J Chem Inf Model - inSARa: intuitive and interactive SAR interpretation by reduced graphs and hierarchical MCS-based network navigation.

Tópicos

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{ method(2212) result(1239) propos(1039) }

Resumo

The analysis of Structure-Activity-Relationships (SAR) of small molecules is a fundamental task in drug discovery. Although a large number of methods are already published, there is still a strong need for novel intuitive approaches. The inSARa (intuitive networks for Structure-Activity Relationships analysis) method introduced herein takes advantage of the synergistic combination of reduced graphs (RG) and the intuitive maximum common substructure (MCS) concept. The main feature of the inSARa concept is a hierarchical network structure of clearly defined substructure relationships based on common pharmacophoric features. Thus, straightforward SAR interpretation is possible by interactive network navigation. When focusing on a set of active molecules at one single target, the resulting inSARa networks are shown to be valuable for various essential tasks in SAR analysis, such as the identification of activity cliffs or "activity switches", bioisosteric exchanges, common pharmacophoric features, or "SAR hotspots".

Resumo Limpo

analysi structureactivityrelationship sar small molecul fundament task drug discoveri although larg number method alreadi publish still strong need novel intuit approach insara intuit network structureact relationship analysi method introduc herein take advantag synergist combin reduc graph rg intuit maximum common substructur mcs concept main featur insara concept hierarch network structur clear defin substructur relationship base common pharmacophor featur thus straightforward sar interpret possibl interact network navig focus set activ molecul one singl target result insara network shown valuabl various essenti task sar analysi identif activ cliff activ switch bioisoster exchang common pharmacophor featur sar hotspot

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