Photonics + AI for Real-Time Molecular Interaction Mapping - Barack Ndenga (Publisher, 2025)
This paper introduces a breakthrough in molecular biophysics through the integration of photonics and artificial intelligence for real-time mapping of molecular interactions. The proposed system, AI-driven photonic interaction mapping (AI-PIM), enables the detection, interpretation, and visualization of biochemical interactions as they occur — translating photonic interference signals into dynamic molecular information. This work extends the continuum of research developed across the author’s previous publications (from the 19ᵗʰ to the 26ᵗʰ), which progressively established the AI–Photonics framework as a unified scientific paradigm. Earlier studies explored photonic computation, energy–information coupling, and AI-optimized docking; this current paper represents their synthesis into a functional real-time molecular monitoring system. By merging light-based quantum sensing with deep neural inference, AI-PIM reveals how photon interference encodes the subtleties of binding affinities, conformational transitions, and energy–information exchanges between biomolecules. This allows for molecular visualization not as static configurations, but as living processes evolving in time and energy space. The model thus transforms molecular bioinformatics into an active, adaptive, and photonic discipline — capable of observing biochemical causality at the speed of light. This research inaugurates a new scientific direction termed Dynamic Quantum Bioinformatics, establishing the foundation for next-generation diagnostics, drug discovery, and bioenergetic computation. Keywords: photonics, artificial intelligence, molecular interaction, quantum biology, real-time bioinformatics, photon interference, biocomputation, energy-information dynamics, AI-photon coupling, dynamic molecular visualization
This 28ᵗʰ scientific contribution presents Photon–AI Real-Time Molecular Mapping, a revolutionary framework integrating photonics and artificial intelligence for dynamic observation of molecular interactions. Unlike conventional static models, this system decodes photon interference patterns to reveal binding events, energy transfer, and conformational changes in real time, achieving microsecond-level resolution. By combining coherent light acquisition, AI-driven signal interpretation, and 3D spatiotemporal mapping, the platform enables unprecedented visualization of biomolecular dynamics, bridging quantum photonics, computational bioinformatics, and molecular biophysics. This work continues the lineage of groundbreaking studies from the 19ᵗʰ to 27ᵗʰ articles, evolving from accelerated drug discovery and phototherapy simulations to fully integrated photonically-informed bioinformatics. It opens new horizons for drug discovery, quantum biology, neurophotonics, and bioenergetics, with potential for nanobiocomputing devices that perform real-time sensing and computation within living systems.