A simplified drift-diffusion model for pandemic propagation (preprint)

Predicting Pandemic evolution involves complex modeling challenges, often requiring detailed discrete mathematics executed on large volumes of epidemiological data. Differential equations have the advantage of offering smooth, well-behaved solutions that try to capture overall predictive trends and averages. We further simplify one of those equations, the SIR model, by offering quasi-analytical solutions and fitting functions that agree well with the numerics, as well as COVID-19 data across a few countries. The equations provide an elegant way to visualize the evolution, by mapping onto the dynamics of an overdamped classical particle moving in the SIR configuration space, drifting down gradient of a potential whose shape is set by the model and parameters in hand. We discuss potential sources of errors in our analysis and their growth over time, and map those uncertainties into a diffusive jitter that tends to push the particle away from its minimum. The combined physical understanding and analytical expressions offered by such an intuitive drift-diffusion model could be particularly useful in making policy decisions going forward.

Potential anti-tumor immune response mechanisms of SARS-CoV-2 in lymphomas: can the devil be converted into a boon? (preprint)

Recently, two cases of complete remission of classical Hodgkin lymphoma (cHL) and follicular lymphoma (FL) after SARS-CoV-2 infection were reported. However, the precise molecular mechanism of this rare event is yet to be understood. Here, we hypothesize a potential anti-tumor immune response of SARS-CoV-2 and based on computational approach show that (i) SARS-CoV-2 Spike-RBD may bind to extracellular domains of CD15, CD27, CD45, and CD152 receptors of cHL or FL, (ii) upon internalization, SARS-CoV-2 membrane (M) protein and Orf3a may bind to gamma-tubulin complex component 3 (GCP3) at its tubulin gamma-1 chain (TUBG1) binding site, (iii) M protein may also interact with TUBG1 blocking its binding to GCP3, (iv) both M and Orf3a may render the GCP2-GCP3 lateral binding where M possibly interacts with GCP2 at its GCP3 binding site and Orf3a to GCP3 at its GCP2 interacting residues, (v) interactions of M and Orf3a with these gamma-tubulin ring complex components potentially block the initial process of microtubule nucleation, leading to cell cycle arrest and apoptosis, (vi) Spike-RBD may also interact with and block PD-1 signaling similar to pembrolizumab and nivolumab like monoclonal antibodies and may induce B-cell apoptosis and remission, (vii) finally, the TRADD interacting PVQLSY motif of Epstein-Barr virus LMP-1, that is responsible for NF-kB mediated oncogenesis, potentially interacts with SARS-CoV-2 Mpro, nsp7, nsp10, and Spike proteins and may regulate the LMP-1 mediated cell proliferation. Taken together, our results suggest a possible therapeutic potential of SARS-CoV-2 in proliferative disorders.

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.