Structural, molecular hybridization and network based identification of miR-373-3p and miR-520e-3p as regulators of NR4A2 human gene involved in neurodegeneration.

MicroRNAs (miRNAs) are short non-coding RNAs with a 22 nucleotide sequence length and docks to the 3'UTR/5'UTR of the gene to regulate their mRNA translation to play a vital role in neurodegenerative diseases. The Nuclear Receptor gene (NR4A2), a transcription factor, and a steroid-thyroid hormone retinoid receptor is involved in neural development, memory formation, dopaminergic neurotransmission, and cellular protection from inflammatory damage. Therefore, recognizing the miRNAs is essential to efficiently target the 3'UTR/5'UTR of the NR4A2 gene and regulate neurodegeneration. Highly stabilized top miRNA-mRNA hybridized structures, their homologs, and identification of the best structures based on their least free energy were evaluated using in silico techniques. The miR-gene, gene-gene network analysis, miR-disease association, and transcription factor binding sites were also investigated. Results suggest top 166 miRNAs targeting the NR4A2 mRNA, but with a total of 10 miRNAs bindings with 100% seed sequence identity (both at 3' and 5'UTR) at the same position on the NR4A2 mRNA region. The miR-373-3p and miR-520e-3p are considered the best candidate miRNAs hybridizing with high efficiency at both 3' and 5'UTR of NR4A2 mRNA. This could be due to the most significant seed sequence length complementary, supplementary pairing, and absence of non-canonical base pairs. Furthermore, the miR-gene network, target gene-gene interaction analysis, and miR-disease association provide an understanding of the molecular, cellular, and biological processes involved in various pathways regulated by four transcription factors (PPARG, ZNF740, NRF1, and RREB1). Therefore, miR-373-3p, 520e-3p, and four transcription factors can regulate the NR4A2 gene involved in the neurodegenerative process.

Computational investigation for identification of potential phytochemicals and antiviral drugs as potential inhibitors for RNA-dependent RNA polymerase of COVID-19.

Since the SARS/MERS epidemic, scientists across the world have been racing to identify the novel-CoVs as it has been predicted that next epidemic can very well be a result from a new mutation of CoV, for which hundred mutations have already been discovered, and the same fear has come true with world facing a raging pandemic due to COVID-19, an infectious disease caused by a newly discovered coronavirus. COVID-19 or Severe acute respiratory syndrome coronavirus2 (SARS-CoV-2), is a single stranded RNA virus. COVID -19 is highly contagious and has resulted in current global pandemic with almost no country of the world unaffected by this virus. Owing to the lack of effective therapeutics or vaccines, the best measures to control human coronaviruses remain a strong public health surveillance system coupled with rapid diagnostic testing and quarantine/social; distancing/lockdowns as and when necessary. In the present study, we have used the insilico approach for the prediction of novel drug molecules from available antiviral drugs and also from natural compounds that can be best target against RNA-dependent RNA-polymerase (Pol/RdRp) protein of SARS-CoV-2 which can be suitable drugs for the treatment of COVID-19 virus. From the current study we observed that three antiviral and three phyto-chemicals have minimum binding energy with the target protein which were further evaluated in molecular dynamics studies and could specifically bind to RdRp protein of COVID-19. Based on results we suggest that these drugs may act as best or novel inhibitor that may be used for the treatment of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Identification of homologous human miRNAs as antivirals towards COVID-19 genome.

The COVID-19 fatality rate is ~57% worldwide. The investigation of possible antiviral therapy using host microRNA (miRNA) to inhibit viral replication and transmission is the need of the hour. Computational techniques were used to predict the hairpin precursor miRNA (pre-miRNAs) of COVID-19 genome with high homology towards human (host) miRNA. Top 21 host miRNAs with >80% homology towards 18 viral pre miRNAs were identified. The Gibbs free energy (ΔG) between host miRNAs and viral pre-miRNAs hybridization resulted in the best 5 host miRNAs having the highest base-pair complementarity. miR-4476 had the strongest binding with viral pre-miRNA (ΔG = -21.8 kcal/mol) due to maximum base pairing in the seed sequence. Pre-miR-651 secondary structure was most stable due to the (1) least minimum free energy (ΔG = -24.4 kcal/mol), energy frequency, and noncanonical base pairing and (2) maximum number of stem base pairing and small loop size. Host miRNAs-viral mRNAs interaction can effectively inhibit viral transmission and replication. Furthermore, miRNAs gene network and gene-ontology studies indicate top 5 host miRNAs interaction with host genes involved in transmembrane-receptor signaling, cell migration, RNA splicing, nervous system formation, and tumor necrosis factor-mediated signaling in respiratory diseases. This study identifies host miRNA/virus pre-miRNAs strong interaction, structural stability, and their gene-network analysis provides strong evidence of host miRNAs as antiviral COVID-19 agents.

Molecular docking analysis of azithromycin and hydroxychloroquine with spike surface glycoprotein of SARS-CoV-2.

Millions of people are affected by COVID-19 since the last quarter of 2019. Treatment using hydroxychloroquine (HCQ) as monotherapy in combination with azithromycin (HCQ-AZ) were administered at several clinical centres to patients tested positive to the virus across continents. Therefore, it is of interest to document the molecular docking analysis data of azithromycin and hydroxychloroquine drug with the spike surface glycoprotein of novel COVID-19. Thus, we report the molecular modelling docking based structural binding features of HCQ-AZ with the spike surface glycoprotein of COVID-19 for further evaluation in this regard.

Immuno-informatics approach for B-cell and T-cell epitope based peptide vaccine design against novel COVID-19 virus.

COVID-19 has brought the world to a standstill with a wave of destruction in country after country with tremendous loss of lives and livelihood in advanced to developing nations. Whole world is staring at the prospect of repeated lockdowns with another wave of COVID-19 predicted to hit the world in September of 2020. The second wave is assumed to be even more destructive with severe impact across much of the world. The only way to defeat this pandemic is to quickly develop a safe and effective vaccine against this raging menace and initiate a global vaccination drive. Our study is an attempt to deploy various computational methods to identify B-cell and T-cell epitopes from the spike surface glycoprotein of SARS-COV-2 which have the novel potential for vaccine development against COVID-19. For this we have taken 8 unique strains with one each from India, China, France, USA, Italy, Australia, Iran and Pakistan. The strain data was extracted from NCBI Database. By analyzing the immune parameters like surface accessibility, antigenicity, variability, conservancy, flexibility, hydrophilicity, allergenicity and toxicity of the conserved sequences of spike glycoprotein using various databases and bioinformatics tools, we identified two potential novel linear (SGTNGTKRFDN and ASVYAWNRK) and one structural B-cell epitope as well as two T-cell epitopes (RLFRKSNLK and IPTNFTISV) which can be used as epitope-based peptide vaccines. Docking simulation assay revealed that above T-cell epitopes have minimum free binding energy and showed strong hydrogen bond interaction which strengthened its potential as being a T-cell epitope for the epitope-based novel vaccine against SARS-CoV-2. This study allows us to claim that B-cell and T-cell epitopes mentioned above provide potential pathways for developing an exploratory vaccine against spike surface glycoprotein of SARS-CoV-2 with high confidence for the identified strains. We will need to confirm our findings with biological assays.

LXR-α genomics programmes neuronal death observed in Alzheimer's disease.

Keeping in view the fact that the most pathognomonic feature of Alzheimer's disease is the abnormal processing of neuronal cell membrane amyloid precursor protein accompanied by significantly elevated human serum and CSF levels of 24-hydroxycholesterol recognised widely as the specific endogenous ligand of Liver X receptor (LXR-α), the present study was addressed to explore the epigenomic-pathway (if any) that connects LXR-α activation with the genes recognised to be involved in the regulation of aberrant Abeta production leading to the generation of toxic and inflammatory mediators responsible for neuronal death. The results of such a study revealed that LXR-α activation by its specific endogenous or exogenous ligands within neuroblastoma cells resulted in the over-expression of PAR-4 gene accompanied by suppression of AATF gene through its inherent capacity to regulate genes coding for SREBP and NF-κB. Over-expression of PAR-4 gene was accompanied by aberrant Abeta production followed by ROS generation and subsequent death of neuroblastoma cells used in the present study as a cellular model for neurons. Further based upon these results, it was proposed that Abeta-induced heme oxygenase-1 can ensure cholesterol-oxidation to provide endogenous ligands for the sustained activation of neuronal LXR-α dependent epigenomic-pathway leading to neuronal death observed in Alzheimer's disease.