Biology subjects

Karuppanan, K.

Publications and source records attributed to Karuppanan, K..

5 recordsLinked to original sources

bioRxiv2022

Omicron (BA.1) and Sub-Variants (BA.1, BA.2 and BA.3) of SARS-CoV-2 Spike Infectivity and Pathogenicity: A Comparative Sequence and Structural-based Computational Assessment

The Omicron variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread throughout the world. We used computational tools to assess the spike infectivity, transmission, and pathogenicity of Omicron (BA.1) and sub-variants (BA.1.1, BA.2, and BA.3) in this study. BA.1 has 39 mutations, BA.1.1 has 40 mutations, BA.2 has 31 mutations, and BA.3 has 34 mutations, with 21 shared mutations between all. We observed 11 common mutations in Omicrons receptor-binding domain and sub-variants. In pathogenicity analysis, the Y505H, N786K, T95I, N211I, N856K, and V213R mutations in omicron and sub-variants are predicted to be deleterious. Due to the major effect of the mutations characterising, in the receptor-binding domain (RBD), we found that Omicron and sub-variants had a higher positive electrostatic surface potential. This could increase interaction between RBD and electronegative human angiotensin-converting enzyme 2 (hACE2). Omicron and sub-variants had a higher affinity for hACE2 and the potential for increased transmission when compared to the wild type. Among Omicron sub-lineages, BA.2 and BA.3 have a higher transmission potential than BA.1 and BA.1.1. We predicted that mutated residues in BA.1.1 (K478), BA.2 (R400, R490, R495), and BA.3 (R397 and H499) formation of new salt bridges and hydrogen bonds. Omicron and sub-variant mutations at Receptor-binding Motif (RBM) residues such as Q493R, N501Y, Q498, T478K, and Y505H all contribute significantly to binding affinity with human ACE2. Interactions with Omicron variant mutations at residues 493, 496, 498, and 501 seem to restore ACE2 binding effectiveness lost due to other mutations like K417N and Y505H.

bioinformatics↗

bioRxiv2021

Omicron and Delta Variant of SARS-CoV-2: A Comparative Computational Study of Spike protein

Emerging SARS-CoV-2 variants, especially those of concern, may have an impact on the viruss transmissibility and pathogenicity, as well as diagnostic equipment performance and vaccine effectiveness. Even though the SARS-CoV-2 Delta variant (B.1.617.2) emerged during Indias second wave of infections, Delta variants have grown dominant internationally and are still evolving. On November 26, 2021, WHO identified the variant B.1.1.529 as a variant of concern, naming it Omicron, based on evidence that Omicron contains numerous mutations that may influence its behaviour. However, the mode of transmission and severity of the Omicron variant remains unknown. We used computational studies to examine the Delta and Omicron variants in this work and found that the Omicron variant had a higher affinity for human ACE2 than the Delta variant due to a significant number of mutations in the SARS-CoV-2 receptor binding domain, indicating a higher potential for transmission. Based on docking studies, the Q493R, N501Y, S371L, S373P, S375F, Q498R, and T478K mutations contribute significantly to high binding affinity with human ACE2. In comparison to the Delta variant, both the entire spike protein and the RBD in Omicron include a high proportion of hydrophobic amino acids such as leucine and phenylalanine. These amino acids are located within the proteins core and are required for structural stability. Omicron has a higher percentage of alpha-helix structure than the Delta variant in both whole spike protein and RBD, indicating that it has a more stable structure. We observed a disorder-order transition in the Omicron variant between spike protein RBD regions 468-473, and it may be significant in the influence of disordered residues/regions on spike protein stability and binding to ACE2. A future study might investigate the epidemiological and biological consequences of the Omicron variant.

bioinformatics↗

bioRxiv2021

Affinity sedimentation and magnetic separation with plant-made immunosorbent nanoparticles for therapeutic protein purification

The virus-based immunosorbent nanoparticle is a nascent technology being developed to serve as a simple and efficacious agent in biosensing and therapeutic antibody purification. There has been particular emphasis on the use of plant virions as immunosorbent nanoparticle chassis for their diverse morphologies and accessible, high yield manufacturing via crop cultivation. To date, studies in this area have focused on proof-of-concept immunosorbent functionality in biosensing and purification contexts. Here we consolidate a previously reported pro-vector system into a single Agrobacterium tumefaciens vector to investigate and expand the utility of virus-based immunosorbent nanoparticle technology for therapeutic protein purification. We demonstrate the use of this technology for Fc-fusion protein purification, characterize key nanomaterial properties including binding capacity, stability, reusability, and particle integrity, and present an optimized processing scheme with reduced complexity and increased purity. Furthermore, we present a coupling of virus-based immunosorbent nanoparticles with magnetic particles as a strategy to overcome limitations of the immunosorbent nanoparticle sedimentation-based affinity capture methodology. We report magnetic separation results which exceed the binding capacity of current industry standards by an order of magnitude.

bioengineering↗

bioRxiv2021

Identification of COVID-19 and COPD common key genes and pathways using a protein-protein interaction approach

Coronavirus disease (COVID-19) is an extremely contagious and cognitive disease that could cause immense hypoxemia. The rise in critically ill patients in epidemic regions has put enormous pressure on hospitals. There is a need to define extreme COVID-19 clinical determinants to optimize clinical diagnosis and the management system is strong. Chronic obstructive pulmonary disease (COPD) is linked to a rapidly increasing risk of death rates in population pneumonia. In this research, a network of protein-protein interaction (PPI) was developed using constructed datasets of COVID-19 and COPD genes to define the interrelationship between COVID-19 and COPD, how it affects each other, and the genes that are responsible for the process. The PPI network shows the top 10 common overlapping genes, which include IL10, TLR4, TNF, IL6, CXCL8, IL4, ICAM1, IFNG, TLR2, and IL18. These are the genes that COVID-19 and high-risk COPD patients are known to be expressed. These important genes shared by COVID-19 and COPD are involved in pathways such as malaria, African trypanosomiasis, inflammatory bowel disease, Chagas disease, influenza, and tuberculosis.

bioinformatics↗

bioRxiv2021

Identification of common key genes and pathways between Covid-19 and lung cancer by using protein-protein interaction network analysis

COVID-19 is indeed an infection that is caused by a recently found coronavirus group, a type of virus proven to cause human respiratory diseases. The high mortality rate was observed in patients who had pre-existing health conditions like cancer. However, the molecular mechanism of SARS-CoV-2 infection in lung cancer patients was not discovered yet at the pathway level. This study was about determining the common key genes of COVID-19 and lung cancer through network analysis. The hub genes associated with COVID-19 and lung cancer were identified through Protein-Protein interaction analysis. The hub genes are ALB, CXCL8, FGF2, IL6, INS, MMP2, MMP9, PTGS2, STAT3 and VEGFA. Through gene enrichment, it is identified both COVID-19 and lung cancer have a common pathway in EGFR tyrosine kinase inhibitor resistance, IL-17 signalling pathway, AGE-RAGE signalling pathway in diabetic complications, HIF-1 signalling pathway and pathways in cancer.

bioinformatics↗