突变序列空间的功能普查：以p53癌症拯救突变体为例。
Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.
作者信息
Danziger Samuel A, Swamidass S Joshua, Zeng Jue, Dearth Lawrence R, Lu Qiang, Chen Jonathan H, Cheng Jianlin, Hoang Vinh P, Saigo Hiroto, Luo Ray, Baldi Pierre, Brachmann Rainer K, Lathrop Richard H
机构信息
University of California, Irvine, CA 92697-3435, USA.
出版信息
IEEE/ACM Trans Comput Biol Bioinform. 2006 Apr-Jun;3(2):114-25. doi: 10.1109/TCBB.2006.22.
Many biomedical problems relate to mutant functional properties across a sequence space of interest, e.g., flu, cancer, and HIV. Detailed knowledge of mutant properties and function improves medical treatment and prevention. A functional census of p53 cancer rescue mutants would aid the search for cancer treatments from p53 mutant rescue. We devised a general methodology for conducting a functional census of a mutation sequence space by choosing informative mutants early. The methodology was tested in a double-blind predictive test on the functional rescue property of 71 novel putative p53 cancer rescue mutants iteratively predicted in sets of three (24 iterations). The first double-blind 15-point moving accuracy was 47 percent and the last was 86 percent; r = 0.01 before an epiphanic 16th iteration and r = 0.92 afterward. Useful mutants were chosen early (overall r = 0.80). Code and data are freely available (http://www.igb.uci.edu/research/research.html, corresponding authors: R.H.L. for computation and R.K.B. for biology).
许多生物医学问题都与感兴趣的序列空间中的突变功能特性相关，例如流感、癌症和艾滋病病毒。对突变特性和功能的详细了解有助于改善医疗和预防。对p53癌症拯救突变体进行功能普查将有助于从p53突变体拯救中寻找癌症治疗方法。我们设计了一种通用方法，通过尽早选择信息丰富的突变体来对突变序列空间进行功能普查。该方法在对71个新的假定p53癌症拯救突变体的功能拯救特性进行的双盲预测测试中进行了测试，这些突变体以三个一组的方式进行迭代预测（共24次迭代）。第一次双盲15点移动准确率为47%，最后一次为86%；在第16次顿悟迭代之前r = 0.01，之后r = 0.92。有用的突变体被尽早选择（总体r = 0.80）。代码和数据可免费获取（http://www.igb.uci.edu/research/research.html，计算方面的通讯作者：R.H.L.，生物学方面的通讯作者：R.K.B.）。
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