2025/11/02 by Ndenga, Barack
paper · doi:10.60763/africarxiv/10242
This work introduces AI-Optimized Photon-Assisted Molecular Docking (PAMD), a groundbreaking paradigm that merges photonic computation with deep reinforcement learning for ultra-fast and highly accurate ligand–receptor docking. By leveraging controlled photon interference patterns, the model generates dynamic docking probability fields that are continuously optimized by neural feedback loops, reducing computational time up to 100× compared to classical algorithms. This photonic–AI synergy enables real-time, scalable, and energy-efficient molecular docking, setting a new foundation for next-generation drug discovery. Benchmarking against AutoDock Vina and AlphaFold-Dock demonstrates superior accuracy and speed, while drastically lowering energy consumption by 85%. PAMD represents a transformative step toward light-speed bioinformatics, bridging quantum physics, AI, and molecular medicine.