J Chem Inf Model - Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor.

Tópicos

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Resumo

Ligand-based approaches are particularly important in the hit identification process of drug discovery when no structural information on the target is available. Pharmacophore descriptors that use a topological representation of the ligands are usually fast enough to screen large compound libraries effectively when seeking novel lead candidates. One example of this kind is the Feature Tree descriptor, a reduced graph representation implemented in the FTrees software. In this study, we tested the screening efficiency of FTrees by both retrospective and prospective screens using known histamine H4 antagonists and serotonin transporter (SERT) inhibitors as query molecules. Our results demonstrate that FTrees can effectively find actives. Particularly when combined with a subsequent 2D fingerprint-based diversity selection, FTrees was found to be extremely effective at discovering a diverse set of scaffolds. Prospective screening of our in-house compound deck provided several novel H4 and SERT ligands that could serve as suitable starting points for further optimization.

Resumo Limpo

ligandbas approach particular import hit identif process drug discoveri structur inform target avail pharmacophor descriptor use topolog represent ligand usual fast enough screen larg compound librari effect seek novel lead candid one exampl kind featur tree descriptor reduc graph represent implement ftree softwar studi test screen effici ftree retrospect prospect screen use known histamin h antagonist serotonin transport sert inhibitor queri molecul result demonstr ftree can effect find activ particular combin subsequ d fingerprintbas divers select ftree found extrem effect discov divers set scaffold prospect screen inhous compound deck provid sever novel h sert ligand serv suitabl start point optim

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