Tencent Quantum Lab, Shenzhen, 518057, China.
AceMapAI Biotechnology, Suzhou, 215000, China.
Sci Rep. 2024 Jul 23;14(1):16942. doi: 10.1038/s41598-024-67897-8.
Quantum computing, with its superior computational capabilities compared to classical approaches, holds the potential to revolutionize numerous scientific domains, including pharmaceuticals. However, the application of quantum computing for drug discovery has primarily been limited to proof-of-concept studies, which often fail to capture the intricacies of real-world drug development challenges. In this study, we diverge from conventional investigations by developing a hybrid quantum computing pipeline tailored to address genuine drug design problems. Our approach underscores the application of quantum computation in drug discovery and propels it towards more scalable system. We specifically construct our versatile quantum computing pipeline to address two critical tasks in drug discovery: the precise determination of Gibbs free energy profiles for prodrug activation involving covalent bond cleavage, and the accurate simulation of covalent bond interactions. This work serves as a pioneering effort in benchmarking quantum computing against veritable scenarios encountered in drug design, especially the covalent bonding issue present in both of the case studies, thereby transitioning from theoretical models to tangible applications. Our results demonstrate the potential of a quantum computing pipeline for integration into real world drug design workflows.
量子计算在计算能力方面优于经典方法,有可能彻底改变包括制药在内的众多科学领域。然而,量子计算在药物发现中的应用主要局限于概念验证研究,这些研究往往无法捕捉到现实世界药物开发挑战的复杂性。在这项研究中,我们通过开发一种针对实际药物设计问题的混合量子计算管道,与传统研究方法分道扬镳。我们的方法强调了量子计算在药物发现中的应用,并推动其向更具可扩展性的系统发展。我们特别构建了我们的多功能量子计算管道,以解决药物发现中的两个关键任务:精确确定涉及共价键断裂的前药激活的吉布斯自由能分布,以及准确模拟共价键相互作用。这项工作是对量子计算在药物设计中实际遇到的场景进行基准测试的开创性努力,特别是两个案例研究中都存在的共价键问题,从而从理论模型过渡到实际应用。我们的结果表明,量子计算管道有可能集成到实际的药物设计工作流程中。
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