ci0c00290_si_001.pdf (655.32 kB)
Identification of Bioisosteric Substituents by a Deep Neural Network
journal contribution
posted on 2020-06-30, 17:37 authored by Peter ErtlBioisosteric design
is a classical technique used in medicinal
chemistry to improve potency, druglike properties, or the synthetic
accessibility of a compound or to find similar potent compounds that
exist in novel chemical space. Bioisosteric design involves replacing
part of a molecule by another part that has similar properties. Such
replacements may be identified by applying medicinal chemistry knowledge,
by mining chemical databases or by choosing analogues similar in molecular
physicochemical properties. In this article, a novel approach to identify
bioisosteric analogues is described where the suggestions are made
by a deep neural network trained on data collected from a large corpus
of medicinal chemistry literature. The network trained in this way
is able to mimic the decision making of experienced medicinal chemists
and identify standard as well as nonclassical bioisosteric analogues,
even for the structures outside the training set. Examples of the
results are provided and application possibilities are discussed.
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bioisosteric analoguesapplication possibilitiesBioisosteric designnonclassical bioisosteric analoguesBioisosteric Substituentsdruglike propertiesnovel approachmining chemical databasesnovel chemical spacecompoundphysicochemical propertiesSuch replacementschemistry knowledgechemistry literatureDeep Neural Network Bioisosteric design
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