Baths Veeky, Roy Utpal, Singh Tarkeshwar
Department of Biological Sciences, Birla Institute of Technology & Science (BITS) Pilani K K BIRLA Goa Campus, Goa 403 726, India.
Theor Biol Med Model. 2011 Mar 31;8:5. doi: 10.1186/1742-4682-8-5.
Fatty acid biosynthesis of Mycobacterium tuberculosis was analyzed using graph theory and influential (impacting) proteins were identified. The graphs (digraphs) representing this biological network provide information concerning the connectivity of each protein or metabolite in a given pathway, providing an insight into the importance of various components in the pathway, and this can be quantitatively analyzed. Using a graph theoretic algorithm, the most influential set of proteins (sets of {1, 2, 3}, etc.), which when eliminated could cause a significant impact on the biosynthetic pathway, were identified. This set of proteins could serve as drug targets. In the present study, the metabolic network of Mycobacterium tuberculosis was constructed and the fatty acid biosynthesis pathway was analyzed for potential drug targeting. The metabolic network was constructed using the KEGG LIGAND database and subjected to graph theoretical analysis. The nearness index of a protein was used to determine the influence of the said protein on other components in the network, allowing the proteins in a pathway to be ordered according to their nearness indices. A method for identifying the most strategic nodes to target for disrupting the metabolic networks is proposed, aiding the development of new drugs to combat this deadly disease.
利用图论分析了结核分枝杆菌的脂肪酸生物合成过程，并鉴定了有影响力（起作用）的蛋白质。代表该生物网络的图（有向图）提供了有关给定途径中每种蛋白质或代谢物连通性的信息，有助于深入了解该途径中各种成分的重要性，并且可以进行定量分析。使用图论算法，鉴定出了最具影响力的蛋白质组（如{1, 2, 3}等组），去除这些蛋白质组可能会对生物合成途径产生重大影响。这组蛋白质可作为药物靶点。在本研究中，构建了结核分枝杆菌的代谢网络，并对脂肪酸生物合成途径进行了潜在药物靶点分析。利用KEGG配体数据库构建代谢网络并进行图论分析。使用蛋白质的接近指数来确定该蛋白质对网络中其他成分的影响，从而可以根据接近指数对途径中的蛋白质进行排序。提出了一种识别破坏代谢网络的最关键靶点的方法，有助于开发对抗这种致命疾病的新药。
