In Silico Models of Biological Activities of Peptides Using the Coefficient of Conformism of a Correlative Prediction and the Las Vegas Algorithm

• Published in: Macromol Vol. 5; no. 2; p. 27
• Main Authors: Toropova, Alla P., Toropov, Andrey A., Roncaglioni, Alessandra, Benfenati, Emilio
• Format: Journal Article
• Language: English
• Published: Madrid MDPI AG 13.06.2025
• Subjects: ACE-inhibitory activity; Algorithms; Amino acids; antioxidant activity; Artificial intelligence; Biological activity; Calibration; Conformity; Mathematical functions; Molecular structure; Monte Carlo method; Optimization; Peptides; QSAR; quasi-SMILES; Symmetry; United States > US; Las Vegas Nevada
• ISSN: 2673-6209; 2673-6209
• DOI: 10.3390/macromol5020027

Peptides are substances with numerous applications in chemistry, biology, medicine, and agriculture. Systematization of knowledge related to peptides may well have not only scientific research but also economic consequences. This study examines the antioxidant activity of peptides and the ACE-inhibitory capacity of peptides. Peptides are considered here containing three or four amino acids. Nevertheless, instead of considering peptides as traditional molecules, an attempt is made here to systematize the corresponding endpoints as mathematical functions of lists of amino acids, rather than considering the corresponding atoms and covalent bonds. New techniques that may be useful in theory and in practice for the development of quantitative structure–property/activity relationships (QSPRs/QSARs) related to certain types of biological activity of peptides are proposed and discussed.