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Orally bioavailable, high molecular weight macrocyclic peptides that inhibit difficult-to-drug protein–protein interactions are of high therapeutic value, and rules for their design were proposed recently. Here, we emphasize the danger of rules that provide a false impression of the lipophilicity required of a clinical candidate.
Computational methods for calculating a protein structure from a given amino acid sequence have revolutionized both our understanding of structural biology and the prediction of protein-binding compounds. This issue features several pieces that explore machine learning approaches for protein structure prediction, benchmarking and evaluation of model quality, and how machine learning algorithms can be used in the drug discovery process.
