Drug development hinges on accurately predicting how small molecules (drugs) interact with larger biological targets (proteins). Where classical computing methods, though advanced, can be slow and expensive, quantum computing offers tools to tackle problems too intricate for classical systems. Proteins are intricate chains of amino acids, folded into complex 3D shapes that form “pockets”, where therapeutic compounds, or ligands, bind. However, this process is far from straightforward. The role of water molecules – critical mediators of protein-ligand interactions – adds another layer of complexity. Inside a cell, water molecules penetrate these pockets, influencing protein shape, stability and the success of ligand binding. Mapping the distribution of water molecules within protein cavities is essential, but computationally demanding – particularly when investigating buried or occluded pockets. Quantum computing specialists Pasqal are collaborating Qubit Pharmaceuticals to develop a hybrid quantum-classical approach for analyzing protein hydration. This approach combines classical algorithms to generate water density data and quantum algorithms to precisely place water molecules inside protein pockets, even in challenging regions.

Full report : Quantum computing provides a revolutionary way to optimize and accelerate the identification of potential drugs.