How Analog Quantum Computing is Transforming Drug Discovery

In drug discovery, speed and precision are critical. Predicting how a drug will interact with its target proteins is a key challenge, and water molecules can play an important role in this process. Misjudging their placement can lead to ineffective drugs, slowing down development.

That’s where a breakthrough from Qubit Pharmaceuticals and Pasqal comes in. Our research, detailed in the paper "Leveraging Analog Quantum Computing with Neutral Atoms for Solvent Conf iguration Prediction in Drug Discovery," introduces a new analog quantum computing algorithm that could improve the accuracy of predicting water molecule behavior in protein structures. This advancement could signif icantly accelerate drug discovery and lead to more targeted, effective treatments.

Why Water Molecules Matter in Drug Design Computing Meets Drug Discovery

Water molecules influence how a drug f its into its protein target, affecting its efficacy. However, predicting their behavior in proteins is extremely complex. Traditional computational methods, while useful, may lack precision and consume significant resources, creating bottlenecks in the drug development process.  Predicting the placement of water molecules within a protein's binding site improves the accuracy of molecular simulations, which in turn helps drug designers develop more targeted therapies.

How Analog Quantum Computing Changes the Game 1: Quantum Adiabatic Evolution

Unlike classical computing, which processes data in binary, analog quantum computing uses qubits that can exist in multiple states at once, allowing it to handle complex calculations more efficiently. In collaboration with Pasqal, Qubit Pharmaceuticals mapped the real, classical challenge of predicting water molecule placement in protein structures—a crucial step in drug design—onto an analog quantum system.

We’ve already demonstrated this approach with 14 qubits, achieving promising results in a practical, real-world context. Even at this early stage, the outcomes are exciting, and we expect even greater advancements as we scale to more qubits and incorporate additional features. Water molecule placement is just one important piece of the drug discovery process, and this method shows real potential to enhance the precision of molecular modeling.

Given the complexity of computational drug discovery, which involves hundreds of steps, there’s vast potential for further optimization. 

To sum it up, this project was led to explore in a proof of concept application the use of analog quantum computing in a specific relevant task in computational drug design. Our approach is designed to scale its performance as both classical and quantum computing improve.

Why This Matters for Drug Discovery—and Patients

If projects like this benef it from increased computational resources, this could mean two things: for drug designers, it could lead to better predictions, fewer failed trials, and faster drug development; which in consequence further down the line, for patients, that would mean quicker access to new therapeutics that would be more likely to work as intended, potentially improving outcomes. By exploring the integration of analog quantum computing into drug discovery, Qubit Pharmaceuticals and Pasqal hope to pave the way for faster, more precise drug design, benefitting both the industry and patients.

Visualisation of the placement of water molecules within a protein structure.

Publication Credits

Mauro D'Arcangelo, Daniele Loco, Fresnel team, Nicolaï Gouraud, Stanislas Angebault, Jules Sueiro, Pierre Monmarché, Jérôme Forêt, Louis-Paul Henry, Loïc Henriet, Jean-Philip Piquemal.

Pasqal, Qubit Pharmaceuticals