Quantum-Inspired Machine Learning for Molecular Docking

arXiv:2401.12999v2 Announce Type: replace-cross
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