Small molecules, big targets: drug discovery faces the protein–protein interaction challenge
By D. Scott, Andrew R. Bayly, Chris Abell, J. Skidmore. Nature reviews. Drug discovery, 2016
971 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology, Organic Chemistry
View Paper: https://www.semanticscholar.org/paper/4f365d6b281136c505605d2f5d73bd143306d5a0
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In Computational Theory and Mathematics
In Molecular Biology
Citations in the corpus
- Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials (2020, background): “Tryptophan, arginine, and tyrosine are more likely to appear in hot-spots than other amino acids.(15,30) Because of the important role of these “hot-spots” amino acids, they are often used to design PPI drugs.”
- Deep learning in bioinformatics: introduction, application, and perspective in big data era (2019, background): “Understanding protein-protein interaction can be helpful for predicting the functionality of uncharacterized proteins and designing drugs [136, 130].”
- Recent advances in Alzheimer’s disease: mechanisms, clinical trials and new drug development strategies (2024, background): “591 Additionally, another Keap1-Nrf2 PPI inhibitor 74 , which combined conformational features signi fi cantly similar to the Keap1-Nrf2 ETGE complex, revealed the unique inhibition mechanism and provided an innovative strategy for the development of new Keap1-Nrf2 PPI inhibitors.”