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Researchers have demonstrated a resource-efficient hybrid quantum-classical method for molecular docking using current NISQ devices, successfully identifying key molecular contacts without yet achieving speed or accuracy advantages over classical computing. This approach aims to offload specific, difficult sub-problems of drug discovery to quantum hardware rather than replacing existing software, highlighting a practical pathway for integrating quantum tools into pharmaceutical workflows despite current hardware limitations.
Source coveringThe Quantum Insider
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Researchers Use IBM Quantum Computer to Test Drug-Docking Method

The Quantum Insider9 min read

Insider Brief A team of Singapore-based researchers reports that a hybrid quantum-classical method could offer a new route to studying drug candidates using today’s Noisy Intermediate-Stage Quantum (NISQ) devices. The researchers used the method to examine how two small molecules bind to proteins. In both tests, the quantum computer identified the same molecular contacts as […]

Researchers demonstrated a resource-efficient hybrid quantum-classical method for molecular docking on an IBM quantum processor. The method represented 18- and 14-variable docking problems using six and five qubits, respectively. The quantum hardware identified the same molecular contacts as classical calculations, although the small-scale tests didn’t demonstrate quantum advantage. A team of Singapore-based researchers reports that a hybrid quantum-classical method could offer a new route to studying drug candidates using today’s Noisy Intermediate-Stage Quantum (NISQ) devices. The researchers used the method to examine how two small molecules bind to proteins. In both tests, the quantum computer identified the same molecular contacts as conventional computer calculations. The approach also reduced the number of qubits needed to handle each problem. One test used six qubits to represent 18 variables, while the other used five qubits to represent 14 variables. The study, published as a preprint on arXiv, was conducted by researchers at Singapore’s Agency for Science, Technology and Research (A*STAR), the National University of Singapore and Nanyang Technological University.…

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