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Deciphering a Pharmacophore Network: A Case Study Using BCRABL Data
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DOI：10.1021/acs.jcim.1c00427.png)
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Abstract
En 中文
This paper introduces a general method that can be used to create groups of pharmacophores to support their further in-depth analysis. A BCR-ABL molecular dataset was used to calculate graph edit distances between pharmacophores and led to their organization into a novel pharmacophore network. The application of a graph layout algorithm allowed us to discriminate between the pharmacophores associated with active compounds and those associated with inactive compounds. A clustering approach was used to refine the partitioning by grouping the pharmacophores based on their structures, activities, and binding modes. Analysis of a newly spatialized pharmacophore network provided us with critical insight into structure-activity relationships, most notably those that revealed distinctions between activity classes and chemical families. As shown, this method permits us to identify families of structurally homogeneous pharmacophores.
Keywords:
DISCOVERY
INHIBITOR
TYROSINE
UTILITY
SPACE
Journal
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5.3
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