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Chem Commun (Camb). 2017 Aug 17;53(67):9372-9375. doi: 10.1039/c7cc05379g.

Computationally-guided optimization of small-molecule inhibitors of the Aurora A kinase-TPX2 protein-protein interaction.

Author information

1
Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, USA and School of Chemistry, Newcastle University, Newcastle upon Tyne NE1 7RU, UK. daniel.cole@ncl.ac.uk.
2
MRC Cancer Unit, University of Cambridge, Hills Road, Cambridge CB2 0XZ, UK and Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
3
Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
4
Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Old Addenbrooke's Site, Cambridge CB2 1GA, UK.
5
Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, USA.
6
MRC Cancer Unit, University of Cambridge, Hills Road, Cambridge CB2 0XZ, UK.
7
MRC Cancer Unit, University of Cambridge, Hills Road, Cambridge CB2 0XZ, UK and Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK and Theory of Condensed Matter Group, Cavendish Laboratory, 19 JJ Thomson Avenue, Cambridge CB3 0HE, UK.

Abstract

Free energy perturbation theory, in combination with enhanced sampling of protein-ligand binding modes, is evaluated in the context of fragment-based drug design, and used to design two new small-molecule inhibitors of the Aurora A kinase-TPX2 protein-protein interaction.

PMID:
28787041
PMCID:
PMC5591577
DOI:
10.1039/c7cc05379g
[Indexed for MEDLINE]
Free PMC Article

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