In the year 1971,the world’s biggest structural biology collaboration name—The Research Collaboratory for Structural Bioinformatics(RCSB),was formed to gather all the structural biologists at a single platform and t...In the year 1971,the world’s biggest structural biology collaboration name—The Research Collaboratory for Structural Bioinformatics(RCSB),was formed to gather all the structural biologists at a single platform and then extended out to be the world’s most extensive structural data repository named RCSB-Protein Data Bank(PDB)(https://www.rcsb.org/)that has provided the service for more than 50 years and continues its legacy for the discoveries and repositories for structural data.The RCSB has evolved from being a collaboratory network to a full-fledged database and tool with a huge list of protein structures,nucleic acid-containing structures,ModelArchive,and AlphaFold structures,and the best is that it is expanding day by day with computational advancement with tools and visual experiences.In this review article,we have discussed how RCSB has been a successful collaboratory network,its expansion in each decade,and how it has helped the ground-breaking research.The PDB tools that are helping the researchers,yearly data deposition,validation,processing,and suggestions that can help the developer improve for upcoming years are also discussed.This review will help future researchers understand the complete history of RCSB and its developments in each decade and how various future collaborative networks can be developed in various scientific areas and can be successful by keeping RCSB as a case study.展开更多
DNA imaging and visualization techniques are crucial in biological experiments and have also emerged as a powerful method for single-molecule studies.Traditional intercalating dyes(e.g.,SYTOX,EtBr,GelRed)can stain DNA...DNA imaging and visualization techniques are crucial in biological experiments and have also emerged as a powerful method for single-molecule studies.Traditional intercalating dyes(e.g.,SYTOX,EtBr,GelRed)can stain DNA but may alter its structure and mechanical properties,and cause photocleavage.Recently,a novel fluorescent DNA-binding protein(FP-DBP)was introduced,which can stain DNA without sequence preference and without inducing photocleavage.In this study,using a custom-built magnetic tweezers system,we performed DNA stretching,twisting and unzipping experiments to compare the mechanical properties of DNA with and without two kinds of intercalating dyes(SYTOX Orange and GelRed)and mCherry FP-DBP.Our results show that mCherry FP-DBP does not affect DNA structure or mechanics,unlike SYTOX Orange and GelRed,making FP-DBP a promising tool for DNA visualization in single-molecule experiments.展开更多
Accurate identification of RNA-ligand binding sites is essential for elucidating RNA function and advancing structurebased drug discovery.Here,we present RLsite,a novel deep learning framework that integrates energy-,...Accurate identification of RNA-ligand binding sites is essential for elucidating RNA function and advancing structurebased drug discovery.Here,we present RLsite,a novel deep learning framework that integrates energy-,structure-and sequence-based features to predict nucleotide-level binding sites with high accuracy.RLsite leverages energy-based threedimensional representations,obtained from atomic probe interactions using a pre-trained ITScore-NL potential,and models their contextual features through a 3D convolutional neural network(3D-CNN)augmented with self-attention.In parallel,structure-based features,including network properties,Laplacian norm,and solvent-accessible surface area,together with sequence-based evolutionary constraint scores,are mapped along the RNA sequence and used as sequential descriptors.These descriptors are modeled using a bidirectional long short-term memory(BiLSTM)network enhanced with multihead self-attention.By effectively fusing these complementary modalities,RLsite achieves robust and precise binding site prediction.Extensive evaluations across four diverse RNA-ligand benchmark datasets demonstrate that RLsite consistently outperforms state-of-the-art methods in terms of precision,recall,Matthews correlation coefficient(MCC),area under the curve(AUC),and overall robustness.Notably,on a particularly challenging test set composed of RNA structures containing junctions,RLsite surpasses the second-best method by 7.3%in precision,3.4%in recall,7.5%in MCC,and 10.8%in AUC,highlighting its potential as a powerful tool for RNA-targeted molecular design.展开更多
Vesicles of lipid bilayer can adopt a variety of shapes due to different coating proteins.The ability of proteins to reshape membrane is typically characterized by inducing spontaneous curvature of the membrane at the...Vesicles of lipid bilayer can adopt a variety of shapes due to different coating proteins.The ability of proteins to reshape membrane is typically characterized by inducing spontaneous curvature of the membrane at the coated area.BAR family proteins are known to have a crescent shape and can induce membrane curvature along their concaved body axis but not in the perpendicular direction.We model this type of proteins as a rod-shaped molecule with an orientation and induce normal curvature along its orientation in the tangential plane of the membrane surface.We show how a ring of these proteins reshapes an axisymmetric vesicle when the protein curvature or orientation is varied.A discontinuous shape transformation from a protrusion shape without a neck to a one with a neck is found.Increasing the rigidity of the protein ring is able to smooth out the transition.Furthermore,we show that varying the protein orientation is able to induce an hourglass-shaped neck,which is significantly narrower than the reciprocal of the protein curvature.Our results offer a new angle to rationalize the helical structure formed by many proteins that carry out membrane fission functions.展开更多
文摘启动子和增强子之间的相互作用(Promoter-Enhancer interaction,PEI)与基因的转录与调控密切相关。本文以人B淋巴细胞系(GM12878)为研究对象,基于染色质环(Loop)数据库构建了启动子-增强子(Promoter-Enhancer,P-E)相互作用数据集,分析了P-E结构中149种转录因子(Transcription factor,TF)以及11种组蛋白修饰(Histone madification,HM)的相关性,筛选出与P-E结构具有较强关联的表观遗传修饰特征,并利用卷积神经网络(Convolutional neural network,CNN)和随机森林(Random forest,RF)算法预测了P-E相互作用对。结果显示RF预测的AUC值(Area under the curve)介于0.84至0.88之间,而CNN的AUC值在0.69至0.77之间,表明RF的预测性能略优于CNN。此外,仅使用TF信号作为特征的AUC值优于仅使用HM信号的情况,表明TF信号对P-E结构的识别具有更佳的效果。最后将TF和HM特征组合后,预测效果能够进一步提升,我们发现EGR1、H3K4me2、EP300等12种特征是预测PEI的重要特征。
文摘In the year 1971,the world’s biggest structural biology collaboration name—The Research Collaboratory for Structural Bioinformatics(RCSB),was formed to gather all the structural biologists at a single platform and then extended out to be the world’s most extensive structural data repository named RCSB-Protein Data Bank(PDB)(https://www.rcsb.org/)that has provided the service for more than 50 years and continues its legacy for the discoveries and repositories for structural data.The RCSB has evolved from being a collaboratory network to a full-fledged database and tool with a huge list of protein structures,nucleic acid-containing structures,ModelArchive,and AlphaFold structures,and the best is that it is expanding day by day with computational advancement with tools and visual experiences.In this review article,we have discussed how RCSB has been a successful collaboratory network,its expansion in each decade,and how it has helped the ground-breaking research.The PDB tools that are helping the researchers,yearly data deposition,validation,processing,and suggestions that can help the developer improve for upcoming years are also discussed.This review will help future researchers understand the complete history of RCSB and its developments in each decade and how various future collaborative networks can be developed in various scientific areas and can be successful by keeping RCSB as a case study.
基金supported by the National Natural Science Foundation of China(Grant No.32371284)the Open Fund of the State Key Laboratory of Optoelectronic Materials and Technologies,Sun Yatsen University(Grant No.OEMT-2024-ZTS-04)support from the Physical Research Platform in the School of Physics,Sun Yatsen University(Grant No.PRPSP,SYSU).
文摘DNA imaging and visualization techniques are crucial in biological experiments and have also emerged as a powerful method for single-molecule studies.Traditional intercalating dyes(e.g.,SYTOX,EtBr,GelRed)can stain DNA but may alter its structure and mechanical properties,and cause photocleavage.Recently,a novel fluorescent DNA-binding protein(FP-DBP)was introduced,which can stain DNA without sequence preference and without inducing photocleavage.In this study,using a custom-built magnetic tweezers system,we performed DNA stretching,twisting and unzipping experiments to compare the mechanical properties of DNA with and without two kinds of intercalating dyes(SYTOX Orange and GelRed)and mCherry FP-DBP.Our results show that mCherry FP-DBP does not affect DNA structure or mechanics,unlike SYTOX Orange and GelRed,making FP-DBP a promising tool for DNA visualization in single-molecule experiments.
基金supported by the National Natural Science Foundation of China(Grant No.12204118)the Guizhou University Talent Fund(Grant No.[2022]30).
文摘Accurate identification of RNA-ligand binding sites is essential for elucidating RNA function and advancing structurebased drug discovery.Here,we present RLsite,a novel deep learning framework that integrates energy-,structure-and sequence-based features to predict nucleotide-level binding sites with high accuracy.RLsite leverages energy-based threedimensional representations,obtained from atomic probe interactions using a pre-trained ITScore-NL potential,and models their contextual features through a 3D convolutional neural network(3D-CNN)augmented with self-attention.In parallel,structure-based features,including network properties,Laplacian norm,and solvent-accessible surface area,together with sequence-based evolutionary constraint scores,are mapped along the RNA sequence and used as sequential descriptors.These descriptors are modeled using a bidirectional long short-term memory(BiLSTM)network enhanced with multihead self-attention.By effectively fusing these complementary modalities,RLsite achieves robust and precise binding site prediction.Extensive evaluations across four diverse RNA-ligand benchmark datasets demonstrate that RLsite consistently outperforms state-of-the-art methods in terms of precision,recall,Matthews correlation coefficient(MCC),area under the curve(AUC),and overall robustness.Notably,on a particularly challenging test set composed of RNA structures containing junctions,RLsite surpasses the second-best method by 7.3%in precision,3.4%in recall,7.5%in MCC,and 10.8%in AUC,highlighting its potential as a powerful tool for RNA-targeted molecular design.
基金support from the the National Natural Science Foundation of China(Grant Nos.12474199(RM)and 12374213(YC))Fundamental Research Funds for Central Universities of China(Grant No.20720240144(RM))111 Project(Grant No.B16029).
文摘Vesicles of lipid bilayer can adopt a variety of shapes due to different coating proteins.The ability of proteins to reshape membrane is typically characterized by inducing spontaneous curvature of the membrane at the coated area.BAR family proteins are known to have a crescent shape and can induce membrane curvature along their concaved body axis but not in the perpendicular direction.We model this type of proteins as a rod-shaped molecule with an orientation and induce normal curvature along its orientation in the tangential plane of the membrane surface.We show how a ring of these proteins reshapes an axisymmetric vesicle when the protein curvature or orientation is varied.A discontinuous shape transformation from a protrusion shape without a neck to a one with a neck is found.Increasing the rigidity of the protein ring is able to smooth out the transition.Furthermore,we show that varying the protein orientation is able to induce an hourglass-shaped neck,which is significantly narrower than the reciprocal of the protein curvature.Our results offer a new angle to rationalize the helical structure formed by many proteins that carry out membrane fission functions.
