10 citations · 10 across the 6 of their papers we have counts for
6 papers
SQD-Enabled Circuit Compression for Resource-Efficient Quantum Chemistry
Kangyu Zheng, Yidong Zhou, Jinglei Cheng +3
Sample-based Quantum Diagonalization (SQD) recovers ground-state energies by classically diagonalizing a Hamiltonian in the subspace spanned by quantum samples, requiring only bits…
Q-Score: A Quantum-Native Scoring Function for Molecular Docking
Kangyu Zheng, Yidong Zhou, Ruihao Li +3
Molecular docking predicts how a small molecule binds to a protein and is a key bottleneck in drug discovery. Classical scoring functions sum empirical pairwise contacts, blind to…
Beyond Affinity: A Benchmark of 1D, 2D, and 3D Methods Reveals Critical Trade-offs in Structure-Based Drug Design
Kangyu Zheng, Kai Zhang, Jiale Tan +7
Currently, the field of structure-based drug design is dominated by three main types of algorithms: search-based algorithms, deep generative models, and reinforcement learning. Whi…
QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation
Kangyu Zheng, Tianfan Fu, Zhiding Liang
The biomedical field is beginning to explore the use of quantum machine learning (QML) for tasks traditionally handled by classical machine learning, especially in predicting ADME…
Quantum-inspired Reinforcement Learning for Synthesizable Drug Design
Dannong Wang, Jintai Chen, Yingzhou Lu +5
Synthesizable molecular design (also known as synthesizable molecular optimization) is a fundamental problem in drug discovery, and involves designing novel molecular structures to…
Quantum-machine-assisted Drug Discovery
Yidong Zhou, Jintai Chen, Jinglei Cheng +8
Drug discovery is lengthy and expensive, with traditional computer-aided design facing limits. This paper examines integrating quantum computing across the drug development cycle t…