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- W2952651853 abstract "The activity of a biological compound is dependent both on specific binding to a target receptor and its ADME (Absorption, Distribution, Metabolism, Excretion) properties. A challenge to predict biological activity is to consider both contributions simultaneously in deriving quantitative models. We present a novel approach to derive QSAR models combining similarity analysis of molecular interaction fields (MIFs) with prediction of logP and/or logD. This new classification method is applied to a set of about 100 compounds related to the auxin plant hormone. The classification based on similarity of their interaction fields is more successful for the indole than the phenoxy compounds. The classification of the phenoxy compounds is however improved by taking into account the influence of the logP and/or the logD values on biological activity. With the new combined method, the majority (8 out of 10) of the previously misclassified derivatives of phenoxy acetic acid are classified in accord with their bioassays. The recently determined crystal structure of the auxin-binding protein 1 (ABP1) enabled validation of our approach. The results of docking a few auxin related compounds with different biological activity to ABP1 correlate well with the classification based on similarity of MIFs only. Biological activity is, however, better predicted by a combined similarity of MIFs + logP/logD approach." @default.
- W2952651853 created "2019-06-27" @default.
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- W2952651853 date "2003-08-05" @default.
- W2952651853 modified "2023-10-14" @default.
- W2952651853 title "A New Approach To Predict the Biological Activity of Molecules Based on Similarity of Their Interaction Fields and the log<i>P</i> and log<i>D</i> Values: Application to Auxins" @default.
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- W2952651853 doi "https://doi.org/10.1021/ci034063n" @default.
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