The DOI matches its Crossref record; 118 of the 118 references it cites were found in a registry or an index.
Hot-spot analysis for drug discovery targeting protein-protein interactions
Open accessAbstract
INTRODUCTION: 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.
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“However, abnormalities in PPIs can result in a various diseases, such as cancers, infectious diseases, and neurodegenerative diseases.306–308”
From Recent advances in targeting the “undruggable” proteins: from drug discovery to clinical trials (2023) · cites this paper as [308]
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Metadata
- Authors
- Rosell, M., & Fernández-Recio, J.
- Affiliations
- Barcelona Supercomputing Center (ES)
- Department of Life Sciences, Barcelona Supercomputing Center (BSC), Barcelona, Spain
- ORCID
- Rosell, Mireia
- Venue
- Expert Opinion on Drug Discovery
- Publisher
- Informa UK Limited
- Published
- 2018-01-29
- Volume
- 13
- Issue
- 4
- Pages
- 327-338
- ISSN
- 1746-0441 (ISSN-L)
- 1746-045X
- OpenAlex
- W2791454012
- Cited by
- 105
- References
- 118
- Citations by year
- 2026: 6 · 2025: 15 · 2024: 19 · 2023: 19 · 2022: 12 · 2021: 9 · 2020: 16 · 2019: 8 · 2018: 1
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- Locations
- Expert Opinion on Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (acceptedVersion, other-oa)
- UPCommons institutional repository (Universitat Politècnica de Catalunya) (acceptedVersion, other-oa)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
- RECERCAT (Consorci de Serveis Universitaris de Catalunya) (submittedVersion, public-domain)
- Funders
- the Spanish Ministry of Economy, Industry and Competitiveness (EFA086/15)
- EU Interreg V POCTEFA
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- protein-protein interaction, hot spot residues, protein-protein interfaces, small molecule inhibitors, rational drug design, molecular docking, molecular dynamics, mutation analysis
- MeSH terms
- Humans, Models, Molecular, Proteins, Drug Design, Computational Biology, Drug Discovery, Molecular Dynamics Simulation, Molecular Docking Simulation
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