A novel multi-omics-based identification of symptoms, comorbid conditions, and possible long-term complications in COVID-19 (preprint)

Till date the comprehensive clinical pictures, comorbid conditions, and long-term complications of COVID-19 are not known. Recently using a multi-omics-based strategy, we have predicted the drugs for COVID-19 management with [~]70% accuracy. Here, using a similar multi-omics-based bioinformatics approach and three-ways of analysis, we identified the symptoms, comorbid conditions, and short, mid and possible long-term complications of COVID-19 with [~]90% precision. In our analysis (i) we identified 27 parent, 170 child, and 403 specific conditions associated with COVID-19. (ii) Among the specific conditions, 36 are viral and 53 short-term, 62 short to mid to long-term, 194 mid to long-term, and 57 are congenital conditions. (iii) At a cut off "count of occurrence" of 4, we found [~] 90% of the enriched conditions are associated with COVID-19. (iv) Except the dry cough and loss of taste, all other COVID-19 associated mild and severe symptoms are enriched. (v) Cardiovascular, pulmonary, metabolic, musculoskeletal, neuropsychiatric, kidney, liver, and immune system disorders are found as top comorbid conditions. (vi) Specific diseases such as myocardial infarction, hypertension, COPD, lung injury, diabetes, cirrhosis, mood disorders, dementia, macular degeneration, chronic kidney disease, lupus, arthritis etc. along with several other diseases are also enriched as top candidates. (vii) Interestingly, many cancers and congenital disorders associated with COVID-19 severity are also identified. (viii) Arthritis, dermatomyositis, glioma, diabetes, psychiatric disorder, cardiovascular diseases having bidirectional relationship with COVID-19 are also found as top ranked conditions. Based on the accuracy ([~]90%) of this analysis, long presence of SARS-CoV-2 RNA in human, and our previously proposed "genetic remittance" assumption, we hypothesize that all the identified comorbid conditions including the short-long-mid and mid-long non-communicable diseases (NCDs) could also be long-term consequences in COVID-19 survivors and warrants long-term observational studies.

Potential Chimeric Peptides to Block the SARS-CoV-2 Spike RBD (preprint)

Background: There are no known medicines or vaccines to control the COVID-19 pandemic caused by SARS-CoV-2 (nCoV). Antiviral peptides are superior to conventional drugs and may also be effective against COVID-19. Hence, we investigated the SARS-CoV-2 Spike RBD (nCoV-RBD) that interacts with hACE2 for viral attachment and entry. Methods: Three strategies and bioinformatics approaches were employed to design potential nCoV-RBD - hACE2 interaction-blocking peptides that may restrict viral attachment and entry. Firstly, the key residues interacting with nCoV-RBD - hACE2 are identified and hACE2 sequence based peptides are designed. Second, peptides from five antibacterial peptide databases that block nCoV-RBD are identified; finally, a chimeric peptide design approach is used to design peptides that can bind to key nCoV-RBD residues. The final peptides are selected based on their physiochemical properties, numbers and positions of key residues binding, binding energy, and antiviral properties. Results: We found (i) three amino acid stretches in hACE2 interact with nCoV-RBD; (ii) effective peptides must bind to three key positions of nCoV-RBD: Gly485/Phe486/Asn487, Gln493, and Gln498/Thr500/Asn501; (iii) Phe486, Gln493, and Asn501 are critical residues; (iv) AC20 and AC23 derived from hACE2 may block two key critical positions; (iv) DBP6 identified from databases can block the three sites of the nCoV-RBD interacting with one critical position Gln498; (v) seven chimeric peptides were considered promising among which cnCoVP-3, cnCoVP-4, and cnCoVP-7 are the top three; and (vi) cnCoVP-4 meets all the criteria and is the best peptide. Conclusion: All the ten peptides need experimental validation for their therapeutic efficacy.

Computational Screening for Potential Drug Candidates Against SARS-CoV-2 Main Protease (preprint)

Background: SARS-CoV-2 that are the causal agent of a current pandemic are enveloped, positive-sense, single-stranded RNA viruses of the Coronaviridae family. Proteases of SARS-CoV-2 are necessary for viral replication, structural assembly and pathogenicity. The ~33.8KDa Mpro protease of SARS-CoV-2 is a non-human homologue and highly conserved among several coronaviruses indicating Mpro could be a potential drug target for Coronaviruses.Methods: Here we performed computational ligand screening of four pharmacophores (OEW, Remdesivir, Hydroxycholoquine and N3) that are presumed to have positive effects against SARS-CoV-2 Mpro protease (6LU7) and also screened 50,000 molecules from the ZINC Database dataset against this protease target.Results: We found 40 pharmacophore-like structures of natural compounds from diverse chemical classes that exhibited better affinity of docking as compared to the known ligands. The 10 best selected ligands namely, ZINC1845382, ZINC1875405, ZINC2092396, ZINC2104424, ZINC44018332, ZINC2101723, ZINC2094526, ZINC2094304, ZINC2104482, ZINC3984030, and ZINC1531664, are mainly classified as β-carboline, Alkaloids and Polyflavonoids, and all of them displayed interactions with dyad CYS145 and HIS41 from the protease pocket in a similar way as with other known ligands.Conclusion: Our results suggest that these 10 molecules could be effective against SARS-CoV-2 protease and may be tested in vitro and in vivo to develop novel drugs against this virus.

Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil (preprint)

Background. We investigated a likely scenario of COVID-19 spreading in Brazil through the complex airport network of the country, for the 90 days after the first national occurrence of the disease. After the confirmation of the first imported cases, the lack of a proper airport entrance control resulted in the infection spreading in a manner directly proportional to the amount of flights reaching each city, following first occurrence of the virus coming from abroad. Methodology. We developed a SIR (Susceptible-Infected-Recovered) model divided in a metapopulation structure, where cities with airports were demes connected by the number of flights. Subsequently, we further explored the role of Manaus airport for a rapid entrance of the pandemic into indigenous territories situated in remote places of the Amazon region. Results. The expansion of the SARS-CoV-2 virus between cities was fast, directly proportional to the airport closeness centrality within the Brazilian air transportation network. There was a clear pattern in the expansion of the pandemic, with a stiff exponential expansion of cases for all cities. The more an airport showed closeness centrality, the greater was its vulnerability to SARS-CoV-2. Conclusions. We discussed the weak pandemic control performance of Brazil in comparison with other tropical, developing countries, namely India and Nigeria. Finally, we proposed measures for containing virus spreading taking into consideration the scenario of high poverty.