Hassan M, Bielawski J P, Hempel J C, Waldman M
Molecular Simulations Inc., San Diego, CA 92121, USA.
Mol Divers. 1996 Oct;2(1-2):64-74. doi: 10.1007/BF01718702.
One of the major goals of rational design of combinatorial libraries is to design libraries with maximum diversity to enhance the potential of finding active compounds in the initial rounds of high-throughput screening programs. We present strategies to visualize and optimize the structural diversity of sets of molecules, which can be either potential substituents to be attached at specific positions of the library scaffold, or entire molecules corresponding to enumerated libraries. The selection of highly diverse subsets of molecules from the library is based on the stochastic optimization of 'Diversity' functions using a single-point-mutation Monte Carlo technique. The Diversity functions are defined in terms of the distances among molecules in multidimensional property space resulting from the calculation of 2D and 3D molecular descriptors. Several Diversity functions, including an implementation of D-Optimal design, are applied to select diverse subsets and the results are compared. The diversity of the selected subsets of molecules is visualized by embedding the intermolecular distances, defined by the molecules in multidimensional property space, into a three-dimensional space.
组合文库合理设计的主要目标之一是设计具有最大多样性的文库，以提高在高通量筛选程序首轮中发现活性化合物的可能性。我们提出了可视化和优化分子集结构多样性的策略，这些分子集既可以是要连接在文库支架特定位置的潜在取代基，也可以是对应于枚举文库的完整分子。从文库中选择高度多样化的分子子集是基于使用单点突变蒙特卡罗技术对“多样性”函数进行随机优化。多样性函数是根据二维和三维分子描述符计算得出的多维属性空间中分子之间的距离来定义的。应用了几种多样性函数，包括D - 最优设计的一种实现方式，来选择不同的子集并比较结果。通过将多维属性空间中分子定义的分子间距离嵌入到三维空间中，来可视化所选分子子集的多样性。
