10.9 kcal/mol, respectively. Meanwhile, the binding affinity for beta-sitosterol and beta-chlorogenin against M pro was found to be -9.7 and -8.4 kcal/mol, respectively. Further, the selected compounds proceeded with molecular dynamics simulation, prime MM-GBSA analysis, and ADME/T property checks to understand the stability, interaction, conformational changes, binding free energy, and pharmaceutical relevant parameters. Moreover, the hotspot residues such as Lys31 and Lys353 for S-ACE2 and catalytic dyad His41 and Cys145 for M pro were actively involved in the inhibition of viral entry. From the in silico analyses, we anticipate that this work could be valuable to ongoing novel drug discovery with potential treatment for COVID-19.

In silico evaluation of isatin-based derivatives with RNA-dependent RNA polymerase of the novel coronavirus SARS-CoV-2.

Isatin (1H-indole-2,3-dione)-containing compounds have been shown to possess several remarkable biological activities. We had previously explored a few isatin-based imidazole derivatives for their predicted dual activity against both inflammation and cancer. We explored 47 different isatin-based derivatives (IBDs) for other potential biological activities using in silico tools and found them to possess anti-viral activity. Using AutoDock tools, the binding site, binding energy, inhibitory constant/Ki and receptor-ligand interactions for each of the compounds were analyzed against SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). The partition coefficient (logP) values were predicted using MedChem Designer tool. Based on the best Ki, binding energy and the ideal range of logP (between 1.0 and 3.0), 10 out of total 47 compounds were deemed to be prospective RdRp inhibitors. Some of these compounds gave better Ki, binding energy and logP values when compared to standard RdRp inhibitors, such as remdesivir (REM) (Ki = 15.61 µM, logP = 2.2; binding energy = -6.95), a clinically approved RdRp inhibitor and nine other RdRp inhibitors. The results showed that the 10 selected IBDs could be further explored. Molecular dynamics simulations (MDSs) showed that the selected RdRp-IBD complexes were highly stable compared to the native RdRp and RdRp-REM complex during 100 ns time periods. DFT studies were performed for the compounds 16a, 24a, 28a, 38a and 40a, to evaluate the charge transfer mechanism for the interactions between the IBDs and the RdRp residues. Among these, ADME profiling revealed that 28a is a possible lead compound which can be explored further for anti-RdRp activity in vitro. Communicated by Ramaswamy H. Sarma.

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2 (preprint)

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of RdRp from the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, we predict that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds nucleoside triphosphates at its proposed active site. Additionally, using molecular docking we have predicted the binding of three widely used kinase inhibitors and five well characterized anti-microbial compounds at the NiRAN domain active site along with their drug-likeliness as well as DFT properties. For the first time ever, using basic biochemical tools, this study shows the presence of a kinase like activity exhibited by the SARS-CoV-2 RdRp. Interestingly, the proposed kinase inhibitors and a few of the predicted nucleotidyl transferase inhibitors significantly inhibited the aforementioned enzymatic activity. In line with the current global COVID-19 pandemic urgency and the emergence of newer strains with significantly higher infectivity, this study provides a new anti-SARS-CoV-2 drug target and potential lead compounds for drug repurposing against SARS-CoV-2.

Searching for target-specific and multi-targeting organics for Covid-19 in the Drugbank database with a double scoring approach (preprint)

The current outbreak of Covid-19 infection due to SARS-CoV-2, a virus from the coronavirus family, has become a major threat to human healthcare. The virus has already infected more than 5 M people and the number of deaths reported has reached more than 330 K which may be attributed to lack of medicine. The traditional drug discovery approach involves many years of rigorous research and development and demands for a huge investment which cannot be adopted for the ongoing pandemic infection. Rather we need a swift and cost-effective approach to inhibit and control the viral infection. With the help of computational screening approaches and by choosing appropriate chemical space, it is possible to identify lead drug-like compounds for Covid-19. In this study, we have used the Drugbank database to screen compounds against the most important viral targets namely 3C-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp) and the spike (S) protein. These targets play a major role in the replication/transcription and host cell recognition, therefore, are vital for the viral reproduction and spread of infection. As the structure based computational screening approaches are more reliable, we used the crystal structures for 3C-like main protease and spike protein. For the remaining targets, we used the structures based on homology modeling. Further, we employed two scoring methods based on binding free energies implemented in AutoDock Vina and molecular mechanics - Generalized Born surface area approach. Based on these results, we propose drug cocktails active against the three viral targets namely 3CL-pro, PLpro and RdRp. Interestingly, one of the identified compounds in this study i.e. Baloxavir marboxil has been under clinical trial for the treatment of Covid-19 infection. In addition, we identified a few compounds such as phthalocyanine, Tadalafil, Lonafarnib, Nilotinib, Dihydroergotamine, R-428 which can bind to all three targets simultaneously and can serve as multi-targeting drugs. Our study also included calculation of binding energies for various compounds currently under drug trials. Among these compounds, it is found that Remdesivir binds to targets, 3CLpro and RdRp with high binding affinity. Moreover, Baricitinib and Umifenovir were found to have superior target-specific binding while Darunavir is found to be a potential multi-targeting drug. As far as we know this is the first study where the compounds from the Drug-bank database are screened against four vital targets of SARS-CoV-2 and illustrates that the computational screening using a double scoring approach can yield potential drug-like compounds against Covid-19 infection.