STRUCTURE PREDICTION BY PROTEIN THREADING

我们已经开发出计算机方法来预测蛋白质的三维结构 通过识别折叠主题来构建结构。蛋白质的序列是 通过数据库中的备用主干结构进行“线程”处理，以及 确定了该序列最稳定的构象。这个 工作集中在三个方面：1)快速评估的 经验自由能函数，2)FAST算法测试 穿透有缝隙的“芯”图案，以及3)芯的识别 要包括在数据库中的子结构。今年我们已经展示了 基于残基接触势的能量函数可以识别 正确的核心主题和在数十亿美元 可供选择，这一特性足以解决许多预测问题。我们 已经对序列的影响进行了统计校正 构图和长度，否则会降低主题识别 专一性。我们已经测试了一种基于Monte的快速线程算法 卡罗技术，并发现它能够识别最优 在几秒钟内对序列和固定大小的核心基序进行比对， 所有这种最优情况都可以通过以下方式确定 枚举。为了定义我们提取的折叠图案的数据库 来自蛋白质数据库的亚结构，由主要螺旋和 Beta-strand，使用抵抗局部扭曲和/或 坐标不精确。每一个都定义了一系列相关的核心主题， 当以蒙特卡洛算法为线程时，允许删除和/或 单个二级结构元素的大小变化。测试 该自适应线程算法及其关联的数据库在 进步。这项研究的意义在于，这些方法可能 允许自动搜索折叠基序数据库，预测 蛋白质中可能几乎没有共同点的亚结构构象 与晶体数据库中的蛋白质同源。

We have developed computer methods to predict protein three-dimensional structure by recognition of folding motif. A protein's sequence is "threaded" through alternative backbone structures in a database, and the conformations most stabilized by that sequence are identified. The work has focused on three areas: 1) derivation of a rapidly-evaluated empirical free energy function, 2) testing of algorithms for fast threading through gapped "core" motifs, and 3) identification of core sub-structures to be included in the database. This year we have shown that an energy function based on residue contact potentials can identify the correct core motif and alignment among many billions of alternatives, a specificity sufficient for many prediction problems. We have developed statistical corrections for effects of sequence composition and length, which otherwise reduce motif-recognition specificity. We have tested a fast-threading algorithm based on a monte carlo technique, and found that it is capable of identifying optimal alignments of sequence and fixed-size core motifs in a few seconds, in all cases where this optimum can be determined with certainty by enumeration. To define a database of folding motifs we have extracted from the Protein Data Bank substructures consisting of major helices and beta-strands, using an algorithm resistant to local distortions and/or coordinate imprecision. Each defines a family of related core motifs, when threaded with a monte carlo algorithm that allows deletions and/or changes in size of individual secondary structure elements. Testing of this adaptive threading algorithm and its associated database is in progress. The significance of this research is that these methods may allow automated search of a folding motif database, predicting substructure conformations in proteins which may share little or no homology with proteins in the crystallographic database.