虚拟原子探针随机采样法用于氨基酸结构描述及其构效关系研究

考虑药物与蛋白质受体的3类非键作用模式, 利用8类虚拟原子探针和Monte Carlo随机采样技术, 得到了一套新的氨基酸侧链表面静电、立体及疏水势能场(ASSPF)参数. 在此基础上对苦味二肽和血管舒缓激五肽进行了结构表征和QSAR研究, 所建模型复相关系数R2和留一法交互检验复相关系数QLOOCV2分别为0.8457, 0.851和0.7688, 0.7952, 同时分析了肽链不同位置上氨基酸侧链对活性的影响, 取得较好的结果.     

天然产物法卡林二醇与人类GABAA受体相互作用的机制

通过分子动力学模拟、伞形采样模拟、结合自由能计算和分子对接等方法,研究了法卡林二醇在γ-氨基丁酸A型(GABA_A)受体上结合作用的模式和对GABA_A受体动态属性的影响,确定了3个有效结合位点均对此受体产生拮抗作用,为后续研究聚乙炔醇类化合物对GABA_A受体作用及相应药物开发提供了理论依据.     

两步柱色谱法分离纯化重组猪β2-肾上腺素能受体

β2-肾上腺素能受体是细胞表面受体的一种,它能通过偶联异源三聚体G蛋白将信号转导引入到细胞内部。本实验在成功克隆、表达β2-肾上腺素能受体的基础上,建立了一种两步柱色谱分离纯化目的蛋白质的方法。首先利用Ni2+螯合的高分辨纯化的预带电荷介质Sepharose High Performance与含有六聚组氨酸标签的蛋白质特异结合的性质,对目的蛋白质进行初步分离,接着运用快流速Q琼脂糖凝胶(Quaternary Sepharose Fast Flow)对其进行进一步的分离纯化。采用该方法得到的β2-肾上腺素能受体蛋白质经十二烷基硫酸钠-聚丙烯酰胺凝胶电泳(SDS-PAGE)和高效凝胶排阻色谱检测其纯度约为95%。结果表明该方法可以对重组猪β2-肾上腺素能受体进行有效的分离纯化。     

载体材料与蛋白质的相互作用及对其构象的影响

蛋白质与载体材料间存在着疏水性、静电等相互作用力。这些作用力不仅决定了蛋白质分子在载体表面吸附的数量,也导致吸附蛋白质分子构象发生变化,引起蛋白质活性的改变。蛋白质的特性(分子量和浓度等)、载体材料的表面结构(表面化学组成和物理结构等)及溶液性质(pH和离子强度等)对蛋白质与载体材料间的相互作用产生影响。利用各种先进的分析技术对载体材料表面的蛋白质分子构象进行表征是这一研究领域的热点。本文对这一方面的最新研究进展进行综述。     

蛋白质表面模块划分及其在结合位点预测中的应用

蛋白质-蛋白质复合物的结合位点预测是计算分子生物学的一个难题. 本文对蛋白质-蛋白质复合物数据集Benchmark 3.0 中的双链蛋白质复合物进行了研究, 计算了单体的残基溶剂可接近表面积和残基间的接触面积, 并据此提出了蛋白质表面模块划分方法. 发现模块的溶剂可接近表面积与其内部接触面积的乘积(PSAIA)值能够提供结合位点的信息. 在78 个双链蛋白质复合物中, 有74 个体系其受体或配体上具有最大或次大PSAIA值的模块是界面模块. 将该方法获得的结合位点信息应用在CAPRI竞赛Target 39 的复合物结构预测中取得了较好的结果. 本文提出的基于模块的蛋白质结合位点预测方法不同于以残基为基础且仅考虑表面残基的传统预测方法, 为蛋白质-蛋白质复合物结合位点预测提供了新思路.     

表面等离子体共振技术在蛋白质-蛋白质相互作用研究中的应用

表面等离子共振(SPR)近年来迅速发展为用于分析生物分子相互作用的一项技术.该技术无需标记、特异性强、灵敏度高、样品用量小,可实现在线连续实时检测.目前SPR已被广泛应用于免疫学、蛋白质组学、药物筛选、细胞信号转导、受体/配体垂钓等领域.该文阐述了基于表面等离子体共振技术生物传感器的基本原理和技术流程,综述了SPR在蛋白质-蛋白质相互作用动力学研究、蛋白质结构及功能研究、蛋白质突变和碎片分析、信号转导中的应用以及SPR在蛋白质-蛋白质相互作用研究中的多项关键技术.指出SPR通过与光谱、电化学等多技术联用后,可以获得更加详实的信息.     

确定蛋白质-短肽复合物结构的新方法

大部分蛋白质 -蛋白质复合物的三维结构在接触表面都显示出很好的几何匹配 .由于蛋白质的表面几何形状和其它的一些物理化学性质在分子的专一性相互作用中起了主要作用 ,所以 ,接触表面几何形状的互补常常被认为是蛋白质分子识别的基础 .一般来说 ,蛋白质接触表面的几何匹配只涉及 5到 1 0几个紧密堆积的氨基酸残基 ,因此 ,蛋白质与蛋白质配体之间的识别计算可以通过蛋白质与突变周围的或与蛋白质表面紧密接触的配体肽段的识别计算来实现 . Stoddard等 [1] 已经利用从 MBP上选取的八肽成功地计算出接近晶体结构的 MBP-受体复合物 .许多研…     

采用柔性分子对接技术模拟蛋白质在疏水作用色谱上的保留行为

将蛋白质与疏水作用色谱(HIC)固定相相互作用分为直接非键/构象作用和蛋白质表面疏水效应两个热力学过程, 从而定量给出了处于浓盐析盐水溶液中HIC保留时间与配基/蛋白质结合自由能之间的二元线性关系. 通过ICM柔性分子对接策略及遗传算法(GA)对27个已知晶体结构的蛋白质与疏水配基的可能结合方式进行模拟和分析, 所得结果与实验观测情况吻合良好. 研究表明, 蛋白质局部疏水效应以及配基与蛋白质的非键/构象作用皆对HIC色谱保留行为影响显著, 且作用区域多集中于蛋白质表面突出部位.     

电化学石英晶体阻抗和FTIR-ATR研究牛血清白蛋白在羟基磷灰石、TiO2表面的吸附

用电化学石英晶体阻抗法(EQCI)和衰减全反射红外光谱法(FTIR-ATR)研究了牛血清白蛋白(BSA)在纳米生物活性材料TiO_2和羟基磷灰石(HAP)上的吸附行为,获得了BSA吸附过程中电极表面的质量变化和电极/蛋白质界面双电层中电容变化以及BSA构象变化等信息。以2步骤连串反应机理分析BSA吸附动力学。结果表明,BSA在2种电极表面的吸附过程均分为吸附和重排2个过程,BSA在TiO_2上吸附速度慢于在HAP上的吸附,且难达到稳定状态。根据Sauerbrey方程结合Martin方程估算了BSA在TiO_2和HAP上饱和吸附时的表面质量覆盖度,分别为1．12×10~(-6)和1．09×10~(-6)g/cm~2。红外谱图结果还表明,生物材料的表面组成对蛋白质吸附动力学和蛋白质结构变化均有影响。BSA在HAP表面吸附时的响应更大,并对蛋白质二级结构的变化影响更大。     

利用表面上的小分子控制细胞黏附

细胞黏附是重要的生理过程,多细胞生物体中大部分种类的细胞都依赖于在表面的黏附而进行其正常生理活动。细胞的黏附需要固定在表面的有机分子（例如蛋白质或多肽）作配体。我们利用表面小分子模拟蛋白质或多肽作为配体,通过与细胞膜上受体结合,促进细胞黏附到表面。聚乙二醇（PEG）可以抵抗细胞在表面的黏附,我们利用含有PEG的表面小分子来调节细胞黏附。细胞表面的受体与胞外基质表面的配体结合是一个动态过程,在适宜时间和空间发生的时候,细胞就会产生运动和迁移,细胞的迁移也是重要的生理过程。本文主要介绍近年来利用小分子的表面化学和微纳米结构控制细胞在表面的黏附和迁移。     

Conditional random surveying for particle deposition on a mica surface.

In using microscopic imaging techniques, unbiased selection of sampling areas is often critical when judgment has to be used to find regions of interest. A conditional random sampling was designed to survey hematite particles on a mica surface using tapping-mode atomic force microscopy, based on three adapted-systematic-sampling methods designed to exclude subjective bias by limiting the freedom of arbitrarily selecting sampling areas. The results of these surveying methods were compared with the average particle surface density modeled by Poisson distribution. It was found that the conditional random sampling could survey particles effectively and improve the data reliability significantly. Ten population-known images from the same mica sheet were used to evaluate these methods, and an average relative error of 12% (maximum 21%) was obtained using the conditional random method with six sampling areas. It was used to investigate the effects of common organic pollutants, benzene, toluene, ethylbenzene, and xylenes on the transport of soil colloids.     

Essential energy space random walks to accelerate molecular dynamics simulations: convergence improvements via an adaptive-length self-healing strategy

Recently, accelerated molecular dynamics (AMD) technique was generalized to realize essential energy space random walks so that further sampling enhancement and effective localized enhanced sampling could be achieved. This method is especially meaningful when essential coordinates of the target events are not priori known; moreover, the energy space metadynamics method was also introduced so that biasing free energy functions can be robustly generated. Despite the promising features of this method, due to the nonequilibrium nature of the metadynamics recursion, it is challenging to rigorously use the data obtained at the recursion stage to perform equilibrium analysis, such as free energy surface mapping; therefore, a large amount of data ought to be wasted. To resolve such problem so as to further improve simulation convergence, as promised in our original paper, we are reporting an alternate approach: the adaptive-length self-healing (ALSH) strategy for AMD simulations; this development is based on a recent self-healing umbrella sampling method. Here, the unit simulation length for each self-healing recursion is increasingly updated based on the Wang-Landau flattening judgment. When the unit simulation length for each update is long enough, all the following unit simulations naturally run into the equilibrium regime. Thereafter, these unit simulations can serve for the dual purposes of recursion and equilibrium analysis. As demonstrated in our model studies, by applying ALSH, both fast recursion and short nonequilibrium data waste can be compromised. As a result, combining all the data obtained from all the unit simulations that are in the equilibrium regime via the weighted histogram analysis method, efficient convergence can be robustly ensured, especially for the purpose of free energy surface mapping.     

Essential energy space random walk via energy space metadynamics method to accelerate molecular dynamics simulations

To overcome the possible pseudoergodicity problem, molecular dynamic simulation can be accelerated via the realization of an energy space random walk. To achieve this, a biased free energy function (BFEF) needs to be priori obtained. Although the quality of BFEF is essential for sampling efficiency, its generation is usually tedious and nontrivial. In this work, we present an energy space metadynamics algorithm to efficiently and robustly obtain BFEFs. Moreover, in order to deal with the associated diffusion sampling problem caused by the random walk in the total energy space, the idea in the original umbrella sampling method is generalized to be the random walk in the essential energy space, which only includes the energy terms determining the conformation of a region of interest. This essential energy space generalization allows the realization of efficient localized enhanced sampling and also offers the possibility of further sampling efficiency improvement when high frequency energy terms irrelevant to the target events are free of activation. The energy space metadynamics method and its generalization in the essential energy space for the molecular dynamics acceleration are demonstrated in the simulation of a pentanelike system, the blocked alanine dipeptide model, and the leucine model.     

A tessellationless integration grid for the polarizable continuum model reaction field

A new integration grid for the Polarizable Continuum Model reaction field is presented. In this scheme (called TsLess) the molecular surface is not partitioned in tesserae, but a set of sampling points is chosen. These points are weighted according to they position on the surface. The new procedure is tested against the GEPOL tesselation method.     

Mapping electron paramagnetic resonance spin label conformations by the simulated scaling method

In order to efficiently simulate spin label behavior when attached to the protein backbone we developed a novel approach that enhances local conformational sampling. The simulated scaling (SS) approach (Li, H., et al. J. Chem. Phys. 2007, 126, 24106) couples the random walk of a potential scaling parameter and molecular dynamics in the framework of hybrid Monte Carlo. This approach allows efficient barrier crossings between conformations. The method retains the thermodynamic detailed balance allowing for determination of relative free energies between various conformations. The accuracy of our method was validated by comparison with the recently resolved X-ray crystal structure of a spin labeled T4 lysozyme in which the spin label was in the interior of the protein. Consistent potentials of mean force (PMF) are obtained for the spin label torsion angles to illustrate their behavior in various protein environments: surface, semiburied, and buried. These PMFs reflect the experimentally observed trends and provide the rationale for the spin label dynamics. We have used this method to compare an implicit and explicit solvent model in spin label modeling. The implicit model, which is computationally faster, was found to be in excellent agreement with the explicit solvent treatment. Based on this collection of results, we believe that the presented approach has great potential in the general strategy of describing the behavior of the spin label using molecular modeling and using this information in the interpretation of EPR measurements in terms of protein conformation and dynamics.     

Adaptive lambda square dynamics simulation: An efficient conformational sampling method for biomolecules

A novel, efficient sampling method for biomolecules is proposed. The partial multicanonical molecular dynamics (McMD) was recently developed as a method that improved generalized ensemble (GE) methods to focus sampling only on a part of a system (GEPS); however, it was not tested well. We found that partial McMD did not work well for polylysine decapeptide and gave significantly worse sampling efficiency than a conventional GE. Herein, we elucidate the fundamental reason for this and propose a novel GEPS, adaptive lambda square dynamics (ALSD), which can resolve the problem faced when using partial McMD. We demonstrate that ALSD greatly increases the sampling efficiency over a conventional GE. We believe that ALSD is an effective method and is applicable to the conformational sampling of larger and more complicated biomolecule systems. © 2013 Wiley Periodicals, Inc.     

A distance geometry heuristic for expanding the range of geometries sampled during conformational search

A recent study of crystal structures of protein-ligand complexes has shown that bioactive conformations tend to be more extended than random ones (Diller and Merz, J. Comput. Aid. Mol. Des. 2002, 16, 105-112). Existing conformational sampling techniques produce molecular conformations with a distribution of geometric sizes that may not cover that of the bioactive conformations. Here, we describe a simple heuristic for biasing the conformational search toward more extended or compact conformations, while maintaining excellent sampling. The method uses a boosting strategy to generate a series of conformations, each of which is at least as extended (or compact) as the previous one. We demonstrate that this method significantly expands the range of geometric sizes generated during the search and thus increases the efficiency of sampling bioactive conformations.     

Using the local elevation method to construct optimized umbrella sampling potentials: Calculation of the relative free energies and interconversion barriers of glucopyranose ring conformers in water

A method is proposed to combine the local elevation (LE) conformational searching and the umbrella sampling (US) conformational sampling approaches into a single local elevation umbrella sampling (LEUS) scheme for (explicit‐solvent) molecular dynamics (MD) simulations. In this approach, an initial (relatively short) LE build‐up (searching) phase is used to construct an optimized biasing potential within a subspace of conformationally relevant degrees of freedom, that is then used in a (comparatively longer) US sampling phase. This scheme dramatically enhances (in comparison with plain MD) the sampling power of MD simulations, taking advantage of the fact that the preoptimized biasing potential represents a reasonable approximation to the negative of the free energy surface in the considered conformational subspace. The method is applied to the calculation of the relative free energies of β‐D ‐glucopyranose ring conformers in water (within the GROMOS 45A4 force field). Different schemes to assign sampled conformational regions to distinct states are also compared. This approach, which bears some analogies with adaptive umbrella sampling and metadynamics (but within a very distinct implementation), is shown to be: (i) efficient (nearly all the computational effort is invested in the actual sampling phase rather than in searching and equilibration); (ii) robust (the method is only weakly sensitive to the details of the build‐up protocol, even for relatively short build‐up times); (iii) versatile (a LEUS biasing potential database could easily be preoptimized for small molecules and assembled on a fragment basis for larger ones). © 2009 Wiley Periodicals, Inc. J Comput Chem 2010