| De novo drug design framework based on mathematical programming method and deep learning model Y Zhao, Q Liu, X Wu, L Zhang, J Du, Q Meng AIChE Journal 68 (9), e17748, 2022 | 11 | 2022 |
| Profiling the structural determinants of aryl benzamide derivatives as negative allosteric modulators of mGluR5 by in silico study Y Zhao, J Chen, Q Liu, Y Li Molecules 25 (2), 406, 2020 | 10 | 2020 |
| Machine learning methods for developments of binding kinetic models in predicting protein‐ligand dissociation rate constants Y Zhao, Q Liu, J Du, Q Meng, L Zhang Smart Molecules 1 (3), e20230012, 2023 | 6 | 2023 |
| Reaction kinetic model considering the solvation effect based on the FMO theory and deep learning X Wu, Q Liu, Y Zhao, L Zhang, J Du Industrial & Engineering Chemistry Research 61 (41), 15261-15272, 2022 | 4 | 2022 |
| 中药系统药理学 Ⅱ: 在药物开发和复方研究领域的应用进展 赵雨靓， 李丰， 石彬彬， 李燕 辽宁中医杂志 47 (3), 213-20, 2020 | 3 | 2020 |
| Computer-aided amine solvent design for carbon capture based on desorption thermodynamic and reaction kinetic models Y Zhao, S Xiang, J Du, Q Meng, J Chen, M Gao, B Xing, Q Liu, L Zhang Separation and Purification Technology 360, 130984, 2025 | 1 | 2025 |
| Accelerating Factor Xa inhibitor discovery with a de novo drug design pipeline Y Zhao, Q Liu, J Du, Q Meng, L Sun, L Zhang Chinese Journal of Chemical Engineering 72, 85-94, 2024 | 1 | 2024 |
| Mixture-of-Experts Based Dissociation Kinetic Model for De Novo Design of HSP90 Inhibitors with Prolonged Residence Time Y Zhao, L Zhang, J Du, Q Meng, L Zhang, H Wang, L Sun, Q Liu Journal of Chemical Information and Modeling 64 (22), 8427-8439, 2024 | | 2024 |
| Hybrid deep learning model for evaluations of protein-ligand binding kinetic property Y Zhao, Q Liu, Y Zhuang, Y Dong, L Liu, J Du, Q Meng, L Zhang Computer Aided Chemical Engineering 53, 259-264, 2024 | | 2024 |
| Machine learning potential model for accelerating quantum chemistry‐driven property prediction and molecular design G Wu, Y Zhao, L Zhang, J Du, Q Meng, Q Liu AIChE Journal, e18741, 0 | | |