Molecular Recognition from Quantum Computing

Owner

Quantum Approach

Quantum Simulation

SDGs

Contributors

University of Copenhagen

Massachusetts Institute of Technology

ETH Zurich

Novo Norddisk A/S

Origins of Contributors

How quantum could help

Accurately calculating molecular interactions is essential for drug discovery but remains a significant computational challenge, especially at the interaction seam where drug and target molecules meet. FreeQuantum is a bottom-up computational pipeline to understand binding in biologically and pharmacologically relevant protein-ligand systems, and it integrates quantum computing, molecular mechanics, and machine learning to address this challenge. It treats key molecular regions as quantum cores, processed by a quantum computer, while handling the rest with varying levels of approximation. Machine learning can in turn further accelerate the workflow by training on data of different accuracy levels. The pipeline’s effectiveness was first demonstrated in the molecular recognition of a well-studied protein-ligand complex, and later applied to a ruthenium-based anti-cancer molecule interacting with its protein target. This work highlights the potential for advancing computational chemistry with quantum computing.