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Updated: Feb 10, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Computational design of heterochiral peptides against a helical target
Vikas Nanda1, William F DeGrado
1Department of Biochemistry, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, Piscataway, New Jersey 08854, USA. nanda@cabm.rutgers.edu
Abstract:
Polypeptides incorporating D-amino acids occasionally occur in nature and are an important class of pharmaceutical molecules. With the use of heterochiral Monte Carlo (HCMC), a method inspired by the de novo design of proteins, we develop peptide scaffolds for interacting with a molecular target, a left-handed alpha-helix. The HCMC approach concurrently seeks to optimize a peptide sequence, its internal conformation, and its docked conformation with a target surface. Several major classes of interactions are observed: (1) homochiral interactions between two alphaL helices, (2) heterochiral interactions between an alphaL and an alphaR helix, and (3) heterochiral interactions between the alphaL target and novel nonhelical structures. We explore the application of HCMC to simulating the preferential enantioselectivity of heterochiral complexes. Implications for biomimetic design in molecular recognition are discussed.
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