Please use this identifier to cite or link to this item: doi:10.22028/D291-30514
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Title: ALLO: A tool to discriminate and prioritize allosteric pockets
Author(s): Akbar, Rahmad
Helms, Volkhard
Language: English
Title: Chemical biology & drug design
Volume: 91
Issue: 4
Startpage: 845
Endpage: 853
Publisher/Platform: Blackwell Munksgaard
Year of Publication: 2018
Publikation type: Journal Article
Abstract: 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.
DOI of the first publication: 10.1111/cbdd.13161
URL of the first publication: https://onlinelibrary.wiley.com/doi/full/10.1111/cbdd.13161
Link to this record: hdl:20.500.11880/28891
http://dx.doi.org/10.22028/D291-30514
ISSN: 1747-0277
1747-0285
Date of registration: 20-Mar-2020
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Biowissenschaften
Professorship: NT - Prof. Dr. Volkhard Helms
Collections:UniBib – Die Universitätsbibliographie

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