Determinants of protein function revealed by combinatorial entropy optimization.

Determinants of protein function revealed by combinatorial entropy optimization.
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DOI:
10.1186/gb-2007-8-11-r232
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发表时间:
2007
期刊:
影响因子:
12.3
通讯作者:
Sander C
Sander C
中科院分区:
生物学1区
文献类型:
--
作者:
Reva B;Antipin Y;Sander C

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提出了一种新的算法,允许仅根据多个序列比对来分配蛋白质特异性残基。这些信息可以用来推断蛋白质的功能。我们使用一种新的算法(组合熵优化[CEO])来识别特异性残基和功能亚家族的蛋白质组相关的进化。特异性残基在亚家族内是保守的,但在亚家族之间是不同的,并且它们通常编码功能多样性。我们得到很好的协议预测特异性残基和实验已知的功能残基在蛋白质界面。这种预测的功能决定因素是有用的解释在自然进化和疾病的突变的功能后果。
A new algorithm is presented allows protein specificity residues to be assigned from multiple sequence alignments alone. This information can be used, amongst other things, to infer protein functions. We use a new algorithm (combinatorial entropy optimization [CEO]) to identify specificity residues and functional subfamilies in sets of proteins related by evolution. Specificity residues are conserved within a subfamily but differ between subfamilies, and they typically encode functional diversity. We obtain good agreement between predicted specificity residues and experimentally known functional residues in protein interfaces. Such predicted functional determinants are useful for interpreting the functional consequences of mutations in natural evolution and disease.
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