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Combinatorial networks Victor S. Lobanov and Dimitris K. Agrafiotis

Summary: Combinatorial networks
Victor S. Lobanov and Dimitris K. Agrafiotis
3-Dimensional Pharmaceuticals, Inc., Exton, PA, USA
A novel approach for the analysis and virtual screening of
large combinatorial libraries is presented. The method at-
tempts to relieve the computational burden by computing the
properties of the products in a way that does not require
their explicit enumeration. In particular, a small subset of
compounds from the virtual library is identified and their
descriptors are calculated in a conventional manner. The
resulting data is used as input to a multilayer perceptron,
which is trained to predict the descriptors of the products
from the descriptors of their respective building blocks.
Once trained, the neural network is able to estimate the
descriptors of the remaining members of the virtual library
with remarkable accuracy, without ever, generating their
connection tables. This method eliminates the two most
time-consuming steps in virtual screening and allows the
processing of very large combinatorial libraries that are
intractable with conventional techniques. 2001 by


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


Collections: Chemistry; Computer Technologies and Information Sciences