Covalent ligands are a fascinating and powerful class of drugs that bind to their biological targets by forming a covalent bond. This type of binding offers several compelling advantages: enhanced selectivity, prolonged duration of action, and improved potency compared to non-covalent drugs.The Cathepsin-K enzyme is a protease involved in breaking down bone and cartilage and is actively studied as a therapeutic target for postmenopausal osteoporosis. The odanacatib ligand is a potent and highly selective covalent inhibitor of Cathepsin-K, and the resulting complex is the target of this use case.Using Kvantify Qrunch (https://www.kvantify.com/products/qrunch) we deployed projective embedding and our proprietary algorithm BEAST-VQE to simulate an active space AS(80,24) of 80 orbitals and 24 electrons centered on the electrophilic carbon from the ligand’s nitrile functional group and the nucleophilic sulfur atom from the Cys-25 Cysteine residue in Cathepsin-K. The surrounding environment was treated with DFT. The computation was executed on Rigetti’s Ankaa-3 device through Amazon Braket, deploying 80 qubits and saturating the computational capacity of the device. Strikingly, the hardware results closely align with the simulated ideal performance and show superior convergence compared to a simulated noise-dominated scenario.The use case shows how Kvantify Qrunch makes it possible to execute real-world chemistry problems on current quantum computer hardware.
