3-dimension HPNX offiattice model is developed from the 2-dimension HP offiattice model. In the HP model, 20 types of amino acid monomers are divided into two classes, H （non-polar monomer） and P （polar monomer）. ...3-dimension HPNX offiattice model is developed from the 2-dimension HP offiattice model. In the HP model, 20 types of amino acid monomers are divided into two classes, H （non-polar monomer） and P （polar monomer）. In the HPNX model, polar monomers are split into positively charged （P）, negatively charged （N） and neutral （X） monomers. A new evolutionary algorithm is applied to study long chains of the HPNX offiattice protein model. This method successfully predict the structures of several proteins in the 3-dimension space that are similar to the structures gotten by X-Ray Crystallography and NMR and published in the PDB（Protein Data Bank）.展开更多
This paper describes a case study of 3D protein structure prediction of six sequences from protein data bank （PDB） by genetic algorithm and tabu search （GATS）, where off-lattice AB model is considered as a simplif...This paper describes a case study of 3D protein structure prediction of six sequences from protein data bank （PDB） by genetic algorithm and tabu search （GATS）, where off-lattice AB model is considered as a simplified model of protein structure. The lowest-energy values required for forming the native conformation of proteins are searched by GATS, and then the coarse structures （i.e., simplified structure） of the proteins are obtained according to the multiple angle parameters corresponding to the lowest energies. All the coarse structures form single hydrophobic cores surrounded by hydrophilic residues, which stay on the right side of the actual characteristic of protein structure. It demonstrates that this approach can predict the 3D protein structure effectively.展开更多
Experimental X-ray crystallography, NMR (Nuclear Magnetic Resonance) spectroscopy, dual polarization interferometry, etc. are indeed very powerful tools to determine the 3-Dimensional structure of a protein (including...Experimental X-ray crystallography, NMR (Nuclear Magnetic Resonance) spectroscopy, dual polarization interferometry, etc. are indeed very powerful tools to determine the 3-Dimensional structure of a protein (including the membrane protein);theoretical mathematical and physical computational approaches can also allow us to obtain a description of the protein 3D structure at a submicroscopic level for some unstable, noncrystalline and insoluble proteins. X-ray crystallography finds the X-ray final structure of a protein, which usually need refinements using theoretical protocols in order to produce a better structure. This means theoretical methods are also important in determinations of protein structures. Optimization is always needed in the computer-aided drug design, structure-based drug design, molecular dynamics, and quantum and molecular mechanics. This paper introduces some optimization algorithms used in these research fields and presents a new theoretical computational method—an improved LBFGS Quasi-Newtonian mathematical optimization method—to produce 3D structures of prion AGAAAAGA amyloid fibrils (which are unstable, noncrystalline and insoluble), from the potential energy minimization point of view. Because the NMR or X-ray structure of the hydrophobic region AGAAAAGA of prion proteins has not yet been determined, the model constructed by this paper can be used as a reference for experimental studies on this region, and may be useful in furthering the goals of medicinal chemistry in this field.展开更多
It has been shown that the progress in the determination of membrane protein structure grows exponentially, with approximately the same growth rate as that of the water-soluble proteins. In order to investigate the ef...It has been shown that the progress in the determination of membrane protein structure grows exponentially, with approximately the same growth rate as that of the water-soluble proteins. In order to investigate the effect of this, on the performance of prediction algorithms for both α-helical and β-barrel membrane proteins, we conducted a prospective study based on historical records. We trained separate hidden Markov models with different sized training sets and evaluated their performance on topology prediction for the two classes of transmembrane proteins. We show that the existing top-scoring algorithms for predicting the transmembrane segments of α-helical membrane proteins perform slightly better than that of β-barrel outer membrane proteins in all measures of accuracy. With the same rationale, a metaoanalysis of the performance of the secondary structure prediction algorithms indicates that existing algorithmic techniques cannot be further improved by just adding more non-homologous sequences to the training sets. The upper limit for secondary structure prediction is estimated to be no more than 70% and 80% of correctly predicted residues for single sequence based methods and multiple sequence based ones, respectively. Therefore, we should concentrate our efforts on utilizing new techniques for the development of even better scoring predictors.展开更多
Dynamic regulation of histone methylation/demethylation plays an important role during development. Mutations and truncations in human plant homeodomain （PHD） finger protein 8 （PHF8） are associated with X-linked m...Dynamic regulation of histone methylation/demethylation plays an important role during development. Mutations and truncations in human plant homeodomain （PHD） finger protein 8 （PHF8） are associated with X-linked mental retardation and facial anomalies, such as a long face, broad nasal tip, cleft lip/cleft palate and large hands, yet its molecular function and structural basis remain unclear. Here, we report the crystal structures of the catalytic core of PHF8 with or without α-ketoglutarate （α-KG） at high resolution. Biochemical and structural studies reveal that PHF8 is a novel histone demethylase specific for di- and mono-methylated histone H3 lysine 9 （H3K9me2/1）, but not for H3K9me3. Our analyses also reveal how human PHF8 discriminates between methylation states and achieves sequence specificity for methylated H3K9. The in vitro demethylation assay also showed that the F279S mutant observed in clinical patients possesses no demethylation activity, suggesting that loss of enzymatic activity is crucial for pathogenesis of PHF8 patients. Taken together, these results will shed light on the molecular mechanism underlying PHF8-associated developmental and neurological diseases.展开更多
G蛋白偶联受体(G protein coupled receptors,GPCRs)是人体内最大的膜受体蛋白家族,具有保守的7次跨膜螺旋结构.GPCR可识别细胞外的各种信号分子,如激素、神经递质、离子、光、气味分子等,与之结合后发生构象改变,随后与细胞内的效应蛋...G蛋白偶联受体(G protein coupled receptors,GPCRs)是人体内最大的膜受体蛋白家族,具有保守的7次跨膜螺旋结构.GPCR可识别细胞外的各种信号分子,如激素、神经递质、离子、光、气味分子等,与之结合后发生构象改变,随后与细胞内的效应蛋白(包括G蛋白、GPCR激酶GRK和阻遏蛋白)相互作用,从而诱导各种细胞反应.作为分布最广泛的细胞表面蛋白,GPCR在所有重要的生理活动中发挥不可或缺的功能作用,是心血管疾病、神经系统疾病、炎症、代谢性疾病、癌症等多种疾病的重要药物靶点.美国食品药品监督管理局(FDA)批准的药物中约34%以GPCR为作用靶点,2011~2015年间,GPCR药物的销售份额占据全球上市药物的27%.近年来,GPCR的结构生物学研究取得了长足的发展,研究成果揭示了GPCR对配体识别和信号转导的分子机制,并为基于结构的药物研发提供了重要信息.本文详细介绍GPCR的结构研究与药物研发进展,并就GPCR结构和功能研究的未来发展方向提出建议.展开更多
基金Supported by the National Natural Science Foundation of China (1027109)
文摘3-dimension HPNX offiattice model is developed from the 2-dimension HP offiattice model. In the HP model, 20 types of amino acid monomers are divided into two classes, H （non-polar monomer） and P （polar monomer）. In the HPNX model, polar monomers are split into positively charged （P）, negatively charged （N） and neutral （X） monomers. A new evolutionary algorithm is applied to study long chains of the HPNX offiattice protein model. This method successfully predict the structures of several proteins in the 3-dimension space that are similar to the structures gotten by X-Ray Crystallography and NMR and published in the PDB（Protein Data Bank）.
基金Supported by the National Natural Science Foundation of China (60975031)the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Ministry of Education of China, the Open Foundation of State Key Laboratory of Bioelectronics of Southeast University, China, and the Natural Science Foundation of Hubei Province, China (2008CDB344 and 2009CDA034)
文摘This paper describes a case study of 3D protein structure prediction of six sequences from protein data bank （PDB） by genetic algorithm and tabu search （GATS）, where off-lattice AB model is considered as a simplified model of protein structure. The lowest-energy values required for forming the native conformation of proteins are searched by GATS, and then the coarse structures （i.e., simplified structure） of the proteins are obtained according to the multiple angle parameters corresponding to the lowest energies. All the coarse structures form single hydrophobic cores surrounded by hydrophilic residues, which stay on the right side of the actual characteristic of protein structure. It demonstrates that this approach can predict the 3D protein structure effectively.
文摘Experimental X-ray crystallography, NMR (Nuclear Magnetic Resonance) spectroscopy, dual polarization interferometry, etc. are indeed very powerful tools to determine the 3-Dimensional structure of a protein (including the membrane protein);theoretical mathematical and physical computational approaches can also allow us to obtain a description of the protein 3D structure at a submicroscopic level for some unstable, noncrystalline and insoluble proteins. X-ray crystallography finds the X-ray final structure of a protein, which usually need refinements using theoretical protocols in order to produce a better structure. This means theoretical methods are also important in determinations of protein structures. Optimization is always needed in the computer-aided drug design, structure-based drug design, molecular dynamics, and quantum and molecular mechanics. This paper introduces some optimization algorithms used in these research fields and presents a new theoretical computational method—an improved LBFGS Quasi-Newtonian mathematical optimization method—to produce 3D structures of prion AGAAAAGA amyloid fibrils (which are unstable, noncrystalline and insoluble), from the potential energy minimization point of view. Because the NMR or X-ray structure of the hydrophobic region AGAAAAGA of prion proteins has not yet been determined, the model constructed by this paper can be used as a reference for experimental studies on this region, and may be useful in furthering the goals of medicinal chemistry in this field.
基金PGB was supported by a scholarship from the State Scholarships Foundation of Greece (SSF) for postdoctoral research in the Department of Cell Biology and Biophysics of the University of Athens (Machine Learning Algorithms for Bioinformatics)
文摘It has been shown that the progress in the determination of membrane protein structure grows exponentially, with approximately the same growth rate as that of the water-soluble proteins. In order to investigate the effect of this, on the performance of prediction algorithms for both α-helical and β-barrel membrane proteins, we conducted a prospective study based on historical records. We trained separate hidden Markov models with different sized training sets and evaluated their performance on topology prediction for the two classes of transmembrane proteins. We show that the existing top-scoring algorithms for predicting the transmembrane segments of α-helical membrane proteins perform slightly better than that of β-barrel outer membrane proteins in all measures of accuracy. With the same rationale, a metaoanalysis of the performance of the secondary structure prediction algorithms indicates that existing algorithmic techniques cannot be further improved by just adding more non-homologous sequences to the training sets. The upper limit for secondary structure prediction is estimated to be no more than 70% and 80% of correctly predicted residues for single sequence based methods and multiple sequence based ones, respectively. Therefore, we should concentrate our efforts on utilizing new techniques for the development of even better scoring predictors.
基金Supplementary information is linked to the online version of the paper on the Cell Research website.Acknowledgments We thank Dr Dawei Li （China Agricultural University） for generously providing us with the experimental conditions during the early stages of this project. We thank Dr Ruiming Xu （Institute of Biophysics, Chinese Academy of Sciences） for critical reading of this manuscript and advice. We thank Dr Pinchao Mei （Chinese Academy of Medical Sciences and Peking Union Medical College）, Xinqi Liu （Nankai University） and Jiemin Wong （East China Normal University） for discussions and advice. The synchrotronradiation experiments were performed at Shanghai Synchrotron Radiation Facility （SSRF） and NE3A in the Photon Factory. Z.C. is supported by the National Basic Research Program of China （973 Program, 2009CB825501）, the National Natural Science Foundation of China （30870494 and 90919043）, the New Century Excellent Talents in University （NCET-07-0808） and the Innovative Project of SKLAB. S. H. is supported by the National Key Laboratory Special Fund 2060204. Z. D. is supported by the National Natural Science Foundation of China （J0730639）.
文摘Dynamic regulation of histone methylation/demethylation plays an important role during development. Mutations and truncations in human plant homeodomain （PHD） finger protein 8 （PHF8） are associated with X-linked mental retardation and facial anomalies, such as a long face, broad nasal tip, cleft lip/cleft palate and large hands, yet its molecular function and structural basis remain unclear. Here, we report the crystal structures of the catalytic core of PHF8 with or without α-ketoglutarate （α-KG） at high resolution. Biochemical and structural studies reveal that PHF8 is a novel histone demethylase specific for di- and mono-methylated histone H3 lysine 9 （H3K9me2/1）, but not for H3K9me3. Our analyses also reveal how human PHF8 discriminates between methylation states and achieves sequence specificity for methylated H3K9. The in vitro demethylation assay also showed that the F279S mutant observed in clinical patients possesses no demethylation activity, suggesting that loss of enzymatic activity is crucial for pathogenesis of PHF8 patients. Taken together, these results will shed light on the molecular mechanism underlying PHF8-associated developmental and neurological diseases.
文摘G蛋白偶联受体(G protein coupled receptors,GPCRs)是人体内最大的膜受体蛋白家族,具有保守的7次跨膜螺旋结构.GPCR可识别细胞外的各种信号分子,如激素、神经递质、离子、光、气味分子等,与之结合后发生构象改变,随后与细胞内的效应蛋白(包括G蛋白、GPCR激酶GRK和阻遏蛋白)相互作用,从而诱导各种细胞反应.作为分布最广泛的细胞表面蛋白,GPCR在所有重要的生理活动中发挥不可或缺的功能作用,是心血管疾病、神经系统疾病、炎症、代谢性疾病、癌症等多种疾病的重要药物靶点.美国食品药品监督管理局(FDA)批准的药物中约34%以GPCR为作用靶点,2011~2015年间,GPCR药物的销售份额占据全球上市药物的27%.近年来,GPCR的结构生物学研究取得了长足的发展,研究成果揭示了GPCR对配体识别和信号转导的分子机制,并为基于结构的药物研发提供了重要信息.本文详细介绍GPCR的结构研究与药物研发进展,并就GPCR结构和功能研究的未来发展方向提出建议.
