Quadratic unconstrained binary optimization and constraint programming approaches for lattice-based cyclic peptide docking.

ABSTRACT: The peptide-protein docking problem is an important problem in structural biology that facilitates rational and efficient drug design. In this work, we explore modeling and solving this problem with the quantum-amenable quadratic unconstrained binary optimization (QUBO) formalism. Our work extends recent efforts by incorporating the objectives and constraints associated with peptide cyclization and peptide-protein docking in the two-particle model on a tetrahedral lattice. We propose a "resource efficient" QUBO encoding for this problem, and baseline its performance with a novel constraint programming (CP) approach. We implement an end-to-end framework that enables the evaluation of our methods on instances from the Protein Data Bank (PDB). Our results show that the QUBO approach, using a

SUBMITTER: Brubaker JK 

PROVIDER: S-EPMC12214603 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature