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Computer implemented method for for selecting an optimally diverse library of small molecules based on validated molecular structural descriptors

机译:基于验证的分子结构描述符选择最佳多样性小分子文库的计算机实现方法

摘要

The use for biological screening purposes of a subset (library) of a large combinatorially accessible chemical universe increases the efficiency of the screening process only if the subset contains members representative of the total diversity of the universe. In order to insure inclusion in the subset of molecules representing the total diversity of the universe under consideration, valid molecular descriptors which quantitatively reflect the diversity of the molecules in the universe are required. A unique validation method is used to examine both a new three dimensional steric metric and some prior art metrics. With this method, the relative usefulness/validity of individual metrics can be ascertained from their application to randomly selected literature data sets. By the appropriate application of validated metrics, the method of this invention selects a subset of a combinatorial accessible chemical universe such that the molecules of the subset are representative of all the diversity present in the universe and yet do not contain multiple members which represent the same diversity (oversample). The use of the neighborhood definition of a validated metric may also be used to combine (without oversampling the same diversity) any number of combinatorial screening libraries.
机译:仅当子集包含代表宇宙总多样性的成员时,将大型组合可访问化学宇宙的子集(库)用于生物筛选的目的才可以提高筛选过程的效率。为了确保包括代表所考虑的宇宙总多样性的分子子集,需要有效地定量描述宇宙中分子多样性的分子描述符。一种独特的验证方法用于检查新的三维空间度量和一些现有技术度量。使用这种方法,可以通过将各个指标应用于随机选择的文献数据集来确定其相对有用性/有效性。通过适当应用经验证的量度,本发明的方法选择了组合可访问化学宇宙的一个子集,使得该子集的分子代表宇宙中存在的所有多样性,但不包含代表相同子集的多个成员。多样性(过采样)。验证度量的邻域定义的使用也可以用于组合(不对相同多样性进行过度采样)任意数量的组合筛选库。

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