Generalizable Quantum Computing Pipeline for Real World Drug Discovery
arxiv(2024)
摘要
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 an advanced quantum computing pipeline tailored to
address genuine drug design problems. Our approach underscores the pragmatic
application of quantum computation and propels it towards practical industrial
adoption. 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.
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