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Quantum-Inspired Machine Learning for Molecular Docking
Feb. 23, 2024, 5:44 a.m. | Runqiu Shu, Bowen Liu, Zhaoping Xiong, Xiaopeng Cui, Yunting Li, Wei Cui, Man-Hong Yung, Nan Qiao
cs.LG updates on arXiv.org arxiv.org
Abstract: Molecular docking is an important tool for structure-based drug design, accelerating the efficiency of drug development. Complex and dynamic binding processes between proteins and small molecules require searching and sampling over a wide spatial range. Traditional docking by searching for possible binding sites and conformations is computationally complex and results poorly under blind docking. Quantum-inspired algorithms combining quantum properties and annealing show great advantages in solving combinatorial optimization problems. Inspired by this, we achieve an …
abstract arxiv cs.ai cs.lg design development drug design drug development dynamic efficiency machine machine learning molecular docking molecules physics.chem-ph processes proteins quantum sampling searching small spatial tool type
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