G-quadruplexes(G4s),as special nucleic acid secondary structures,are promising therapeutic targets for enhancing immune response.We designed a bifunctional(two Pt-Cl bonds)PyPDSplatin complex(BiPP)by coupling PyPDS wi...G-quadruplexes(G4s),as special nucleic acid secondary structures,are promising therapeutic targets for enhancing immune response.We designed a bifunctional(two Pt-Cl bonds)PyPDSplatin complex(BiPP)by coupling PyPDS with cisplatin.Due to the retention of two chlorine atoms,BiPP can covalently bind to two sites on G4s,thereby enhancing binding stability.BiPP retains the classical cisplatin structure,which helps to maintain it in a neutral or weakly charged state,facilitating the passage of dichloroplatin complexes across the cell membrane.BiPP not only significantly bolstered the antitumor efficacy of chemotherapy but also induced damage to G4s,facilitating their efflux from the nucleus and thereby activating a synergistic interplay between the absent in melanoma 2-apoptosis-associated speck-like protein containing a CARD(AIM2-ASC)and cyclic GMP-AMP synthase-stimulator of the interferon gene(cGAS-STING)pathways.Moreover,BiPP initiated a molecular cascade that triggers pyroptosis by down-regulating baculoviral IAP repeat containing 7(BIRC7)gene expression.During this process,caspase-3 is activated to cleave gasdermin E(GSDME),releasing its N-terminal domain(GSDNE-N),which subsequently induces pyroptosis.This interaction culminates in the formation of a highly integrated antitumor immune network in conjunction with the BIRC7-caspase-3-GSDME system.Our findings not only unveil the pivotal role played by G4s in the context of antitumor immunity,but also open an avenue for the application of G4-guided chemotherapy agents in immunotherapy.展开更多
The selection and modulation of the static and dynamic units within molecular-scale actuators,particularly regarding framework structures,are critical for initiating synergistic inter-and intramolecular motions.Howeve...The selection and modulation of the static and dynamic units within molecular-scale actuators,particularly regarding framework structures,are critical for initiating synergistic inter-and intramolecular motions.However,achieving controllable macroscopic mechanical switching through the collective transfer of microscopic motion while minimizing energy dissipation presents a significant challenge.This paper reports a two-dimensional magnetic coordination framework,Fe(tpe)(NCBH_(3))_(2)(tpe=1,1,2,2-tetra(pyridin-4-yl)ethene,1),synthesized by the minimally sized,planar tetradentate pyridine-based tpe ligand in conjunction with the precursor Fe(NCBH_(3))_(2).A single-crystal-to-single-crystal(SCSC)transformation,occurring via the adsorption and desorption of C_(2)Cl_(4) vip molecules,is directly associated with the activation of spin crossover(SCO)and CO_(2)/C_(2)H_(2) separation performance,correlating with the overall elastic frustration and toughness present in the framework.The establishment of multiple C–Hδ+⋯Hδ−–B dihydrogen bonds surrounding the tpe ligand facilitates its effective function as a static unit,simultaneously augmenting cooperativity with the Fe(NCBH_(3))_(2) acting as a dynamic unit,thereby enabling a macroscopic shape change in the free single crystal with reduced energy dissipation.The spin transition of the Fe2+metal center,activated by SCSC transformation and serving as a driving force for crystal macroscopic deformation,provides new insights into the mechanism of structural adaptability in frameworks and designing novel molecular machines.展开更多
Graph deep learning models,which incorporate a natural inductive bias for atomic structures,are of immense interest in materials science and chemistry.Here,we introduce the Materials Graph Library(MatGL),an open-sourc...Graph deep learning models,which incorporate a natural inductive bias for atomic structures,are of immense interest in materials science and chemistry.Here,we introduce the Materials Graph Library(MatGL),an open-source graph deep learning library for materials science and chemistry.Built on top of the popular Deep Graph Library(DGL)and Python Materials Genomics(Pymatgen)packages,MatGL is designed to be an extensible“batteries-included”library for developing advanced model architectures for materials property predictions and interatomic potentials.At present,MatGL has efficient implementations for both invariant and equivariant graph deep learning models,including the Materials 3-body Graph Network(M3GNet),MatErials Graph Network(MEGNet),Crystal Hamiltonian Graph Network(CHGNet),TensorNet and SO3Net architectures.MatGL also provides several pretrained foundation potentials(FPs)with coverage of the entire periodic table,and property prediction models for out-of-box usage,benchmarking and fine-tuning.Finally,MatGL integrates with PyTorch Lightning to enable efficient model training.展开更多
基金support from the National Key Research and Development Program of China[2022YFB3804502]the National Natural Science Foundation of China[92353301,22277151,22293053,22007103,22293050,and 22307054]+4 种基金the Natural Science Foundation of Guangdong Province[2024B1515020083]the Guangzhou Science and Technology Plan Project[2023A04J1941]the Fundamental Research Funds for the Central Universities,the China National Postdoctoral Program for Innovative Talents(BX20230154)the China Postdoctoral Science Foundation(2023M731591)the Jiangsu Funding Program for Excellent Postdoctoral Talent(2023ZB201).
文摘G-quadruplexes(G4s),as special nucleic acid secondary structures,are promising therapeutic targets for enhancing immune response.We designed a bifunctional(two Pt-Cl bonds)PyPDSplatin complex(BiPP)by coupling PyPDS with cisplatin.Due to the retention of two chlorine atoms,BiPP can covalently bind to two sites on G4s,thereby enhancing binding stability.BiPP retains the classical cisplatin structure,which helps to maintain it in a neutral or weakly charged state,facilitating the passage of dichloroplatin complexes across the cell membrane.BiPP not only significantly bolstered the antitumor efficacy of chemotherapy but also induced damage to G4s,facilitating their efflux from the nucleus and thereby activating a synergistic interplay between the absent in melanoma 2-apoptosis-associated speck-like protein containing a CARD(AIM2-ASC)and cyclic GMP-AMP synthase-stimulator of the interferon gene(cGAS-STING)pathways.Moreover,BiPP initiated a molecular cascade that triggers pyroptosis by down-regulating baculoviral IAP repeat containing 7(BIRC7)gene expression.During this process,caspase-3 is activated to cleave gasdermin E(GSDME),releasing its N-terminal domain(GSDNE-N),which subsequently induces pyroptosis.This interaction culminates in the formation of a highly integrated antitumor immune network in conjunction with the BIRC7-caspase-3-GSDME system.Our findings not only unveil the pivotal role played by G4s in the context of antitumor immunity,but also open an avenue for the application of G4-guided chemotherapy agents in immunotherapy.
基金funded by the Ningbo Soft Science Science Research Program(2023R002)Ningbo Natural Science Foundation(2022J096)+1 种基金National Natural Science Foundation of China(21571110)Natural Science Foundation of Zhejiang province(LY18B010003).
文摘The selection and modulation of the static and dynamic units within molecular-scale actuators,particularly regarding framework structures,are critical for initiating synergistic inter-and intramolecular motions.However,achieving controllable macroscopic mechanical switching through the collective transfer of microscopic motion while minimizing energy dissipation presents a significant challenge.This paper reports a two-dimensional magnetic coordination framework,Fe(tpe)(NCBH_(3))_(2)(tpe=1,1,2,2-tetra(pyridin-4-yl)ethene,1),synthesized by the minimally sized,planar tetradentate pyridine-based tpe ligand in conjunction with the precursor Fe(NCBH_(3))_(2).A single-crystal-to-single-crystal(SCSC)transformation,occurring via the adsorption and desorption of C_(2)Cl_(4) vip molecules,is directly associated with the activation of spin crossover(SCO)and CO_(2)/C_(2)H_(2) separation performance,correlating with the overall elastic frustration and toughness present in the framework.The establishment of multiple C–Hδ+⋯Hδ−–B dihydrogen bonds surrounding the tpe ligand facilitates its effective function as a static unit,simultaneously augmenting cooperativity with the Fe(NCBH_(3))_(2) acting as a dynamic unit,thereby enabling a macroscopic shape change in the free single crystal with reduced energy dissipation.The spin transition of the Fe2+metal center,activated by SCSC transformation and serving as a driving force for crystal macroscopic deformation,provides new insights into the mechanism of structural adaptability in frameworks and designing novel molecular machines.
基金intellectually led by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under contract No. DE-AC02-05-CH11231 (Materials Project program KC23MP). This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award DOE-ERCAP0026371. T.W.Ko also acknowledges the support of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a Schmidt Futures program. We also acknowledged AdvanceSoft Corporation for implementing the LAMMPS interface.
文摘Graph deep learning models,which incorporate a natural inductive bias for atomic structures,are of immense interest in materials science and chemistry.Here,we introduce the Materials Graph Library(MatGL),an open-source graph deep learning library for materials science and chemistry.Built on top of the popular Deep Graph Library(DGL)and Python Materials Genomics(Pymatgen)packages,MatGL is designed to be an extensible“batteries-included”library for developing advanced model architectures for materials property predictions and interatomic potentials.At present,MatGL has efficient implementations for both invariant and equivariant graph deep learning models,including the Materials 3-body Graph Network(M3GNet),MatErials Graph Network(MEGNet),Crystal Hamiltonian Graph Network(CHGNet),TensorNet and SO3Net architectures.MatGL also provides several pretrained foundation potentials(FPs)with coverage of the entire periodic table,and property prediction models for out-of-box usage,benchmarking and fine-tuning.Finally,MatGL integrates with PyTorch Lightning to enable efficient model training.
