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- W2800677598 abstract "Peptides have recently attracted much attention as promising drug candidates. Rational design of peptide-derived therapeutics usually requires structural characterization of the underlying protein-peptide interaction. Given that experimental characterization can be difficult, reliable computational tools are needed. In recent years, a variety of approaches have been developed for 'protein-peptide docking', that is, predicting the structure of the protein-peptide complex, starting from the protein structure and the peptide sequence, including variable degrees of information about the peptide binding site and/or conformation. In this review, we provide an overview of protein-peptide docking methods and outline their capabilities, limitations, and applications in structure-based drug design. Key challenges are also briefly discussed, such as modeling of large-scale conformational changes upon binding, scoring of predicted models, and optimal inclusion of varied types of experimental data and theoretical predictions into an integrative modeling process." @default.
- W2800677598 created "2018-05-17" @default.
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- W2800677598 date "2018-08-01" @default.
- W2800677598 modified "2023-10-12" @default.
- W2800677598 title "Protein–peptide docking: opportunities and challenges" @default.
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- W2800677598 doi "https://doi.org/10.1016/j.drudis.2018.05.006" @default.
- W2800677598 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29733895" @default.
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