Computational investigation reveals that the mutant strains of SARS-CoV2 have differential structural and binding properties

SARS-CoV2 Nsp3 protein triggers cell death and exacerbates amyloid β42-mediated neurodegeneration

JOURNAL/nrgr/04.03/01300535-202406000-00044/inline-graphic1/v/2023-10-30T152229Z/r/image-tiff

Infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) virus, responsible for the coronavirus disease 2019 (COVID-19) pandemic, induces symptoms including increased inflammatory response, severe acute respiratory syndrome (SARS), cognitive dysfunction like brain fog, and cardiovascular defects. Long-term effects of SARS-CoV2 COVID-19 syndrome referred to as post-COVID-19 syndrome on age-related progressive neurodegenerative disorders such as Alzheimer’s disease remain understudied. Using the targeted misexpression of individual SARS-CoV2 proteins in the retinal neurons of the Drosophila melanogaster eye, we found that misexpression of nonstructural protein 3 (Nsp3), a papain-like protease, ablates the eye and generates dark necrotic spots. Targeted misexpression of Nsp3 in the eye triggers reactive oxygen species production and leads to apoptosis as shown by cell death reporters, terminal deoxynucleotidyl transferase (TdT) dUTP Nick-end labeling (TUNEL) assay, and dihydroethidium staining. Furthermore, Nsp3 misexpression activates both apoptosis and autophagy mechanism(s) to regulate tissue homeostasis. Transient expression of SARS-CoV2 Nsp3 in murine neuroblastoma, Neuro-2a cells, significantly reduced the metabolic activity of these cells and triggers cell death. Misexpression of SARS-CoV2 Nsp3 in an Alzheimer’s disease transgenic fly eye model (glass multiple repeats [GMR]>amyloid β42) further enhances the neurodegenerative rough eye phenotype due to increased cell death. These findings suggest that SARS-CoV2 utilizes Nsp3 protein to potentiate cell death response in a neurodegenerative disease background that has high pre-existing levels of neuroinflammation and cell death.

Nucleocapsid single point-mutation associated with drop-out on RT-PCR assay for SARS-CoV-2 detection

BACKGROUND

Since its beginning, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been a challenge for clinical and molecular diagnostics, because it has been caused by a novel viral agent. Whole-genome sequencing assisted in the characterization and classification of SARS-CoV-2, and it is an essential tool to genomic surveillance aiming to identify potentials hot spots that could impact on vaccine immune response and on virus diagnosis. We describe two cases of failure at the N2 target of the RT-PCR test Xpert® Xpress SARS-CoV-2.

METHODS

Total nucleic acid from the Nasopharyngeal (NP) and oropharyngeal (OP) swab samples and cell supernatant isolates were obtained. RNA samples were submitted to random amplification. Raw sequencing data were subjected to sequence quality controls, removal of human contaminants by aligning against the HG19 reference genome, taxonomic identification of other pathogens and genome recovery through assembly and manual curation. RT-PCR test Xpert® Xpress SARS-CoV-2 was used for molecular diagnosis of SARS-CoV-2 infection, samples were tested in duplicates.

RESULTS

We identified 27 samples positive for SARS-CoV-2 with a nucleocapsid (N) gene drop out on Cepheid Xpert® Xpress SARS-CoV-2 assay. Sequencing of 2 of 27 samples revealed a single common mutation in the N gene C29197T, potentially involved in the failed detection of N target.

CONCLUSIONS

This study highlights the importance of genomic data to update molecular tests and vaccines.

Whole exome sequencing identifies novel variants of PIK3CA and validation of hotspot mutation by droplet digital PCR in breast cancer among Indian population

BACKGROUND

Breast cancer (BC) is the most common malignancy with very high incidence and relatively high mortality in women. The PIK3CA gene plays a pivotal role in the pathogenicity of breast cancer. Despite this, the mutational status of all exons except exons 9 and 20 still remains unknown.

METHODS

This study uses the whole exome sequencing (WES) based approach to identify somatic PIK3CA mutations in Indian BC cohorts. The resultant hotspot mutations were validated by droplet digital PCR (ddPCR). Further, molecular dynamics (MD) simulation was applied to elucidate the conformational and functional effects of hotspot position on PIK3CA protein.

RESULTS

In our cohort, PIK3CA showed a 44.4% somatic mutation rate and was among the top mutated genes. The mutations of PIK3CA were confined in Exons 5, 9, 11, 18, and 20, whereas the maximum number of mutations lies within exons 9 and 20. A total of 9 variants were found in our study, of which 2 were novel mutations observed on exons 9 (p.H554L) and 11 (p.S629P). However, H1047R was the hotspot mutation at exon 20 (20%). In tumor tissues, there was a considerable difference between copy number of wild-type and H1047R mutant was detected by ddPCR. Significant structural and conformational changes were observed during MD simulation, induced due to point mutation at H1047R/L position.

CONCLUSIONS

The current study provides a comprehensive view of novel as well as reported single nucleotide variants (SNVs) in PIK3CA gene associated with Indian breast cancer cases. The mutation status of H1047R/L could serve as a prognostic value in terms of selecting targeted therapy in BC.

Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation

BACKGROUND AND OBJECTIVE

The current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp.

METHODS

Herein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp-inhibitor complexes.

RESULTS

Based on docking scores and significant binding interactions with crucial residues (Lys553, Arg557, Lys623, Cys815, and Ser816) in the RNA binding site of RdRp, three existing drugs, ZINC285540154, ZINC98208626, ZINC28467879, and five compounds from ZINC20 (ZINC739681614, ZINC1166211307, ZINC611516532, ZINC1602963057, and ZINC1398350200) were selected, and the conformational stability of RdRp due to their binding was confirmed through molecular dynamics simulation. The free energy calculations revealed these compounds possess strong binding affinities for RdRp. In addition, these novel inhibitors exhibited drug-like features, good absorption, distribution, metabolism, and excretion profile and were found to be non-toxic.

CONCLUSION

The compounds identified in the study by multifold computational strategy can be validated in vitro as potential non-nucleoside inhibitors of SARS-CoV-2 RdRp and holds promise for the discovery of novel drugs against COVID-19 in future.

In silico scanning of structural and functional deleterious nsSNPs in Arabidopsis thaliana's SOG1 protein, using molecular dynamic simulation approaches

Suppressor of gamma response 1 (SOG1) is a member of the NAC domain family transcription factors of the DNA damage response (DDR) signaling in the plant's genome. SOG1 is directly involved in transcriptional response to DNA damage, cell cycle checkpoints and ATR or ATM-mediated activation of the DNA damage responses and repair functioning in programmed cell death and regulation of end reduplication. Different mutations in the SOG1 protein lead to severe diseases and, ultimately, cell death. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that cause different diseases or programmed cell death. The current study applied different computational approaches to Arabidopsis thaliana L. SOG1 protein to identify the potential deleterious nsSNPs and monitor their impact on the structure, function and protein stability. Various bioinformatics tools were applied to analyze the retrieved 34 nsSNPs and interestingly extracted four deleterious nsSNPs, that is, ensvath13968004 (Q166L), tmp18998388 (P159L), ensvath01103049 (K199N) and tmp18998295 (Y190F). For example, homology modeling, conservation and conformational analysis of the mutant's models were considered to scrutinize the deviations of these variants from the native SOG1 structure. All atoms molecular dynamic simulation confirmed the significance of these mutations on the protein stability, residual and structural conformation, compactness, surface conformation, dominant motion, Gibbs free energy distribution and dynamic effects. Similarly, protein-protein interaction revealed that SOG1 operates as a hub-linking cluster of various proteins, and any changes in the SOG1 might result in the disassociation of several signal transduction cascades.Communicated by Ramaswamy H. Sarma.