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Meta-models for predicting blood brain barrier penetration based on physicochemical descriptors, like h-bond donors/acceptors and partition coefficients
Meta-models for predicting blood brain barrier penetration based on physicochemical descriptors, like h-bond donors/acceptors and partition coefficients
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机译：基于理化描述符（例如，h键供体/受体和分配系数）预测血脑屏障渗透的元模型
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摘要
Descriptor based models, employing at least two descriptors, predict activities of compounds under consideration. Those activities may be biology-based activities such as the ability of the compound to cross the blood brain barrier. In one example, the model predicts a compound's solubility, its ability to be absorbed in the intestine, and its ability to cross the blood brain barrier. The descriptors of interest are typically physicochemical properties of the whole molecule. Examples include a log P or log D, molecular weight or related size-based descriptors, the number of hydrogen bond donors and/or hydrogen bond acceptors, formal charge, lipophilicity, and the like.
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