AI Research
QFoldAgent: An Autonomous Quantum Optimization Multi-Agent System for Protein Structure Prediction
Hybrid quantum-classical protein structure prediction depends strongly on Hamiltonian penalty weights, yet existing lattice-based workflows typically fix these coefficients by hand and evaluate only very short fragments in simulation. We present QFoldAgent, a closed-loop multi-ag...
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ArXiv CS.AI
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ArXiv CS.AI
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This research introduces an autonomous multi-agent system for protein structure prediction, showcasing how AI can iteratively refine quantum optimization parameters. The QFoldAgent framework demonstrates a promising approach to overcoming limitations in current quantum-classical protein folding workflows by learning optimal Hamiltonian penalty weights.
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