J Chem Inf Model - Virtual fragment screening: discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints.

Tópicos

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Resumo

Virtual fragment screening (VFS) is a promising new method that uses computer models to identify small, fragment-like biologically active molecules as useful starting points for fragment-based drug discovery (FBDD). Training sets of true active and inactive fragment-like molecules to construct and validate target customized VFS methods are however lacking. We have for the first time explored the possibilities and challenges of VFS using molecular fingerprints derived from a unique set of fragment affinity data for the histamine H(3) receptor (H(3)R), a pharmaceutically relevant G protein-coupled receptor (GPCR). Optimized FLAP (Fingerprints of Ligands and Proteins) models containing essential molecular interaction fields that discriminate known H(3)R binders from inactive molecules were successfully used for the identification of new H(3)R ligands. Prospective virtual screening of 156,090 molecules yielded a high hit rate of 62% (18 of the 29 tested) experimentally confirmed novel fragment-like H(3)R ligands that offer new potential starting points for the design of H(3)R targeting drugs. The first construction and application of customized FLAP models for the discovery of fragment-like biologically active molecules demonstrates that VFS is an efficient way to explore protein-fragment interaction space in silico.

Resumo Limpo

virtual fragment screen vfs promis new method use comput model identifi small fragmentlik biolog activ molecul use start point fragmentbas drug discoveri fbdd train set true activ inact fragmentlik molecul construct valid target custom vfs method howev lack first time explor possibl challeng vfs use molecular fingerprint deriv uniqu set fragment affin data histamin h receptor hr pharmaceut relev g proteincoupl receptor gpcr optim flap fingerprint ligand protein model contain essenti molecular interact field discrimin known hr binder inact molecul success use identif new hr ligand prospect virtual screen molecul yield high hit rate test experiment confirm novel fragmentlik hr ligand offer new potenti start point design hr target drug first construct applic custom flap model discoveri fragmentlik biolog activ molecul demonstr vfs effici way explor proteinfrag interact space silico

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