Environment-Conditioned Design of α-Helical Peptides.
- 1Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, Santiago de CompostelaE-15782, Spain.
- 2Organic Chemistry Department, Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares (CiQUS), Universidade de Santiago de Compostela, Campus Vida s/n, Santiago de CompostelaE-15782, Spain.
Abstract
Peptides at biological interfaces often encode function through preferential compatibility with chemical environments rather than through binding to a single molecular target. We report a physically motivated, knowledge-based Hamiltonian for programming such preferences in α-helical peptides. The model maps amino-acid sequences onto a normalized energy landscape that combines helix propensity, local sequence context, residue contacts, solvent exposure, membrane charge coupling, and electrostatic screening. Random-reference Z-scores place different lengths, residue sets, and environments on a common scale. In homogeneous benchmarks, the Hamiltonian separates experimentally characterized alanine-rich Glu/Lys water-soluble helices from WALP/GWALP transmembrane model helices. In interfacial benchmarks, it recognizes canonical membrane-active antimicrobial peptides as preferentially stabilized at anionic interfaces over neutral, cationic, aqueous, and apolar alternatives, while rejecting non-antimicrobial helical controls. The same score generates sequence libraries for environment-specific compatibility, polar-apolar robustness, and one-vs-rest anionic selectivity. Low-energy ensembles display amphipathic segregation, charge regulation, and hydrophobicity periodicity at sequence separations of 3 and 4 residues, linking the designed sequences to interpretable chemical organization. Because the objective is a discrete Hamiltonian, it can be explored by exact search, classical heuristics, and binary-encoded quantum-compatible workflows without changing the scoring function. This framework provides a transparent route to design α-helical peptides whose environmental preferences are specified directly in the molecular objective.
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BibTeX
@article{condetorres2026environmentconditioned,
title = {{Environment-Conditioned Design of α-Helical Peptides.}},
author = {Daniel Conde-Torres and Rebeca García-Fandiño and Ángel Piñeiro},
journal = {Journal of chemical theory and computation},
year = {2026},
month = sep,
doi = {10.1021/acs.jctc.6c01278},
url = {https://europepmc.org/article/MED/42917473},
note = {CC BY},
}
RIS
TY - JOUR
TI - Environment-Conditioned Design of α-Helical Peptides.
AU - Daniel Conde-Torres
AU - Rebeca García-Fandiño
AU - Ángel Piñeiro
PY - 2026
DA - 2026/09/01
JO - Journal of chemical theory and computation
DO - 10.1021/acs.jctc.6c01278
UR - https://europepmc.org/article/MED/42917473
AB - Peptides at biological interfaces often encode function through preferential compatibility with chemical environments rather than through binding to a single molecular target. We report a physically motivated, knowledge-based Hamiltonian for programming such preferences in α-helical peptides. The model maps amino-acid sequences onto a normalized energy landscape that combines helix propensity, local sequence context, residue contacts, solvent exposure, membrane charge coupling, and electrostatic screening. Random-reference Z-scores place different lengths, residue sets, and environments on a common scale. In homogeneous benchmarks, the Hamiltonian separates experimentally characterized alanine-rich Glu/Lys water-soluble helices from WALP/GWALP transmembrane model helices. In interfacial benchmarks, it recognizes canonical membrane-active antimicrobial peptides as preferentially stabilized at anionic interfaces over neutral, cationic, aqueous, and apolar alternatives, while rejecting non-antimicrobial helical controls. The same score generates sequence libraries for environment-specific compatibility, polar-apolar robustness, and one-vs-rest anionic selectivity. Low-energy ensembles display amphipathic segregation, charge regulation, and hydrophobicity periodicity at sequence separations of 3 and 4 residues, linking the designed sequences to interpretable chemical organization. Because the objective is a discrete Hamiltonian, it can be explored by exact search, classical heuristics, and binary-encoded quantum-compatible workflows without changing the scoring function. This framework provides a transparent route to design α-helical peptides whose environmental preferences are specified directly in the molecular objective.
SN - 1549-9618
SN - 1549-9626
ER -