Reduced-Alphabet QUBO/Ising Formulation for Constraint-Driven Cyclic Peptide Sequence Design

Cyclic peptide design requires balancing local residue preferences with constraints from ring-forming chemistry, residue spacing, topology, target compatibility, and developability. Here, we present a reduced-alphabet quadratic unconstrained binary optimization (QUBO)/Ising formulation for constraint-driven cyclic peptide sequence design. Amino acids are grouped into physicochemical or interaction-based residue classes, and peptide positions are represented by binary residue-class assignment variables. The objective combines one-hot sequence validity, cyclization constraints, optional target-compatibility terms, motif and composition rules, and coarse developability proxies. By modifying the relevant constraint terms, the same framework can represent head-to-tail, disulfide-bridged, stapled, and bicyclic peptide designs. A resource-aware eight-class alphabet motivated by MJ interaction-profile clustering is used as a default representation to balance coarse interaction-pattern preservation with encoding cost. The resulting QUBO/Ising objective is solver-agnostic and can be explored using classical or quantum-compatible binary optimization procedures. The model is intended as an early-stage search-space reduction and prioritization layer: it produces low-energy residue-class sequences rather than final molecular candidates, which require amino-acid decoding, cyclization-aware construction, and downstream structural or experimental validation.

Source: arXiv:2606.23253v1 - http://arxiv.org/abs/2606.23253v1 PDF: https://arxiv.org/pdf/2606.23253v1 Original Link: http://arxiv.org/abs/2606.23253v1