Abstract
The colon cancer (CC) is one of the most common malignancies, and more than one million people become the prey of colon cancer every year worldwide. The CC initiates, develops, and progresses in various ways. But all these ways cannot be understood fully to till date. So, any effort taken in the CC research is a step toward prevention and cure of this devastating disease. In the present scenario, there are various in silico approaches as well as computational strategies available for gene expression analysis for CC like SAGEmap, X Profiler, digital gene expression displayer (DGED), digital differential display (DDD), and Digital Extractor. The drug discovery and drug development are very cumbersome, intense, and interdisciplinary processes. There are various methods available for the in silico drug designing and development such as homology modeling, molecular docking, virtual high-throughput screening, quantitative structure-activity relationship, hologram quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), pharmacophore mapping, microarray analysis, conformational analysis, and Monte Carlo simulation. With the help of in silico approaches, many novel drug targets for CC like cytochrome P450 2A7, Rab3A, SFRP1, TLR4, MLH1, MSH6, survivin, FGFR-4, and ras oncogene products (H-ras, K-ras, and N-ras) have been identified. Although these tools can act at good starting points in disease gene discovery, there is a need for experimental validation of in silico-derived differential expression and drug design results.
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Lodhi, S.S., Sinha, M., Jaiswal, Y.K., Wadhwa, G. (2018). In Silico Studies on Colon Cancer. In: Wadhwa, G., Shanmughavel, P., Singh, A., Bellare, J. (eds) Current trends in Bioinformatics: An Insight. Springer, Singapore. https://doi.org/10.1007/978-981-10-7483-7_8
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