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| 1 | A small molecule inhibitor of the UBE2F-CRL5 axis induces apoptosis and radiosensitization in lung cancer显示文摘Protein neddylation is catalyzed by a neddylation activating enzyme(NAE,E1),an E2 conjugating enzyme,and an E3 ligase.In various types of human cancers,the neddylation pathway is abnormally activated.Our previous study validated that the neddylation E2 UBE2F is a promising therapeutic target in lung cancer.Although the NAE inhibitor MLN4924/pevonedistat is currently under clinical investigation as an anti-cancer agent,there are no small molecules available that selectively target UBE2F.Here,we report,for the first time,the discovery,via structure-based virtual screen and chemical optimization,of such a small molecule,designated as HA-9104.HA-9104 binds to UBE2F,reduces its protein levels,and consequently inhibits cullin-5 neddylation.Blockage of cullin-5 neddylation inactivates cullin-RING ligase-5(CRL5)activity,leading to accumulation of the CRL5 substrate,NOXA,to induce apoptosis.Moreover,HA-9104 appears to form the DNA adduct via its 7-azaindole group to induce DNA damage and G2/M arrest.Biologically,HA-9104 effectively suppresses the growth and survival of lung cancer cells and confers radiosensitization in both in vitro cell culture and in vivo xenograft tumor models.In summary,we discovered a small molecule,designated HA-9104,that targets the UBE2F-CRL5 axis with anti-cancer activity alone or in combination with radiation. | Tiantian Xu Qisheng Ma Yanan Li Qing Yu Peichen Pan Yawen Zheng Zhijian Li Xiufang Xiong Tingjun Hou Bin Yu Hongmin Liu Yi Sun | 2022 | Signal Transduction and Targeted Therapy2022，7，11： | 2 |
| 2 | Discovery of a small molecule inhibitor of cullin neddylation that triggers ER stress to induce autophagy显示文摘Protein neddylation is catalyzed by a three-enzyme cascade,namely an E1 NEDD8-activating enzyme(NAE),one of two E2 NEDD8 conjugation enzymes and one of several E3 NEDD8 ligases.The physiological substrates of neddylation are the family members of cullin,the scaffold component of cullin RING ligases(CRLs).Currently,a potent E1 inhibitor,MLN4924,also known as pevonedistat,is in several clinical trials for anti-cancer therapy.Here we report the discovery,through virtual screening and structural modifications,of a small molecule compound HA-1141 that directly binds to NAE in both in vitro and in vivo assays and effectively inhibits neddylation of cullins 1 e5.Surprisingly,unlike MLN4924,HA-1141 also triggers non-canonical endoplasmic reticulum(ER)stress and PKR-mediated terminal integrated stress response(ISR)to activate ATF4 at an early stage,and to inhibit protein synthesis and mTORC1 activity at a later stage,eventually leading to autophagy induction.Biologically,HA-1141 suppresses growth and survival of cultured lung cancer cells and tumor growth in in vivo xenograft lung cancer models at a well-tolerated dose.Taken together,our study has identified a small molecule compound with the dual activities of blocking neddylation and triggering ER stress,leading to growth suppression of cancer cells. | Yanan Li Chaorong Wang Tiantian Xu Peichen Pan Qing Yu Lei Xu Xiufang Xiong Tingjun Hou Sunliang Cui Yi Sun | 2021 | Acta Pharmaceutica Sinica B2021，11，11： | 1 |
| 3 | Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network显示文摘Covalent ligands have attracted increasing attention due to their unique advantages,such as long residence time,high selectivity,and strong binding affinity.They also show promise for targets where previous efforts to identify noncovalent small molecule inhibitors have failed.However,our limited knowledge of covalent binding sites has hindered the discovery of novel ligands.Therefore,developing in silico methods to identify covalent binding sites is highly desirable.Here,we propose DeepCoSI,the first structure-based deep graph learning model to identify ligandable covalent sites in the protein.By integrating the characterization of the binding pocket and the interactions between each cysteine and the surrounding environment,DeepCoSI achieves state-of-the-art predictive performances.The validation on two external test sets which mimic the real application scenarios shows that DeepCosI has strong ability to distinguish ligandable sites from the others.Finally,we profiled the entire set of protein structures in the RCSB Protein Data Bank(PDB)with DeepCoSI to evaluate the ligandability of each cysteine for covalent ligand design,and made the predicted data publicly available on website. | Hongyan Du Dejun Jiang Junbo Gao Xujun Zhang Lingxiao Jiang Yundian Zeng Zhenxing Wu Chao Shen Lei Xu Dongsheng Cao Tingjun Hou Peichen Pan | 2022 | Research2022，，4： | 1 |
| 4 | FPGA de- sign automation:a survey显示文摘 | Deming Chen Jason Cong Peichen Pan | 2006 | Electronic Design Au- tomation2006，1，3： | 1 |
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