J Chem Inf Model - Compound set enrichment: a novel approach to analysis of primary HTS data.

Tópicos

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Resumo

The main goal of high-throughput screening (HTS) is to identify active chemical series rather than just individual active compounds. In light of this goal, a new method (called compound set enrichment) to identify active chemical series from primary screening data is proposed. The method employs the scaffold tree compound classification in conjunction with the Kolmogorov-Smirnov statistic to assess the overall activity of a compound scaffold. The application of this method to seven PubChem data sets (containing between 9389 and 263679 molecules) is presented, and the ability of this method to identify compound classes with only weakly active compounds (potentially latent hits) is demonstrated. The analysis presented here shows how methods based on an activity cutoff can distort activity information, leading to the incorrect activity assignment of compound series. These results suggest that this method might have utility in the rational selection of active classes of compounds (and not just individual active compounds) for followup and validation.

Resumo Limpo

main goal highthroughput screen hts identifi activ chemic seri rather just individu activ compound light goal new method call compound set enrich identifi activ chemic seri primari screen data propos method employ scaffold tree compound classif conjunct kolmogorovsmirnov statist assess overal activ compound scaffold applic method seven pubchem data set contain molecul present abil method identifi compound class weak activ compound potenti latent hit demonstr analysi present show method base activ cutoff can distort activ inform lead incorrect activ assign compound seri result suggest method might util ration select activ class compound just individu activ compound followup valid

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