The folding of many small proteins is kinetically a two-state process with one major free-energy barrier to overcome,which can be roughly regarded as the inverse process of unfolding.In this work,we first use a Gaussi...The folding of many small proteins is kinetically a two-state process with one major free-energy barrier to overcome,which can be roughly regarded as the inverse process of unfolding.In this work,we first use a Gaussian network model to predict the folding nucleus corresponding to the major free-energy barrier of protein 2 GB1,and find that the folding nucleus is located in theβ-sheet domain.High-temperature molecular dynamics simulations are then used to investigate the unfolding process of 2 GB1.We draw free-energy surface from unfolding simulations,taking RMSD and contact number as reaction coordinates,which confirms that the folding of 2 GB1 is kinetically a two-state process.The comparison of the contact maps before and after the free energy barrier indicates that the transition from native to non-native structure of the protein is kinetically caused by the destruction of theβ-sheet domain,which manifests that the folding nucleus is indeed located in theβ-sheet domain.Moreover,the constrained MD simulation further confirms that the destruction of the secondary structures does not alter the topology of the protein retained by the folding nucleus.These results provide vital information for upcoming researchers to further understand protein folding in similar systems.展开更多
7月10-14日,为了纪念豪士科集团成立100周年,豪士科集团子公司、全球领先的高空作业平台及伸缩臂叉装车制造商JLG（捷尔杰）于全球范围内开展了为期1周的Good to Give Back公益周（以下简称：G2GB公益周）,以此凸显JLG＂关注安全、珍爱...7月10-14日,为了纪念豪士科集团成立100周年,豪士科集团子公司、全球领先的高空作业平台及伸缩臂叉装车制造商JLG（捷尔杰）于全球范围内开展了为期1周的Good to Give Back公益周（以下简称：G2GB公益周）,以此凸显JLG＂关注安全、珍爱生命＂的精神传承与发展理念。展开更多
为精确表述公共交通资源的分布特征,进而准确衡量公共交通服务的公平性,以公交可达性作为公共交通资源度量指标,考虑可达性数据统计特性,选取对数正态(Logarithmic Normal,Lognormal)、对数Logistic(Fisk)、伽玛(Gamma)、韦伯(Weibull)...为精确表述公共交通资源的分布特征,进而准确衡量公共交通服务的公平性,以公交可达性作为公共交通资源度量指标,考虑可达性数据统计特性,选取对数正态(Logarithmic Normal,Lognormal)、对数Logistic(Fisk)、伽玛(Gamma)、韦伯(Weibull)、Singh-Maddala(SM)、Dagum、第二类Beta(Beta of the Second Kind, B2)和广义第二类Beta(Generalized Beta of the Second Kind,GB2)8种分布函数对公交可达性数据进行拟合,并检验各分布函数的拟合效果,从而寻找对公交可达性数据拟合效果最佳的分布函数。计算结果显示,各分布函数拟合效果从优至劣排序为:GB2> B2> Dagum>SM>Fisk>Lognormal>Weibull>Gamma,即四参数分布函数的拟合效果优于三参数分布函数,三参数分布函数的拟合效果优于两参数分布函数。研究表明:四参数GB2分布函数对公交可达性数据的拟合效果最佳,可更准确地体现出公共交通资源的分配情况。展开更多
基金Project supported by the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA17010504)the National Natural Science Foundation of China(Grant No.11947302)。
文摘The folding of many small proteins is kinetically a two-state process with one major free-energy barrier to overcome,which can be roughly regarded as the inverse process of unfolding.In this work,we first use a Gaussian network model to predict the folding nucleus corresponding to the major free-energy barrier of protein 2 GB1,and find that the folding nucleus is located in theβ-sheet domain.High-temperature molecular dynamics simulations are then used to investigate the unfolding process of 2 GB1.We draw free-energy surface from unfolding simulations,taking RMSD and contact number as reaction coordinates,which confirms that the folding of 2 GB1 is kinetically a two-state process.The comparison of the contact maps before and after the free energy barrier indicates that the transition from native to non-native structure of the protein is kinetically caused by the destruction of theβ-sheet domain,which manifests that the folding nucleus is indeed located in theβ-sheet domain.Moreover,the constrained MD simulation further confirms that the destruction of the secondary structures does not alter the topology of the protein retained by the folding nucleus.These results provide vital information for upcoming researchers to further understand protein folding in similar systems.
文摘为精确表述公共交通资源的分布特征,进而准确衡量公共交通服务的公平性,以公交可达性作为公共交通资源度量指标,考虑可达性数据统计特性,选取对数正态(Logarithmic Normal,Lognormal)、对数Logistic(Fisk)、伽玛(Gamma)、韦伯(Weibull)、Singh-Maddala(SM)、Dagum、第二类Beta(Beta of the Second Kind, B2)和广义第二类Beta(Generalized Beta of the Second Kind,GB2)8种分布函数对公交可达性数据进行拟合,并检验各分布函数的拟合效果,从而寻找对公交可达性数据拟合效果最佳的分布函数。计算结果显示,各分布函数拟合效果从优至劣排序为:GB2> B2> Dagum>SM>Fisk>Lognormal>Weibull>Gamma,即四参数分布函数的拟合效果优于三参数分布函数,三参数分布函数的拟合效果优于两参数分布函数。研究表明:四参数GB2分布函数对公交可达性数据的拟合效果最佳,可更准确地体现出公共交通资源的分配情况。
