J Chem Inf Model - Capturing structure-activity relationships from chemogenomic spaces.

Tópicos

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{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Modeling off-target effects is one major goal of chemical biology, particularly in its applications to drug discovery. Here, we describe a new approach that allows the extraction of structure-activity relationships from large chemogenomic spaces starting from a single chemical structure. Several public source databases, offering a vast amount of data on structure and activity for a large number of different targets, have been investigated for their usefulness in automated structure-activity relationships (SAR) extraction. SAR tables were constructed by assembling similar structures around each query structure that have an activity record for a particular target. Quantitative series enrichment analysis (QSEA) was applied to these SAR tables to identify trends and to transform these trends into topomer CoMFA models. Overall more than 1700 SAR tables with topomer CoMFA models have been obtained from the ChEMBL, PubChem, and ChemBank databases. These models were able to highlight the structural trends associated with various off-target effects of marketed drugs, including cases where other structural similarity metrics would not have detected an off-target effect. These results indicate the usefulness of the QSEA approach, particularly whenever applicable with public databases, in providing a new means, beyond a simple similarity between ligand structures, to capture SAR trends and thereby contribute to success in drug discovery.

Resumo Limpo

model offtarget effect one major goal chemic biolog particular applic drug discoveri describ new approach allow extract structureact relationship larg chemogenom space start singl chemic structur sever public sourc databas offer vast amount data structur activ larg number differ target investig use autom structureact relationship sar extract sar tabl construct assembl similar structur around queri structur activ record particular target quantit seri enrich analysi qsea appli sar tabl identifi trend transform trend topom comfa model overal sar tabl topom comfa model obtain chembl pubchem chembank databas model abl highlight structur trend associ various offtarget effect market drug includ case structur similar metric detect offtarget effect result indic use qsea approach particular whenev applic public databas provid new mean beyond simpl similar ligand structur captur sar trend therebi contribut success drug discoveri

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