Codon Usage Bias Analysis of Human Papillomavirus 18s L1 Protein and its Host Adaptability
Shinde, V. V.; Bankariya, S.; Kaur, P.
Show abstract
Human Papillomavirus 18 (HPV 18) is known as a high-risk variant associated with cervical and anogenital malignancies. High-risk types HPV 18 and HPV 16 (human papillomavirus 16) play a major part in about 70 percent of cervical cancer worldwide (Ramakrishnan et al., 2015). The L1 protein of HPV 18 (HPV 18s L1 protein), also known as major capsid L1 protein is targeted in the vaccine development against HPV 18 due to its non-oncogenic and non-infectious properties with self-assembly ability into virus-like particles. In the present analysis, an extensive codon usage bias analysis of HPV 18s L1 protein and adaptation to its host human was conducted. The Effective number (Nc) Grand Average of Hydropathy (GRAVY), Index of Aromaticity (AROMO), and Codon Bias Index (CBI) values revealed no biases in codon usage of HPV 18s L1 protein. The data of the Codon Adaptation Index (CAI), and Relative Codon Deoptimization Index (RCDI) indicate adaptation of HPV 18s L1 protein according to its host human. The domination of selection pressure on codon usage of HPV 18s L1 protein was demonstrated based on GC12 vs GC3, Nc vs GC3, and frequency of optimal codons (FOP). The Parity plot revealed that the genome of HPV 18s L1 protein has a preference for purine over pyrimidine, that is G nucleotides over C, and no preference for A over T but A/T richness was observed in the genome of HPV 18s L1 protein. In the Nucleotide composition, GC1 richness ultimately represents evolutionary aspects of codon usage. Furthermore, these findings can be used in currently ongoing vaccine development and gene therapy to design viral vectors.
Matching journals
The top 12 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- An Issue of Concern: Unique Truncated ORF8 Protein Variants of SARS-CoV-2 97%
- Identification of novel mutations in RNA-dependent RNA polymerases of SARS-CoV-2 and their implications on its protein structure 96%
- Prediction of antiviral drugs against African Swine Fever Viruses based on protein-protein interaction analysis 92%
Similar papers in this journal
- In silico comparative genomics of SARS-CoV-2 to determine the source and diversity of the pathogen in Bangladesh 95%
- SARS-CoV-2: Proof of recombination between strains and emergence of possibly more virulent ones 95%
- Comparative in silico analysis of ftsZ gene from different bacteria reveals the preference for core set of codons in coding sequence structuring and secondary structural elements determination 95%
Similar papers in this journal
- Analysis of single nucleotide polymorphisms between 2019-nCoV genomes and its impact on codon usage 96%
- Whole Genome Comparison of Pakistani Corona Virus with Chinese and US Strains along with its Predictive Severity of COVID-19 95%
- In silico analysis of SNPs in human phosphofructokinase, Muscle (PFKM) gene: An apparent therapeutic target of aerobic glycolysis and cancer 95%
Similar papers in this journal
- Comparative Analysis of Human Coronaviruses Focusing on Nucleotide Variability and Synonymous Codon Usage Pattern 97%
- SARS-CoV-2 transcriptome analysis and molecular cataloguing of immunodominant epitopes for multi-epitope based vaccine design 94%
- A Computational Approach to Design Potential siRNA Molecules as a Prospective Tool for Silencing Nucleocapsid Phosphoprotein and Surface Glycoprotein Gene of SARS-CoV-2 93%
Similar papers in this journal
- Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India 95%
- Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for advantageous mutations for growth in human cells 93%
- The baculovirus promoter OpIE2 sequence has inhibitory effect on the activity of the Cytomegalovirus (CMV) promoter in HeLa and HEK-293T cells 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.