STATISTICS OF PROTEIN THREADING

需要严格的统计数据， 结构比较现在普遍承认，特别是在 在NCBI的BLAST程序套件的成功之光。 从在序列问题中应用统计学到应用 他们在结构问题显然是下一步整理 蛋白质之间的距离蛋白质线程是 获取查询序列的操作，并测试其 匹配结构数据库的成员。述结构可以是 被认为是固定方向的管道（二级结构）， 蛋白质残基之间相互作用的距离。中的残基 查询序列就像一串不同颜色的珠子。 “珠子串”是“线程”通过“管”，直到 蛋白质残基之间的相互作用是有利的， 可能问题随之而来：最有利的相互作用 发现与偶然性一致，还是表明 查询序列结构的系统相似性与试探性 线程结构？我们有一些初步的近似， 统计意义是令人鼓舞的，因为他们 系统性和一致性地高估真实p值， 系数约300。我们目前正在研究 产生这种高估的结构相关性，来纠正它。

The need for rigorous statistics in sequence and structure comparison is now generally conceded, particularly in light of the success of the BLAST suite of programs at NCBI. Moving from applying statistics in sequence problems to applying them in structure problems is clearly the next step in sorting out distant relations between proteins. Protein threading is the operation of taking a query sequence, and testing its ability to match members of a structural database. The structures may be thought of as tubes (secondary structures) that fix orientations and distances for interactions between protein residues. The residues in the query sequence are like differently colored beads in a string. The "string of beads" is "threaded" through the "tubes" until interactions between the protein residues are as favorable as possible. The question then arises: is the most favorable interaction discovered consistent with chance alone, or does it indicate a systematic similarity of query sequence's structure with the tentative threading structure? We have some initial approximations to the statistical significance that are encouraging, in that they systematically and consistently overestimate the true p-values by a factor of about 300. We are currently exploring the protein structural correlations that produce this overestimate, to correct it.