Drug repositioning against COVID-19: a first line treatment.

COVID-19 disease caused by the SARS-CoV-2 virus has shaken our health and wealth foundations. Although COVID-19 vaccines will become available allowing for attenuation of disease progression rates, distribution of vaccines can create other challenges and delays. Hence repurposed drugs against SARS-CoV-2 can be an attractive parallel strategy that can be integrated into routine clinical practice even in poorly-resourced countries. The present study was designed using knowledge of viral pathogenesis and pharmacodynamics of broad-spectrum antiviral agents (BSAAs). We carried out the virtual screening of BSAAs against the SARS-CoV-2 spike glycoprotein, RNA dependent RNA polymerase (RdRp), the main protease (Mpro) and the helicase enzyme of SARS-CoV-2. Imatinib (a tyrosine kinase inhibitor), Suramin (an anti-parasitic), Glycyrrhizin (an anti-inflammatory) and Bromocriptine (a dopamine agonist) showed higher binding affinity to multiple targets. Further through molecular dynamics simulation, critical conformational changes in the target protein molecules were revealed upon drug binding which illustrates the favorable binding conformations of antiviral drugs against SARS-CoV-2 target proteins. The resulting drugs from the present study in combination and in cocktails from the arsenal of existing drugs could reduce the translational distance and could offer substantial clinical benefit to decrease the burden of COVID-19 illness. This also creates a roadmap for subsequent viral diseases that emerge.Communicated by Ramaswamy H. Sarma.

Genomic Characterization of SARS-CoV2 from Peshawar Pakistan Using Next-Generation Sequencing.

This study aimed to characterize the whole genome of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) isolated from an oropharyngeal swab specimen of a Pashtun Pakistani patient using next-generation sequencing. Upon comparing the SARS-CoV2 genome to the reference genome, a total of 10 genetic variants were identified. Among the 10 genetic variants, 1 missense mutation (c.1139A > G, p.Lys292Glu) in the Open Reading Frame 1ab (ORF1ab) positioned at 112 in the non-structural protein 2 (NSP2) was found to be unique. Phylogenetic analysis (n = 84) revealed that the current SARS-CoV2 genome was closely clustered with 8 Pakistani strains belonging to Punjab, Federal Capital, Azad Jammu and Kashmir (AJK), and Khyber Pakhtunkhwa (KP). In addition, the current SARS-CoV2 genome was very similar to the genome of SARS-CoV2 reported from Guam, Taiwan, India, the USA, and France. Overall, this study reports a slight mismatch in the SARS-CoV2 genome, indicating the presence of a single unique missense mutation. However, phylogenetic analysis revealed that the current SARS-CoV2 genome was closely clustered with 8 other Pakistani strains.

Viroinformatics approach to explore the inhibitory mechanism of existing drugs repurposed to fight against COVID-19.

The rapid breakout of the coronavirus disease of 2019 (COVID-19) has been declared pandemic with serious global concern due to high morbidity and mortality. As we enter the phase beyond limitations there is an urgent need for explicit treatment against COVID-19. To face this immediate global challenge, drug development from scratch is a lengthy process and unrealistic to conquer this battle. Drug repurposing is an emerging and practical approach where existing drugs, safe for humans, are redeployed to fight this harder to treat disease. A number of multi clinical studies have repurposed combined cocktail (remdesivir + chloroquine and favipiravir + chloroquine) to be effective against COVID-19. However, the exact mechanistic aspect has not yet been revealed. In the present study, we have tried to decipher the mechanistic aspects of existing medicines at the viral entry and replication stage via the structural viroinformatics approach. Here we implied the molecular docking and dynamic simulations with emphasis on the unique structural properties of host receptor angiotensin-converting enzyme 2 (ACE2), SARS-CoV2 spike protein and RNA dependent RNA polymerase enzyme (RdRp) of the SARS-CoV2. Deep structural analysis of target molecules exposed key binding residues and structural twists involved in binding with important pharmacophore features of existing drugs [(7-chloro-N-[5-(diethylamino)pentan-2-yl]quinolin-4-amine (chloroquine),N-[[4-(4-methylpiperazin-1-yl)phenyl]methyl]-1,2-oxazole-5-carboxamide N-[[4-(4-methylpiperazin-1-yl)phenyl]methyl]-1,2-oxazole-5-carboxamide) (SSAA09E2), 2-ethylbutyl (2S)-2-{[(S)-{[(2R,3S,4R,5R)-5-{4-aminopyrrolo[2,1-f][1,2,4]triazin-7-yl}-5-cyano-3 (remdesivir) and 6-Fluor-3-oxo-3,4-dihydro-2-pyrazincarboxamid (favipiravir)]. It is evident from this structural informatics study that combo of chloroquine + SSAA09E2 with remdesivir or favipiravir could significantly restrain the virus at the entry and replication stage. Thus, drug repurposition is an attractive approach with reduced time and cost to treat COVID-19, we don't have enough time as the whole world is lockdown and we are in urgent need of an obvious therapeutics' measures.

Drug designing against NSP15 of SARS-COV2 via high throughput computational screening and structural dynamics approach.

The rapid outbreak of the COVID-19 also known as SARS-CoV2 has been declared pandemic with serious global concern. As there is no effective therapeutic against COVID-19, there is an urgent need for explicit treatment against it. The focused objective of the current study is to propose promising drug candidates against the newly identified potential therapeutic target (endonuclease, NSP15) of SARS-CoV2. NSP15 is an attractive druggable target due to its critical role in SARS-CoV2 replication and virulence in addition to interference with the host immune system. Here in the present study, we integrated the high throughput computational screening and dynamic simulation approach to identify the most promising candidate lead compound against NSP15.5-fluoro-2-oxo-1H-pyrazine-3-carboxamide (favipiravir), (3R,4R, 5R)-3,4-Bis(benzyloxy)-5-((benzyloxy) methyl) dihydrofuran-2(3H)-one) remedesivir, 1,3-thiazol-5-ylmethyl N-[(2S,3S, 5S)-3-hydroxy-5-[[(2 S)-3-methyl-2-[[methyl-[(2-propan-2-yl-1,3-thiazol-4-yl)methyl]carbamoyl]amino]butanoyl]amino]-1,6-diphenylhexan-2-yl]carbamate (ritonavir), ethyl (3R,4R, 5S)-4-acetamido-5-amino-3-pentan-3-yloxycyclohexene-1-carboxylate (oseltamivir), and (2 S)-N-[(2S,4S, 5S)-5-[[2-(2,6-dimethylphenoxy)acetyl]amino]-4-hydroxy-1,6-diphenylhexan-2-yl]-3-methyl-2-(2-oxo-1,3-diazinan-1-yl)butanamide (lopinavir) were chosen as a training set to generate the pharmacophore model. A dataset of ~140,000 compounds library was screened against the designed pharmacophore model and 10 unique compounds were selected that passed successfully through geometry constraints, Lipinski Rule of 5, and ADME/Tox filters along with a strong binding affinity for NSP15 binding cavity. The best fit compound was selected for dynamic simulation to have detailed structural features critical for binding with the NSP15 protein. Given our detailed integrative computational analysis, a Small molecule (3,3-Dimethyl-N-[4-(1-piperidinylcarbonyl) phenyl] butanamide) with drug-like properties and high binding affinity with the NSP15 is proposed as a most promising potential drug against COVID-19. The current computational integrative approach may complement high-throughput screening and the shortlisted small molecule may contribute to selective targeting of NSP15 to stop the replication of SARS-CoV2.