Classification of piperazinylalkylisoxazole library by recursive partitioning

Hye Jung Kim, Woo Kyu Park, Seo Cho Yong, Tai No Kyoung, Yeong Koh Hun, Hyunah Choo, Nim Pae Ae

Research output: Contribution to journalArticle

Abstract

A piperazinylalkylisoxazole library containing 86 compounds was constructed and evaluated for the binding affinities to dopamine (D3) and serotonin (5-HT2A/2C) receptor to develop antipsychotics. Dopamine antagonists (DA) showing selectivity for D3 receptor over the D2 receptor, serotonin antagonists (SA), and serotonindopamine dual antagonists (SDA) were identified based on their binding affinity and selectivity. The analogues were divided into three groups of 7 DAs (D3), 33 SAs (5-HT 2A/2C), and 46 SDAs (D3 and 5-HT2A/2C). A classification model was generated for identifying structural characteristics of those antagonists with different affinity profiles. On the basis of the results from our previous study, we conducted the generation of the decision trees by the recursive-partitioning (RP) method using Cerius2 2D descriptors, and identified and interpreted the descriptors that discriminate in-house antipsychotic compounds.

Original languageEnglish
Pages (from-to)111-116
Number of pages6
JournalBulletin of the Korean Chemical Society
Volume29
Issue number1
DOIs
Publication statusPublished - 2008 Jan 20

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All Science Journal Classification (ASJC) codes

  • Chemistry(all)

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