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AI · Nanobody · Molecular Design

Jourmore

人工智能 解码分子世界 — 聚焦 纳米抗体 工程与 分子设计、计算毒理学的智能预测。

人工智能 / 深度学习 纳米抗体筛选与工程 分子设计与表征
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Research 研究方向

🧬 小分子 & 蛋白 & 纳米抗体

  • 计算机辅助药物筛选与设计 (CADD/AIDD)
  • 计算毒理学 / 网络毒理学 / 网络药理学 (Network)

🍎 食品暗物质与毒性预测 (计算毒理学)

  • 食品中未知化合物 (暗物质) 空间分析与危害识别
  • 有毒化合物预测及毒性机制解析 (机器学习 + MD)

Publications 代表性论文

  • [1] Mao J, Song Y, Kong M, Guo Y, Liu Y, Pu X. Thermostability Prediction Powered by Synergistic Deep Learning at Experimental and Theoretical Levels for Nanobodies. ACS Applied Materials & Interfaces. 2026. DOI
  • [2] Li YL, Mao J#, Zhou XY, Zhang DN, Li YZ, Cao ZX, Ren JX. Discovery of anti-glioblastoma natural products based on andrographolide derivatives: efficiently identifying potential multi-target and multifunctional molecules through the integration of in silico methods and experimental verification. Molecular Diversity. 2026. DOI
  • [3] Pan CC, Yang CM, Mao J*. Sense-of-agency as clinically accessible features for schizophrenia prediction: Interpretable ensemble machine learning research and webserver development. Asian Journal of Psychiatry. 2025,111:104674. DOI
  • [4] Li YL, Mao J#, Zhu JH, Zhang H, Ding L. Identification of Salvianolic acid A as a potent inhibitor of PDEs to enhance proliferation of human neural stem cells. Journal of Molecular Structure. 2025,1324:140905. DOI
  • [5] Li YL, Mao J#, Cheng Z, Zhou XY, Zhang DN, Li YZ, Cao ZX, Ren JX. Identification of Salvianolic acid A as a potent inhibitor of PDEs to enhance proliferation of human neural stem cells. Molecular Diversity. 2025. DOI
  • [6] Kong M, Chen X, Mao J, Yu J, Song YP, Guo YZ, Pu XM. Machine Learning Navigated Allosteric Network to Unveil Biased Allosteric Modulation of GPCRs. Journal of Chemical Theory and Computation. 2025,21(19):9669-9686. DOI
  • [7] Chen X, Wang K, Chen J, Wu C, Mao J, Song Y, Liu Y, Shao Z, Pu X. Integrative residue-intuitive machine learning and MD Approach to Unveil Allosteric Site and Mechanism for β2AR. Nature Communications. 2024,15(1):8130. DOI
  • [8] Hu J, Yang SR, Mao J, Shi CJ, Wang GC, Liu YJ, Pu XM. Exploring a general convolutional neural network-based prediction model for critical casting diameter of metallic glasses. Journal of Alloys and Compounds. 2023,947:169479. DOI
  • [9] 专利 — 基于深度学习和计算模拟的蛋白质变构调节剂的识别方法, 中国发明专利 ZL202211500668.3 (授权日2023.9.8).
  • [10] Mao J, Luo QQ, Zhang HR, Zheng XH, Shen C, Qi HZ, Hu ML, Zhang H. Discovery of microtubule stabilizers with novel scaffold structures based on virtual screening, biological evaluation, and molecular dynamics simulation. Chemico-Biological Interactions. 2022,352:109784. DOI
  • [11] Yang MH, Mao J#, Zhu JH, Zhang H, Ding L. Wangzaozin A, a potent novel microtubule stabilizer, targets both the taxane and laulimalide sites on β-tubulin through molecular dynamics simulations. Life Sciences. 2022:120583. DOI
  • [12] Zhang H, Qi HZ, Mao J, Zhang HR, Luo QQ, Hu ML, Shen C, Ding L. Discovery of novel microtubule stabilizers targeting taxane binding site by applying molecular docking, molecular dynamics simulation, and anticancer activity testing. Bioorganic Chemistry. 2022,122:105722. DOI
  • [13] Zhang H, Mao J#, Yang YL, Liu CT, Shen C, Zhang HR, Xie HZ, Ding L. Discovery of novel tubulin inhibitors targeting taxanes site by virtual screening, molecular dynamic simulation, and biological evaluation. Journal of Cellular Biochemistry. 2021,122(11):1609-1624. DOI
  • [14] Zhang H, Mao J#, Qi HZ, Ding L. In silico prediction of drug-induced developmental toxicity by using machine learning approaches. Molecular Diversity. 2020,24(4):1281-1290. DOI
  • [15] Zhang H, Mao J#, Qi HZ, Xie HZ, Shen C, Liu CT, Ding L. Developing novel computational prediction models for assessing chemical-induced neurotoxicity using naïve Bayes classifier technique. Food and Chemical Toxicology. 2020,143:111513. DOI
  • [16] Zhang H, Liu CT, Mao J, Shen C, Xie RL, Mu B. Development of novel in silico prediction model for drug-induced ototoxicity by using naïve Bayes classifier approach. Toxicology in Vitro. 2020,65:104812. DOI
  • [17] Zhang H, Shen C, Liu RZ, Mao J, Liu CT, Mu B. Developing novel in silico prediction models for assessing chemical reproductive toxicity using the naïve Bayes classifier method. Journal of Applied Toxicology. 2020,40(9):1198-1209. DOI
  • [18] NBsPocket: A Computational Platform Integrating an Pocket Database for Hapten-Specific Nanobody Screening and Analysis.
  • [19] BBB Permeability Prediction Models: Characteristic Substructure Analysis, Molecular Dynamics Verification, and Rational Lead Optimization.

About

2026 – Now
XHU · 教学科研岗,化学与生物信息学
2022 – 2026
SCU · 博士,化学与生物信息学
2019 – 2022
NWNU · 硕士,计算机辅助药物设计 & 计算毒理学
2017 – 2019
ZJU · 科研助理,生物信息学
2014 – 2018
CMC · 本科,基因工程/细胞工程

Jourmore (Jun Mao)

📧 maojun@xhu.edu.cn

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