由NMR获取原子间距离约束计算蛋白质三维结构

提出一种以核磁共振(NMR)技术获取蛋白质分子多肽链中原于对(主要是H—H对)的距离约束,来计算蛋白质在溶液中的三维结构的方法。这种方法把肽平面之间的二面角当作独立变量,通过从局部到整体逐渐最优化的方法使适当构造的目标函数最小,计算出这些二面角,以及主链每个残基上六种原子N、H~N、C~α、H~α、C′、O的空间坐标.本方法已编写成计算程序DISNMA,并以碱性胰蛋白酶抑制剂(BPTI)为标准结构,得到了很好的验证.     

由NMR获取原子间距离约束计算蛋白质三维结构

提出一种以核磁共振(NMR)技术获取蛋白质分子多肽链中原于对(主要是H-H对)的距离约束,来计算蛋白质在溶液中的三维结构的方法。这种方法把肽平面之间的二面角当作独立变量,通过从局部到整体逐渐最优化的方法使适当构造的目标函数最小,计算出这些二面角,以及主链每个残基上六种原子N、H^N、C^α、H^α、C'、O的空间坐标.本方法已编写成计算程序DISNMA,并以碱性胰蛋白酶抑制剂(BPTI)为标准结构,得到了很好的验证.     

蛋白质分子中生物能量传输基本方程椭圆波解的讨论

在庞小峰关于蛋白质分子能量传输基本方程的基础上,求出了该方程的另一类解析解－－椭圆皮解。并验证了孤子解的存在性。还获得了椭圆波解的质量、动量和能量表达工。     

基于克隆选择的混合遗传算法在碳纳米管结构优化中的研究

针对分子动力学模拟中碳纳米管的结构优化问题，提出了一种新的优化算法.新的优化算法在遗传算法的基础上，引入了克隆选择机理和模拟退火技术.对五个典型函数的优化测试结果表明，该算法搜索过程稳定性好，可较好地实现全局最优.将其应用于碳纳米管原子结构优化，加快了能量优化速度，提高了优化质量.模拟结果说明，混合遗传算法的优化时间随原子数增加而呈线性增长.在碳纳米管原子数较多时，结构优化时间比共轭梯度法降低一个数量级左右，大大降低了系统的模拟时间. 关键词： 分子动力学 碳纳米管 能量优化 遗传算法 克隆选择算法     

C60、C240、C60@C240富勒烯分子压缩特性的分子动力学研究

采用Tersoff-Brenner势的分子动力学方法,研究了双石墨层作用下C60、C240及C60@C240富勒烯分子的压缩力学特性.根据计算结果,讨论了三种分子压缩过程中几何构形、能量、压缩载荷等的变化及其差异.研究表明,压缩过程中,仅C240分子出现了“塌陷“现象,塌陷时,该分子的能量及外载一度下降;相同压缩应变下,C240的体积压缩率以及C60@C240的能量吸收率最大,而C60的体积压缩率及能量吸收率均最小; C60@C240分子的最大承载能力及C240的最大承受变形能力最大,而C60分子的最大承载和最大承受变形能力均最小;在C60@C240分子的压缩中,当应变小于20%时,内笼C60的体积及其能量变化很小;C60与C240之间的范德华尔能在整个压缩C60@C240分子的能量变化中仅仅占有非常小的份额.     

蛋白质溶液结构及动力学的核磁共振研究

高场液相核磁共振技术作为解析高分辨率蛋白质结构的两大主要手段之一,在近二十几年的时间里得到了迅猛的发展. 一方面,随着谱仪硬件技术、核磁脉冲技术和蛋白质标记技术的不断发展,液相核磁共振技术所能够研究的蛋白质不断突破分子量的限制,可以达到几万,甚至几十万. 另一方面,液相核磁共振技术成功地应用于蛋白质分子动力学的研究中,是目前唯一能够对蛋白质多个位点同时进行动力学研究的实验方法,并且仍在不断地创新、发展和完善中. 本文从蛋白质溶液结构的解析和动力学的研究两个主要方面对液相核磁共振研究的基本方法进行简要的介绍,并结合实例介绍一些最新的研究进展.     

距离几何法计算多肽溶液三维结构的初步探讨

度量矩阵距离几何法是一种计算分子三维结构的算法,初步探讨了它的理论及其实际的应用,在SGI工作站SYBYL平台上改进了原有程序,并以BUSHⅡA为实例与DIANA方法和SYBYL原程序做了比较和讨论.此外,还提出一个有关三角约束的推测.     

蛋白质分子核磁共振谱峰的特性及其化学位移归属

尽可能完全、准确地归属蛋白质分子的核磁共振（Nuclear Magnetic Resonance,NMR）谱峰,是解析可信赖、高质量的蛋白质三维空间溶液结构的首要条件．自动归属软件的开发和应用,已经方便并加快了蛋白质分子核磁共振谱峰的归属进程．然而,对蛋白质核磁共振研究领域的新手来说,因为缺乏对蛋白质分子的核磁共振谱峰特性的系统认识而可能发生对自动归属结果的错误指认或指认不完全,从而导致蛋白质结构解析的错误或偏差．该文针对蛋白质分子中的核磁共振谱峰特性,比如同位素效应和立体异构等,结合具体的蛋白质分子的核磁共振实验图谱,进行了较为详尽的论述,期望对从事蛋白质核磁共振的研究者在理解蛋白质分子的核磁共振谱峰特性及其归属方面有所裨益．     

激光—激光子相互作用蛋白质能量传输模型的数值模拟研究

引入了一个新的模型来描述蛋白质子中Ａｍｉｄｅ－Ⅰ振动能量的贮与传输。这种模型是在Ｄａｖｙｄｏｖ模型的基础上加以改进，引入激子的相互作用项。并用数值模拟的方法说明了该模型可以存在静止和运动的局域模式。     

在三通道α-螺旋蛋白质中传递生物能量的孤子的特性

用庞小峰先生提出的生物能量传递的新理论和 Runge-Kutta数值模拟方法,研究了三通道α-螺旋蛋白质中激发的孤子的动力学特性,求出在0K和300K温度下该孤子稳定地沿蛋白质链传递.由此可见,它能担任在蛋白质分子中传递生物能量的功能.从而再次证实了新理论的可利用性.     

蛋白质三维结构的定量比较与立体显示

介绍了我们自行设计的两个计算软件COMP和DRAW,COMP用于定量叠合比较一组蛋白质分子的三维空间结构.DRAW用于显示蛋白质分子在三维坐标空间的立体图案.     

三维流线上风方法

1引言在流场的数值模拟中，为了消除高雷诺数流动中数值的不稳定和非物理振荡，普遍采用能反映流动物理本质的上风方法。在有限元法中，上风法主要有三种表达形式：（1）采用有上风特性的权函数，如SUPG法山；你对流项和扩散项分别离散，对流项直接采用上游点作为积分点，如MonotoneStreamelineUpwind法［‘］及SkewedPositly，CoeficientUpwind法［’］；由用特征法处理非定常的对流扩散方程，使其具有上风特性，采用传统的Galerkin法离散方程，如TaylorGalerkin法＊。ttice及SchniPke门提出的一种流线上风方法能方便地应用于已有的…     

Tip models and force definitions in molecular dynamics simulations of scanning force microscopy

The definition of the time varying force on a tip with internal degrees of freedom in atomistic molecular dynamics (MD) simulations of scanning force microscopy experiments is discussed. We show that the static expression for the tip force is inadequate for calculating force fluctuations within the MD simulations and suggest a different method of calculating the tip force. By studying the size of tip force fluctuations for different tip models and various tip positions with respect to the surface, we demonstrate that the new method works equally well in both static and dynamic cases.     

Nanoscale thermal cloaking by in-situ annealing silicon membrane

With the advent of thermal metamaterials, many new thermal functionalities have been proposed, like thermal cloaking, concentrating, etc. However, these thermal functionalities are based on the transformation thermotics or scattering cancellation technique, which, derived from Fourier's law, cannot apply to the micro-/nanoscale counterparts. In this paper, we design a nanoscale thermal cloak based on a crystalline silicon (Si) membrane and investigate the in-plane phonon transport via non-equilibrium molecular dynamics (NEMD) simulation by in-situ tuning the thermal conductivity of the thermal cloak from crystalline Si to amorphous Si. The two-dimensional temperature profile is obtained, and the thermal cloaking effect is evaluated by the ratio of heat flux. By analyzing the phonon density of state (PDOS) and the mode participation ratio (MPR), the mechanism can be attributed to the phonon localization in the annealed cloaking region. The proposed nanoscale thermal cloak by in-situ tuned thermal conductivity, may trigger the development of nanoscale thermal functionalities and open avenues for and thermal management for nano-photonics and nano-electronics.     

1H NMR study of N(CH3)4H(ClF2CCOO)2

The proton spin–lattice relaxation times and ¹H NMR second moments were measured over a wide range of temperature. The results were compared with those of the ¹⁹F NMR relaxation that we obtained earlier. For both nuclear species, the evolution of the longitudinal magnetizations with time is observed to be strongly bi-exponential and were in good quantitative agreement with the cross-relaxation theory.     

分析复杂化学及生物体系分子动力学模拟轨迹的聚类方法

Molecular dynamics (MD) simulation has become a powerful tool to investigate the structurefunction relationship of proteins and other biological macromolecules at atomic resolution and biologically relevant timescales. MD simulations often produce massive datasets containing millions of snapshots describing proteins in motion. Therefore, clustering algorithms have been in high demand to be developed and applied to classify these MD snapshots and gain biological insights. There mainly exist two categories of clustering algorithms that aim to group protein conformations into clusters based on the similarity of their shape (geometric clustering) and kinetics (kinetic clustering). In this paper, we review a series of frequently used clustering algorithms applied in MD simulations, including divisive algorithms, agglomerative algorithms (single-linkage, complete-linkage, average-linkage, centroid-linkage and ward-linkage), center-based algorithms (K-Means, K-Medoids, K-Centers, and APM), density-based algorithms (neighbor-based, DBSCAN, density-peaks, and Robust-DB), and spectral-based algorithms (PCCA and PCCA+). In particular, differences between geometric and kinetic clustering metrics will be discussed along with the performances of different clustering algorithms. We note that there does not exist a one-size-fits-all algorithm in the classification of MD datasets. For a specific application, the right choice of clustering algorithm should be based on the purpose of clustering, and the intrinsic properties of the MD conformational ensembles. Therefore, a main focus of our review is to describe the merits and limitations of each clustering algorithm. We expect that this review would be helpful to guide researchers to choose appropriate clustering algorithms for their own MD datasets.     

Progress in correlation spectroscopy at ultra-fast magic-angle spinning: basic building blocks and complex experiments for the study of protein structure and dynamics

Recent progress in multi-dimensional solid-state NMR correlation spectroscopy at high static magnetic fields and ultra-fast magic-angle spinning is discussed. A focus of the review is on applications to protein resonance assignment and structure determination as well as on the characterization of protein dynamics in the solid state. First, the consequences of ultra-fast spinning on sensitivity and sample heating are considered. Recoupling and decoupling techniques at ultra-fast MAS are then presented, as well as more complex experiments assembled from these basic building blocks. Furthermore, we discuss new avenues in biomolecular solid-state NMR spectroscopy that become feasible in the ultra-fast spinning regime, such as sensitivity enhancement based on paramagnetic doping, and the prospect of direct proton detection.     

Effect of thermal annealing on nanoimprinted Cu-Ni alloys using molecular dynamics simulation

The mechanical behaviors of nanoimprinted Cu-Ni alloys before and after annealing were studied using molecular dynamics simulation with a tight-binding potential. The results showed that when the punch is advancing, the punching force obtained from the simulation with a tight-binding potential is lower than with the Morse potential. During and after withdrawing the punch from the specimen, the adhesive phenomena are observed and the large residual stress in the Cu-Ni alloys is induced. During the annealing process, the internal energy of Cu-Ni alloys decreased with increasing the temperature and the component of Cu. In addition, comparing the maximum residual stress in the Cu-Ni alloys with and without annealing treatment, the stress is significantly released after annealing, especially in the higher component of Ni.