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Curr Drug Targets. 2017;18(9):1104-1111. doi: 10.2174/1389450118666161116130155.

Understanding the Structural Basis for Inhibition of Cyclin-Dependent Kinases. New Pieces in the Molecular Puzzle.

Author information

1
Laboratory of Computational Systems Biology, Faculty of Biosciences - Pontifical Catholic University of Rio Grande do Sul (PUCRS), Av. Ipiranga, 6681, Porto Alegre-RS 90619-900, Brazil.
2
Graduate Program in Cellular and Molecular Biology, Faculty of Biosciences, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Av. Ipiranga, 6681. Porto Alegre-RS 90619-900, Brazil.

Abstract

BACKGROUND:

Cyclin-dependent kinases (CDKs) comprise an important protein family for development of drugs, mostly aimed for use in treatment of cancer but there is also potential for development of drugs for neurodegenerative diseases and diabetes. Since the early 1990s, structural studies have been carried out on CDKs, in order to determine the structural basis for inhibition of this protein target.

OBJECTIVE:

Our goal here is to review recent structural studies focused on CDKs. We concentrate on latest developments in the understanding of the structural basis for inhibition of CDKs, relating structures and ligand-binding information.

METHOD:

Protein crystallography has been successfully applied to elucidate over 400 CDK structures. Most of these structures are complexed with inhibitors. We use this richness of structural information to describe the major structural features determining the inhibition of this enzyme.

RESULTS:

Structures of CDK1, 2, 4-9, 12 13, and 16 have been elucidated. Analysis of these structures in complex with a wide range of different competitive inhibitors, strongly indicate some common features that can be used to guide the development of CDK inhibitors, such as a pattern of hydrogen bonding and the presence of halogen atoms in the ligand structure.

CONCLUSION:

Nowadays we have structural information for hundreds of CDKs. Combining the structural and functional information we may say that a pattern of intermolecular hydrogen bonds is of pivotal importance for inhibitor specificity. In addition, machine learning techniques have shown improvements in predicting binding affinity for CDKs.

KEYWORDS:

Cyclin-dependent kinase; binding affinity; drug design; inhibitors; machine learning; neurodegenerative disease

[Indexed for MEDLINE]

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