Leveraging protein quaternary structure to identify oncogenic driver mutations

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• 作者：Gregory A. Ryslik ; Yuwei Cheng ; Yorgo Modis ; Hongyu Zhao
• 刊名：BMC Bioinformatics
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：17
• 期：1
• 全文大小：2,097 KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105

文摘

Background Identifying key “driver” mutations which are responsible for tumorigenesis is critical in the development of new oncology drugs. Due to multiple pharmacological successes in treating cancers that are caused by such driver mutations, a large body of methods have been developed to differentiate these mutations from the benign “passenger” mutations which occur in the tumor but do not further progress the disease. Under the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of algorithms that identify these clusters has become a critical area of research.