In silico: analysis of retinoblastoma gene & novel drug designing
Clinical Proteomics and Bioinformatics
Data mining has emerged as a very powerful tool to extract information. In the present study RB1 gene, which is a tumor suppressor gene has been studied. Data mining is done first at Ground Level Mining, in which relevant data sets are collected and then reduced to the minimum size possible through statistical representation. Chromosome Report is studied to determine the chromosome location of the gene under study. It regulates cell cycle as a check point for p53 and for other genes as well,
... r genes as well, specifying cell fate. The mRNA Report gives detailed information regarding the gene for its identification and transcript sequences. The Peptide Report reveals highly descriptive data regarding protein, SNP regions, position and alleles. A special emphasis is given to protein interactions and blastp result for study of homologous protein sequences. Phylogenetic tree is generated using homologous protein sequences for Phylogenetic Inference and homology with other taxa. The preclinical data of cyclosporine has suggested that it has a significant role in treating retinoblastoma malignancies but the binding of Actinomycin-D with Rb is far better as evident by the low e-total value signifying its greater affinity. Therefore the drug is suggested as a potential drug for future in treatment of retinoblastoma and associated retinoblastoma malignancies.