Protein loop modeling is a challenging yet highly nontrivial task in protein structure prediction.Despite recent progress,existing methods including knowledge-based,ab initio,hybrid,and deep learning(DL)methods fall s...Protein loop modeling is a challenging yet highly nontrivial task in protein structure prediction.Despite recent progress,existing methods including knowledge-based,ab initio,hybrid,and deep learning(DL)methods fall substantially short of either atomic accuracy or computational efficiency.To overcome these limitations,we present KarmaLoop,a novel paradigm that distinguishes itself as the first DL method centered on full-atom(encompassing both backbone and side-chain heavy atoms)protein loop modeling.Our results demonstrate that KarmaLoop considerably outperforms conventional and DL-based methods of loop modeling in terms of both accuracy and efficiency,with the average RMSDs of 1.77 and 1.95Åfor the CASP13+14 and CASP15 benchmark datasets,respectively,and manifests at least 2 orders of magnitude speedup in general compared with other methods.Consequently,our comprehensive evaluations indicate that KarmaLoop provides a state-of-the-art DL solution for protein loop modeling,with the potential to hasten the advancement of protein engineering,antibody-antigen recognition,and drug design.展开更多
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 stud...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.展开更多
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 neddylat...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.展开更多
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...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.展开更多
基金supported by the National Key Research and Development Program of China(2022YFF1203000)the National Natural Science Foundation of China(22220102001,82204279,22007082,and 62006219)+2 种基金the Fundamental Research Funds for the Central Universities(226-2022-00220)the Natural Science Foundation of Zhejiang Province(LQ21B030013)Hong Kong Innovation and Technology Fund(Project No.ITS/241/21).
文摘Protein loop modeling is a challenging yet highly nontrivial task in protein structure prediction.Despite recent progress,existing methods including knowledge-based,ab initio,hybrid,and deep learning(DL)methods fall substantially short of either atomic accuracy or computational efficiency.To overcome these limitations,we present KarmaLoop,a novel paradigm that distinguishes itself as the first DL method centered on full-atom(encompassing both backbone and side-chain heavy atoms)protein loop modeling.Our results demonstrate that KarmaLoop considerably outperforms conventional and DL-based methods of loop modeling in terms of both accuracy and efficiency,with the average RMSDs of 1.77 and 1.95Åfor the CASP13+14 and CASP15 benchmark datasets,respectively,and manifests at least 2 orders of magnitude speedup in general compared with other methods.Consequently,our comprehensive evaluations indicate that KarmaLoop provides a state-of-the-art DL solution for protein loop modeling,with the potential to hasten the advancement of protein engineering,antibody-antigen recognition,and drug design.
基金National Key R&D Program of China(2021YFA1101000 to Y.S.,and 2018YFE0195100 to H.L.)Zhejiang Provincial Natural Science Foundation of China(LD22H300003 to Y.S.)+1 种基金A grant from Research Center for Life Science and Human Health,Binjiang Institute of Zhejiang University(ZY202205SMKY007 to Y.S.)National Natural Science Foundation of China(82020108030 for H.L.).
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.
基金National Key R&D Program of China(2016YFA0501800 to Yi Sun)for financial support。
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.
基金This work was financially supported by the National Natural Science Foundation of China(21575128,81773632,and 22173118)the National Key Research and Development Program of China(2021YFF1201400)+4 种基金the Natural Science Foundation of Zhejiang Province(LZ19H300001)the Hunan Provincial Science Fund for Distinguished Young Scholars(2021JJ10068)the Fundamental Research Funds for the Central Universities(2020QNA7003)the Science and Technology Innovation Program of Hunan Province(2021RC4011)Key R&D Program of Zhejiang Province(2020C03010).
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.
