Artificial Intelligence for Peptide Stability Prediction and Peptide Modifi-cation Strategies
Peptides are a class of molecules whose molecular size is between small molecules and proteins,and which have a unique drug-like space.Peptides have the advantages of high selectivity and low immunogenicity.However,the primary and advanced struc-tures of peptides are easily destroyed,leading to easy degradation of peptides in vivo with short half-life and low bioavailability.Pep-tide instability restricts its druggability.Backbone modification and motif modification of peptides prolong half-life.Peptide stability prediction based on artificial intelligence can accelerate the development process of peptide formulations,which has the potential to shake the paradigm of peptide drug development.Because of the richness of the influencing factors of peptide stability,the concepts of structural stability,metabolic stability,and thermodynamic stability of peptides were introduced,and the wet experimental metrics that could be used as machine learning labels was summarized.Recent peptide stability prediction studies cover both in vitro and in vivo stability of peptides.Accordingly,the advances in the prediction of peptide formulation stability,peptide in vitro stability,peptide gastrointestinal stability,and PK parameters of insulin analogs were presented.Common methods to improve the stability of peptides were summarized.
peptide stabilitycomputer aided drug designpeptide modificationinsulin analoguemachine learningdeep learning
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