Hybrid Quantum-Classical Algorithms for Drug Discovery and Molecular Simulation

Abstract: This study explores the implementation of hybrid quantum-classical algorithms in the realm of drug discovery and molecular simulation, with an emphasis on optimizing molecular interaction prediction. The integration of quantum computing paradigms, particularly the Variational Quantum Eigensolver (VQE), with classical machine learning techniques is evaluated for its efficacy in simulating molecular systems. Key results demonstrate superior accuracy in predicting binding affinities and reaction energetics using the hybrid models compared to traditional methods. The findings offer significant implications for accelerating the drug development pipeline, particularly in early-stage candidate screening. Keywords: Hybrid computing, Quantum simulation, Molecular interaction, Drug discovery, Variational Quantum Eigensolver, Quantum-classical integration