ALLO: A tool to discriminate and prioritize allosteric pockets,Chemical Biology & Drug Design

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ALLO: A tool to discriminate and prioritize allosteric pockets
Chemical Biology & Drug Design ( IF 3.2 ) Pub Date : 2018-01-19 , DOI: 10.1111/cbdd.13161
Rahmad Akbar ₁ , Volkhard Helms ₁

Affiliation

Allosteric proteins make up a substantial proportion of human drug targets. Thus, rational design of small molecule binders that target these proteins requires the identification of putative allosteric pockets and an understanding of their potential activity. Here, we characterized allosteric pockets using a set of physicochemical descriptors and compared them to pockets that are found on the surface of a protein. Further, we trained predictive models capable of discriminating allosteric pockets from orthosteric pockets and models capable of prioritizing allosteric pockets in a set of pockets found on a given protein. Such models might be useful for identifying novel allosteric sites and in turn, potentially new allosteric drug targets. Datasets along with a Python program encapsulating the predictive models are available at http://github.com/fibonaccirabbits/allo.

中文翻译：

ALLO：区分和确定变构口袋优先级的工具

变构蛋白质占人类药物靶标的很大比例。因此，针对这些蛋白的小分子结合剂的合理设计需要鉴定假定的变构口袋并了解其潜在活性。在这里，我们使用一组理化描述符来表征变构袋，并将它们与蛋白质表面上的袋进行比较。此外，我们训练了能够区分正构口袋和正构口袋的预测模型，以及能够对给定蛋白质上的一组口袋中的变构口袋进行优先排序的模型。这样的模型可能对于识别新的变构位点以及反过来可能潜在的新的变构药物靶标很有用。数据集以及封装了预测模型的Python程序可在http://github.com上获得。

更新日期：2018-01-19

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