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Pathway Modeling of Prostate Cancer, Breast Cancer and TuberculosisBKBK

6th World Congress on Biotechnology

BK Malik1, Sunkara Mounika2, Vaishali Chakraborty2, Yogesh Kumar Jakhar2, Poonam Malik2, Neha Malik3, Uzma Khanam2, Nameet Kaur1 and Mustafa Alhajiisa1

1Sharda University, India 2Amity University Noida, UP, India 3Northwestern University Chicago, USA

Posters-Accepted Abstracts: J Biotechnol Biomater

DOI: 10.4172/2155-952X.C1.044

Abstract
Pathway modeling gives us a view of the natural systems and their interactions and helps to generate new hypothesis. The present study focuses on the analysis of pathways involvedin Breast cancer and Prostate cancer.The hypersensitivity pathway responsible for Androgen Independent Prostate Cancer showed that the enzyme 5-�±-reductase is the key regulator of this pathway. Hence, if this enzyme is targeted from the drug development aspect it may help to combat prostate cancer. Similarly, by reducing the concentration of homocysteine and controlling the low levels of folate in the metabolic pathways with respect to time course would help to control the breast cancer risk in women. Here, the COPASI model is used to know the pathway modelling of particular pathway which would help in altering the malfunctioning of the pathway. As the pathway modelling completely based on the time course and concentration levels, the amount risk factors can be controlled with equal maintenance of time and concentrations.Tuberculosis, caused by Mycobacterium tuberculosis is one of the main diseases to mankind. Designing of appropriate antimicrobial agents depend upon the novel drug targets of pathogen. COPASI model has been used for the simulation and modeling of shikimate pathway. The shikimate pathway starts from condensation of 2-phosphoenolpyruvate and D-erythrose-4- phosphate to chorismate.Chorismate is the only precursor for the amino acid biosynthesis in this pathogen.The validated kinetic model can be used to determine the contribution of each enzyme to the final product formation rate, to profile intermediate concentrations, and predict responses to inhibition effects. Using the model, conditions most appropriate for high-throughput screening can be optimized.
Biography

Email: bk.malik@sharda.ac.in

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