J Chem Inf Model - Hit expansion approaches using multiple similarity methods and virtualized query structures.

Tópicos

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Resumo

Ligand-based virtual screening and computational hit expansion methods undoubtedly facilitate the finding of novel active chemical entities, utilizing already existing knowledge of active compounds. It has been demonstrated that the parallel execution of complementary similarity search methods enhances the performance of such virtual screening campaigns. In this article, we examine the use of virtualized template (query, seed) structures as an extension to common search methods, such as fingerprint and pharmacophore graph-based similarity searches. We demonstrate that template virtualization by bioisosteric enumeration and other rule-based methods, in combination with standard similarity search techniques, represents a powerful approach for hit expansion following high-throughput screening campaigns. The reliability of the methods is demonstrated by four different test data sets representing different target classes and two hit finding case studies on the epigenetic targets G9a and LSD1.

Resumo Limpo

ligandbas virtual screen comput hit expans method undoubt facilit find novel activ chemic entiti util alreadi exist knowledg activ compound demonstr parallel execut complementari similar search method enhanc perform virtual screen campaign articl examin use virtual templat queri seed structur extens common search method fingerprint pharmacophor graphbas similar search demonstr templat virtual bioisoster enumer rulebas method combin standard similar search techniqu repres power approach hit expans follow highthroughput screen campaign reliabl method demonstr four differ test data set repres differ target class two hit find case studi epigenet target ga lsd

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