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Cancer being one of the dreadful diseases with no perfect treatment till date is laying a platform for the continuous research. Molecular methodologies for the diagnosis and analysis are gaining rapid importance and accuracy. The current work aimed to Collect the cancer blood samples followed by the extraction and purification of the DNA. The DNA thus obtained was used for the amplification of the P53 gene, one of the very important gene involved in the cancer cell metabolism. The amplification was performed using universal primers and the sequencing was performed. The sequence thus obtained was further used for insilico analysis. In the Insilico method the protein sequence corresponding to the obtained gene sequence was retrieved from the available Database Gene cards. The protein sequence was later used to develop the 3D structure of the protein as can be obtained from RCSB Protein Data Bank. This structure was targeted to dock with 10 of the 50 chemicals used for screening. The screening of the chemicals included the Drug likeliness, Ambiguity and Toxicity analysis. The docking was performed in HEX Software and the results were analyzed. Based on the results obtained it can be concluded that the chemical p53 modulator 10d with the docking energy of -275.77 is the best potent ligand used to bind with the receptor P53. Thus it can be used as one of the good drugs in treating the symptoms of cancer.
Insilico Drug Designing, P53 Modulator 10d, Docking
Cancer also known as a malignant tumor or malignant neoplasm, is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. Not all tumors are cancerous; benign tumors do not spread to other parts of the body. Possible signs and symptoms include: a new lump, abnormal bleeding, a prolonged cough, unexplained weight loss, and a change in bowel movements among others. While these symptoms may indicate cancer they may also occur due to other issues. There are over 100 different known cancers that affect humans. The “war against cancer” is, in actuality, a battle against a large group of sometimes very different conditions caused by differing agents. Generally, cancer results from an altered balance between cell proliferation – growth and division – and cell death. A number of factors, including certain genes, viruses, chemicals or exposure to radiation, have been blamed for these normal activities gone awry. Mutations in identifiable genes are, as a group, the latest of these factors to be discovered. They have also served as fuel for excitement over potential clues to ways that drugs may be designed to battle the varied disease. Cancer is a genetic disease; it results from mutations in somatic cells. To understand it at a molecular level, we need to identify the relevant mutations and to discover how they give rise to cancerous cell behavior. Finding the mutations is easy in one respect: the mutant cells are favored by natural selection and call attention to them selves by giving rise to tumors. The hard task then begins: how are the genes with the carcinogenic mutations to be identified among all the other genes in the cancerous cells? A similar needle-in-haystack problem arises in any search for a gene underlying a given mutant phenotype, but for cancer the task is particularly complex. To make matters worse, most cancer cells will contain mutations that are accidental by-products of genetic instability, and it can be difficult to distinguish these from the mutations that have a causative role in the disease.
In the relatively short history of cancer genetics as is apparent from this, the accrual of p53 mutations equips emerging tumor cells with much more than just the loss of wtp53 tumor suppressor function. This poses mutp53 as a valid target for inactivation by prospective anticancer therapies. A number of such molecules have already been identified and described, and shown to exert antitumor effects in experimental mouse models. Yet, approaches that are more directly aimed toward elimination of mutp53, such as therapeutic administration of p53 siRNA to cancer patients whose tumors exhibit high mutp53 expression, are also worthy of consideration. Moreover, one may attempt to target proteins whose expression is markedly up-regulated by mutp53,
Particularly in cases in which such proteins are “druggable” targets, such as transmembrane or secreted proteins or enzymes whose catalytic activity is susceptible to inhibition by small molecular weight compounds.
The current work was aimed to identify the SNP if any present in the P53 gene of the Homo sapiens that has a major role in cell division and onset of cancer. The blood samples were collected from 10 patients and it was found that at some point in the gene there was a change in the amino acid G to C in 3 of the 10 samples. These results cannot be taken as conclusive evidence for the role of SNP in diseased condition as only 3 out of the 10 samples were showing the mutant allele in spite of the fact that all the fact that all the samples were from the effected patients. Some patients were having the mutate allele where as the others possessed normal allele in spite of their diseased condition. Thus a complete conclusion cannot be drawn from the data; the work can be extended with an increased sample size to obtain conclusive evidence. Further the work was processed for Insilico Drug development against the P53 protein involved in Cancer. The structure of the protein was obtained from the Public Database RCSB PDB. The structure was further used for docking with the ligand selected from the Pubchem Database. The ligand was obtained from the Pubchem after screening for several parameters. The ligand that was selected after docking was P53 Modulator 10d due to its lowest docking energy of -257.77. Thus its can be concluded that this ligand can be used in the treatment of Cancer for targeting the P53 protein.
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