aiqbench takeQuantum Computing

Researchers successfully simulated the autoproteolysis of the ADGRG1 receptor using a hybrid quantum-classical architecture that couples a 54-qubit IQM processor with NVIDIA H100 GPUs. This approach overcomes current computational limits to model million-atom systems relevant to drug discovery for adhesion GPCRs, which remain a significant unmet target in pharmaceutical development. The study demonstrates a practical pathway for applying quantum hardware to complex biochemical problems that are intractable for classical supercomputers alone.

Sources coveringQuantum Zeitgeist, arXiv

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ADGRG1 receptor cleavage simulated with 54-qubit quantum processor

Quantum ZeitgeistOctober 21, 20265 min read

Researchers used a 54-qubit IQM quantum processor to model ADGRG1 receptor autoproteolysis, a key process in a million-atom system.

A 54-qubit IQM quantum processor is at the heart of a new simulation that models a biologically important process: a protein cutting itself in two. Researchers from QMatter, the Technical University of Munich, University College London, Leibniz Supercomputing Centre, Ludwig-Maximilians-Universität München, NVIDIA, and IQM Quantum Computers coupled the quantum processor with up to 1,200 NVIDIA H100 GPUs to model the autoproteolysis of ADGRG1, an adhesion G-protein-coupled receptor linked to both brain development disorders and aggressive breast cancer. Understanding precisely how this cleavage happens could provide a basis for targeting…

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