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Expert Opin Drug Discov. 2018 Apr;13(4):327-338. doi: 10.1080/17460441.2018.1430763. Epub 2018 Jan 29.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

Author information

1
a Department of Life Sciences , Barcelona Supercomputing Center (BSC) , Barcelona , Spain.
2
b Structural Biology Unit , Institut de Biologia Molecular de Barcelona (IBMB), CSIC , Barcelona , Spain.

Abstract

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

KEYWORDS:

Protein-protein interactions; computational docking; drug discovery; interface hot-spot residues

PMID:
29376444
DOI:
10.1080/17460441.2018.1430763
[Indexed for MEDLINE]

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