教育经历
2002—2006北京大学物理学院 理学学士
2006—2012北京大学定量生物学中心 理学博士
2012—2016The University of Kansas 博士后
2016—2021华东师范大学化学与分子工程学院 副研究员
2021—今复旦大学药学院药物化学系 副研究员
2018—2020 基金委青年科学基金 主持
2019—2022 上海市科委自然科学基金探索类项目 主持
人工智能蛋白质和小分子药物设计，生物大分子结构和功能模拟
综合采用机器学习和分子模拟等方法，在蛋白结构设计和稳定性预测、蛋白-小分子药物相互作用微观机理和设计、生物大分子模拟等方面取得了创新成果，目前已发表科研论文60余篇，谷歌学术总引用8000余次。
(1) Xia, W.; He, L.; Bao, J.; Qi, Y.; Zhang, J. Z. H. Insights into Small Molecule Inhibitor Bindings to PD-L1 with Residue-Specific Binding Free Energy Calculation. J. Biomol. Struct. Dyn.2021, 0 (0), 1–9.
(2) Shao, G.; Bao, J.; Pan, X.; He, X.; Qi, Y.; Zhang, J. Z. H. Computational Analysis of Residue-Specific Binding Free Energies of Androgen Receptor to Ligands. Front. Mol. Biosci.2021, 8 (March), 1–9.
(3) Huang, D.; Tian, S.; Qi, Y.; Zhang, J. Z. H. Binding Modes of Small‐Molecule Inhibitors to the EED Pocket of PRC2. ChemPhysChem2020, 21 (3), 263–271.
(4) Wang, R.; Cong, Y.; Li, M.; Bao, J.; Qi, Y.; Zhang, J. Z. H. Molecular Mechanism of Selective Binding of NMS-P118 to PARP-1 and PARP-2: A Computational Perspective. Front. Mol. Biosci.2020, 7 (April).
(5) Qi, Y.; Lee, J.; Cheng, X.; Shen, R.; Islam, S. M.; Roux, B.; Im, W. CHARMM‐GUI DEER Facilitator for Spin‐pair Distance Distribution Calculations and Preparation of Restrained‐ensemble Molecular Dynamics Simulations. J. Comput. Chem.2020, 41 (5), 415–420.
(6) Li, Z.; Bao, J.; Qi, Y.; Zhang, J. Z. H. Computational Approaches to Studying Methylated H4K20 Recognition by DNA Repair Factor 53BP1. Phys. Chem. Chem. Phys.2020, 22 (11), 6136–6144.
(7) Qi, Y.; Zhang, J. Z. H. DenseCPD: Improving the Accuracy of Neural-Network-Based Computational Protein Sequence Design with DenseNet. J. Chem. Inf. Model.2020, 60 (3), 1245–1252.
(8) He, L.; Bao, J.; Yang, Y.; Dong, S.; Zhang, L.; Qi, Y.; Zhang, J. Z. H. Study of SHMT2 Inhibitors and Their Binding Mechanism by Computational Alanine Scanning. J. Chem. Inf. Model.2019, 59 (9), 3871–3878.
(9) Cao, H.; Wang, J.; He, L.; Qi, Y.; Zhang, J. Z. DeepDDG: Predicting the Stability Change of Protein Point Mutations Using Neural Networks. J. Chem. Inf. Model.2019, 59 (4), 1508–1514.
(10) Qi, Y.; Lee, J.; Klauda, J. B.; Im, W. CHARMM-GUI Nanodisc Builder for Modeling and Simulation of Various Nanodisc Systems. J. Comput. Chem.2019, 40 (7), 893–899.
(11) Wang, J.; Cao, H.; Zhang, J. Z. H.; Qi, Y. Computational Protein Design with Deep Learning Neural Networks. Sci. Rep.2018, 8 (1), 1–9.
(12) Qi, Y.; Lee, J.; Singharoy, A.; McGreevy, R.; Schulten, K.; Im, W. CHARMM-GUI MDFF/XMDFF Utilizer for Molecular Dynamics Flexible Fitting Simulations in Various Environments. J. Phys. Chem. B2017, 121 (15), 3718–3723.
(13) Hsu, P.-C.; Bruininks, B. M. H.; Jefferies, D.; Cesar Telles de Souza, P.; Lee, J.; Patel, D. S.; Marrink, S. J.; Qi, Y.; Khalid, S.; Im, W. CHARMM-GUI Martini Maker for Modeling and Simulation of Complex Bacterial Membranes with Lipopolysaccharides. J. Comput. Chem.2017, 38 (27), 2354–2363.
(14) Qi, Y.; Klauda, J. B.; Im, W. Effects of Spin-Labels on Membrane Burial Depth of MARCKS-ED Residues. Biophys. J.2016, 111 (8), 1600–1603.
(15) Qi, Y.; Ingólfsson, H. I.; Cheng, X.; Lee, J.; Marrink, S. J.; Im, W. CHARMM-GUI Martini Maker for Coarse-Grained Simulations with the Martini Force Field. J. Chem. Theory Comput.2015, 11 (9), 4486–4494.
(16) Qi, Y.; Cheng, X.; Han, W.; Jo, S.; Roux, B.; Schulten, K.; Im, W. CHARMM-Gui Pace Cg Builder for Solution, Micelle, Bilayer and Vesicle Simulations. Biophys. J.2015, 106 (2), 809a.
(17) Qi, Y.; Jo, S.; Im, W. Roles of Glycans in Interactions between Gp120 and HIV Broadly Neutralizing Antibodies. Glycobiology2015, 26 (3), 251–260.
(18) Qi, Y.; Cheng, X.; Lee, J.; Vermaas, J. V.; Pogorelov, T. V.; Tajkhorshid, E.; Park, S.; Klauda, J. B.; Im, W. CHARMM-GUI HMMM Builder for Membrane Simulations with the Highly Mobile Membrane-Mimetic Model. Biophys. J.2015, 109 (10), 2012–2022.
(19) Qi, Y.; Im, W. Quantification of Drive-Response Relationships Between Residues During Protein Folding. J. Chem. Theory Comput.2013, 9 (8), 3799–3805.
(20) Qi, Y.; Wang, Q.; Tang, B.; Lai, L. Identifying Allosteric Binding Sites in Proteins with a Two-State Gô Model for Novel Allosteric Effector Discovery. J. Chem. Theory Comput.2012, 8 (8), 2962–2971.
(21) Qi, Y.; Huang, Y.; Liang, H.; Liu, Z.; Lai, L. Folding Simulations of a de Novo Designed Protein with a Betaalphabeta Fold. Biophys. J.2010, 98 (2), 321–329.
