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Multidimensional Scaling of Combinatorial Libraries without
 

Summary: Multidimensional Scaling of
Combinatorial Libraries without
Explicit Enumeration
DIMITRIS K. AGRAFIOTIS, VICTOR S. LOBANOV
3-Dimensional Pharmaceuticals, Inc., 665 Stockton Drive, Exton, Pennsylvania 19341
Received 2 January 2001; accepted 15 May 2001
ABSTRACT: A novel approach for the multidimensional scaling of large
combinatorial libraries is presented. The method employs a multilayer
perceptron, which is trained to predict the coordinates of the products on the
nonlinear map from pertinent features of their respective building blocks. This
method limits the expensive enumeration and descriptor generation to only a
small fraction of products and, in addition, relieves the enormous computational
effort required for the low-dimensional embedding by conventional iterative
multidimensional scaling algorithms. In effect, the method provides an explicit
mapping function from reagents to products, and allows the vast majority of
compounds to be projected without constructing their connection tables. The
advantages of this approach are demonstrated using two combinatorial libraries
based on the reductive amination and Ugi reactions, and three descriptor sets
that are commonly used in similarity searching, diversity profiling and
structure­activity correlation. © 2001 John Wiley & Sons, Inc. J Comput

  

Source: Agrafiotis, Dimitris K. - Molecular Design and Informatics Group, Johnson & Johnson Pharmaceutical Research and Development

 

Collections: Chemistry; Computer Technologies and Information Sciences