J Chem Inf Model - SAR monitoring of evolving compound data sets using activity landscapes.

Tópicos

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{ data(1737) use(1416) pattern(1282) }
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{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

In pharmaceutical research, collections of active compounds directed against specific therapeutic targets usually evolve over time. Small molecule discovery is an iterative process. New compounds are discovered, alternative compound series explored, some series discontinued, and others prioritized. The design of new compounds usually takes into consideration prior chemical and structure-activity relationship (SAR) knowledge. Hence, historically grown compound collections represent a viable source of chemical and SAR information that might be utilized to retrospectively analyze roadblocks in compound optimization and further guide discovery projects. However, SAR analysis of large and heterogeneous sets of active compounds is also principally complicated. We have subjected evolving compound data sets to SAR monitoring using activity landscape models in order to evaluate how composition and SAR characteristics might change over time. Chemotype and potency distributions in evolving data sets directed against different therapeutic targets were analyzed and alternative activity landscape representations generated at different points in time to monitor the progression of global and local SAR features. Our results show that the evolving data sets studied here have predominantly grown around seed clusters of active compounds that often emerged early on, while other SAR islands remained largely unexplored. Moreover, increasing scaffold diversity in evolving data sets did not necessarily yield new SAR patterns, indicating a rather significant influence of "me-too-ism" (i.e., introducing new chemotypes that are similar to already known ones) on the composition and SAR information content of the data sets.

Resumo Limpo

pharmaceut research collect activ compound direct specif therapeut target usual evolv time small molecul discoveri iter process new compound discov altern compound seri explor seri discontinu other priorit design new compound usual take consider prior chemic structureact relationship sar knowledg henc histor grown compound collect repres viabl sourc chemic sar inform might util retrospect analyz roadblock compound optim guid discoveri project howev sar analysi larg heterogen set activ compound also princip complic subject evolv compound data set sar monitor use activ landscap model order evalu composit sar characterist might chang time chemotyp potenc distribut evolv data set direct differ therapeut target analyz altern activ landscap represent generat differ point time monitor progress global local sar featur result show evolv data set studi predomin grown around seed cluster activ compound often emerg earli sar island remain larg unexplor moreov increas scaffold divers evolv data set necessarili yield new sar pattern indic rather signific influenc metooism ie introduc new chemotyp similar alreadi known one composit sar inform content data set

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