人类丝氨酸消旋酶的同源模建及其与多肽类抑制剂的分子对接

利用同源模建和分子动力学模拟方法构建了人类丝氨酸消旋酶(hSR)的三维结构, 并利用profile-3D和procheck方法评估了模型的可靠性. 在此基础上用分子对接程序(affinity)将多肽类抑制剂A和B分别与hSR进行对接, 获得了其复合物结构的理论模型. 通过配体与受体之间相互作用能和结构分析给出了此类抑制剂与hSR的具体结合方式, 明确了hSR与此类抑制剂结合时起重要作用的氨基酸残基, 为基于人类丝氨酸消旋酶三维结构的药物设计提供重要的参考信息.     

An integrative in silico approach to the structure of Omp33-36 in Acinetobacter baumannii

Omp33-36 in A. baumannii, a bacterium causing serious nosocomial infections, is a virulence factor associated with the pathogen metabolic fitness as well as its adherence and invasion to human epithelial cells. This protein is also involved in interaction of the bacteria with host cells by binding to fibronectin. Moreover, Omp33-36 renders cytotoxicity to A. baumannii in addition to inducing apoptosis and modulation of autophagy. In the present study, an integrated strategy is launched to pierce into the 3D structure of Omp33-36 protein. The signal peptide within the sequence was determined, then, topology as well as secondary and tertiary structures of the protein were predicted. The mature protein assigned as a 14-stranded barrel in which residues 1–19 is removed as signal peptide. The obtained 3D models were evaluated in terms of quality; and then, served as queries to find similar protein structures. The hits were analyzed regarding topology among which 14-stranded were considered. The most qualified model was refined and then its sequence aligned to its counterpart similar structure protein (CymA from Klebsiella oxytoca). The determined structure of Omp33-36 could justify its porin function and carbapenem-resistance associated with the loss of this protein.     

人类2-氨基3-羧基粘康酸6-半醛脱羧酶(ACMSD)与底物及抑制剂作用模型的理论研究

利用同源模建和分子动力学模拟方法构建了人类2-氨基3-羧基粘康酸6-半醛脱羧酶(hACMSD)的三维结构, 并利用Profile-3D和Procheck等方法评估了模型的可靠性. 在此基础上, 用分子对接程序(Affinity), 将其底物2-氨基3-羧基粘康酸6-半醛(ACMS)和抑制剂喹啉酸(QA)分别与hACMSD进行对接, 获得了复合物结构的理论模型. 通过配体与受体之间相互作用能和结构分析给出了底物和抑制剂的具体结合方式, 明确了hACMSD与底物和抑制剂结合时起重要作用的氨基酸残基.     

A deterministic algorithm for constrained enumeration of transmembrane protein folds

A deterministic algorithm for enumeration of transmembrane protein folds is presented. Using a set of sparse pairwise atomic distance constraints (such as those obtained from chemical cross-linking, FRET, or dipolar EPR experiments), the algorithm performs an exhaustive search of secondary structure element packing conformations distributed throughout the entire conformational space. The end result is a set of distinct protein conformations, which can be scored and refined as part of a process designed for computational elucidation of transmembrane protein structures.     

Using Homology Modeling, Molecular Dynamics and Molecular Docking Techniques to Identify Inhibitor Binding Regions of Somatostatin Receptor 1

The G protein coupled receptor(GPCR), one of the members in the superfamily, which consists of thousands of integral membrane proteins, exerts a wide variety of physiological functions and responses to a large portion of the drug targets. The 3D structure of somatostatin receptor 1(SSTR1) was modeled and refined by means of homology modeling and molecular dynamics simulation. This model was assessed by Verify-3D and Vadar, which confirmed the reliability of the refined model. The interaction between the inhibitor cysteamine, somatostatin(SST) and SSTR1 was investigated by a molecular docking program, Affinity. The binding module not only showed the crucial residues involved in the interaction, but also provided important information about the interaction between SSTR1 on the one hand and ligands on the other, which might be the significant evidence for the structure-based design.     

Protein structure determination by high-resolution solid-state NMR spectroscopy: application to microcrystalline ubiquitin

High-resolution solid-state NMR spectroscopy has become a promising method for the determination of three-dimensional protein structures for systems which are difficult to crystallize or exhibit low solubility. Here we describe the structure determination of microcrystalline ubiquitin using 2D (13)C-(13)C correlation spectroscopy under magic angle spinning conditions. High-resolution (13)C spectra have been acquired from hydrated microcrystals of site-directed (13)C-enriched ubiquitin. Inter-residue carbon-carbon distance constraints defining the global protein structure have been evaluated from 'dipolar-assisted rotational resonance' experiments recorded at various mixing times. Additional constraints on the backbone torsion angles have been derived from chemical shift analysis. Using both distance and dihedral angle constraints, the structure of microcrystalline ubiquitin has been refined to a root-mean-square deviation of about 1 A. The structure determination strategies for solid samples described herein are likely to be generally applicable to many proteins that cannot be studied by X-ray crystallography or solution NMR spectroscopy.     

Binding site elucidation of hydantoin-based antagonists of LFA-1 using multidisciplinary technologies: evidence for the allosteric inhibition of a protein--protein interaction

The binding site on the lymphocyte function-associated antigen-1 (LFA-1) of a class of hydantoin-based antagonists of leukocyte cell adhesion has been identified. This site resides in the inserted-domain (I-domain) of the CD11a chain at a location that is distal to residues known to be required for interactions with the intercellular adhesion molecules. This finding supports the hypothesis that the molecules are antagonizing cell adhesion via an allosteric modification of LFA-1. The binding site was identified using an integrated immunochemical, chemical, and molecular modeling approach. Antibodies that map to epitopes on the I-domain were blocked from binding to the purified protein by the hydantoins, indicating that the hydantoin-binding site resides on the I-domain. Photoaffinity labeling of the I-domain followed by LC/MS and LC/MS/MS analysis of the enzymatic digest identified proline 281 as the primary amino acid residue covalently attached to the photoprobe. Distance constraints derived from this study coupled with known SAR considerations allowed for the construction of a molecular model of the I-domain/inhibitor complex. The atomic details of the protein/antagonist interaction were accurately predicted by this model, as subsequently confirmed by the X-ray crystal structure of the complex.     

膜蛋白跨膜区段的预测分析

将连续小波变换技术的时频局部化特点和氨基酸的疏水特性相结合,提出了一种用于预测膜蛋白跨膜区段数目和位置的新方法,以代码为1YST的膜蛋白为例,对小波尺度和疏水值的种类进行了选择,同时描述了该法对跨膜螺旋区数目和位置的预测分析过程.从膜蛋白数据库中随机抽取36个蛋白质(含跨膜螺旋区232)作为测试集,采用该方法对其跨膜螺旋区进行预测,其中222个跨膜螺旋区能被准确预测,准确率为96.1%.结果表明,该法具有较高的预测准确性.     

A comparison of different functions for predicted protein model quality assessment

In protein structure prediction, a considerable number of models are usually produced by either the Template-Based Method (TBM) or the ab initio prediction. The purpose of this study is to find the critical parameter in assessing the quality of the predicted models. A non-redundant template library was developed and 138 target sequences were modeled. The target sequences were all distant from the proteins in the template library and were aligned with template library proteins on the basis of the transformation matrix. The quality of each model was first assessed with QMEAN and its six parameters, which are C_β interaction energy (C_beta), all-atom pairwise energy (PE), solvation energy (SE), torsion angle energy (TAE), secondary structure agreement (SSA), and solvent accessibility agreement (SAE). Finally, the alignment score (score) was also used to assess the quality of model. Hence, a total of eight parameters (i.e., QMEAN, C_beta, PE, SE, TAE, SSA, SAE, score) were independently used to assess the quality of each model. The results indicate that SSA is the best parameter to estimate the quality of the model.     

Use of 13Calpha chemical shifts in protein structure determination

A physics-based method aimed at determining protein structures by using NOE-derived distances together with observed and computed 13C chemical shifts is proposed. The approach makes use of 13Calpha chemical shifts, computed at the density functional level of theory, to obtain torsional constraints for all backbone and side-chain torsional angles without making a priori use of the occupancy of any region of the Ramachandran map by the amino acid residues. The torsional constraints are not fixed but are changed dynamically in each step of the procedure, following an iterative self-consistent approach intended to identify a set of conformations for which the computed 13Calpha chemical shifts match the experimental ones. A test is carried out on a 76-amino acid, all-alpha-helical protein; namely, the Bacillus subtilis acyl carrier protein. It is shown that, starting from randomly generated conformations, the final protein models are more accurate than an existing NMR-derived structure model of this protein, in terms of both the agreement between predicted and observed 13Calpha chemical shifts and some stereochemical quality indicators, and of similar accuracy as one of the protein models solved at a high level of resolution. The results provide evidence that this methodology can be used not only for structure determination but also for additional protein structure refinement of NMR-derived models deposited in the Protein Data Bank.     

Ab initio modelling of the N-terminal domain of the secretin receptors

G protein coupled receptors of the secretin family are activated by peptide hormones of about 30 residues in length. There is considerable sequence homology within both the hormone and receptor families. The receptors possess in addition to the integral membrane domain a characteristic extracellular domain of about 120 residues in length, having conserved cysteine residues, which are involved in disulphide bridge formation, and tryptophanes, which have been shown to be critical for hormone binding. This extracellular domain does not have detectable homology to any known protein fold. In order to be able to propose a structure for this domain we have used ab initio prediction methods combined with constraints based on experimental results for the disulphide connectivity. The results of computational tools for predicting secondary structure and accessibility, together with ligand binding and mutational data and other structural considerations were used in the ab initio protein folding programs DRAGON and GADGET and also the simpler program RAMBLE, which was able to explore different permutations of disulphide bond connectivity, tryptophan side chain orientation and chain topology. The methods generated a limited number of plausible models but no single unique solution was found under the constraints. One of these was refined into a full atomic model that contained a possible peptide binding site comprising the most conserved residues.     

VoteDock: Consensus docking method for prediction of protein–ligand interactions

Molecular recognition plays a fundamental role in all biological processes, and that is why great efforts have been made to understand and predict protein–ligand interactions. Finding a molecule that can potentially bind to a target protein is particularly essential in drug discovery and still remains an expensive and time‐consuming task. In silico, tools are frequently used to screen molecular libraries to identify new lead compounds, and if protein structure is known, various protein–ligand docking programs can be used. The aim of docking procedure is to predict correct poses of ligand in the binding site of the protein as well as to score them according to the strength of interaction in a reasonable time frame. The purpose of our studies was to present the novel consensus approach to predict both protein–ligand complex structure and its corresponding binding affinity. Our method used as the input the results from seven docking programs (Surflex, LigandFit, Glide, GOLD, FlexX, eHiTS, and AutoDock) that are widely used for docking of ligands. We evaluated it on the extensive benchmark dataset of 1300 protein–ligands pairs from refined PDBbind database for which the structural and affinity data was available. We compared independently its ability of proper scoring and posing to the previously proposed methods. In most cases, our method is able to dock properly approximately 20% of pairs more than docking methods on average, and over 10% of pairs more than the best single program. The RMSD value of the predicted complex conformation versus its native one is reduced by a factor of 0.5 Å. Finally, we were able to increase the Pearson correlation of the predicted binding affinity in comparison with the experimental value up to 0.5. © 2010 Wiley Periodicals, Inc. J Comput Chem 32: 568–581, 2011     

Correlation between 19F environment and isotropic chemical shift in barium and calcium fluoroaluminates

High-speed MAS (19)F NMR spectra are recorded and reconstructed for 10 compounds from BaF(2)-AlF(3) and CaF(2)-AlF(3) binary systems which leads to the determination of 77 isotropic (19)F chemical shifts in various environments. A first attribution of NMR lines is performed for 8 compounds using a superposition model as initially proposed by B. Bureau et al. The phenomenological parameters of this model are then refined to improve the NMR line assignment. A satisfactory reliability is reached with a root-mean-square (RMS) deviation between calculated and measured values equal to 6 ppm. The refined parameters are then successfully tested on alpha-BaCaAlF(7) whose structure was recently determined. Finally, the isotropic chemical shift ranges are defined for shared, unshared, and "free" fluorine atoms encountered in the investigated binary systems. So, the fluorine surroundings can be deduced from the NMR line positions in compounds whose structure is unknown. Such an approach can also be applied to fluoride glasses.     

Characterization of complicated new polymorphs of chlorothalonil by X-ray diffraction and computer crystal structure prediction

A simultaneous experimental and computational search for polymorphs of chlorothalonil (2,4,5,6-tetrachloro-1,3-benzenedicarbonitrile) has been conducted, leading to the first characterization of forms 2 and 3. The crystal structure prediction study, using a specifically developed anisotropic atom-atom potential for chlorothalonil, gave as the global minimum in the lattice energy a structure that was readily refined against powder diffraction data to the known form 1 (P2(1)/a). The structure of form 2 was solved and refined from powder diffraction data, giving a disordered structure in the Rm (166) space group (Z = 3). It could also be refined against a P1 ordered model, starting from a low-energy hypothetical sheet structure found in the computational search. This shows that the disorder could be associated with the stacking of ordered sheets. The disordered structure for form 2 was later confirmed by single-crystal X-ray diffraction. The structure of form 3, determined from single-crystal diffraction, contains three independent molecules in the asymmetric unit in P2(1) (4) (Z = 6). Powder diffraction showed that this single-herringbone structure was similar to two low-energy structures found in the search. Further analysis confirmed that form 3 has a similar lattice energy and contains elements from both these predicted structures, which can be considered as good approximations to the form 3 structure.     

Determination of fluid--solid transitions in model protein solutions using the histogram reweighting method and expanded ensemble simulations

Protein crystallization conditions are usually identified by empirical screening methods because of the complexity of the process, such as the existence of nonequilibrium phases and the different crystal forms that may result from changes in solution conditions. Here the crystallization of a model protein is studied using computer simulation. The model consists of spheres that have both an isotropic interaction of short range and anisotropic interactions between patch-antipatch pairs. The free energy of a protein crystal is calculated using expanded ensemble simulations of the Einstein crystal, and NpT-Monte Carlo simulations with histogram reweighting are used to determine the fluid-solid coexistence. The histogram reweighting method is also used to trace out the complete coexistence curve, including multiple crystal phases, with varying reduced temperature, which corresponds to changing solution conditions. At a patch-antipatch interaction strength five times that of the isotropic interaction, the protein molecules form a stable simple cubic structure near room temperature, whereas an orientationally disordered face-centered-cubic structure is favored at higher temperatures. The anisotropic attractions also lead to a weak first-order transition between orientationally disordered and ordered face-centered-cubic structures at low temperature, although this transition is metastable. A complete phase diagram, including a fluid phase, three solid phases, and two triple points, is found for the six-patch protein model. A 12-patch protein model, consistent with the face-centered-cubic structure, leads to greater thermodynamic stability of the ordered phase. Metastable liquid-liquid phase equilibria for isotropic models with varying attraction tails are also predicted from Gibbs ensemble simulations.     

煤液化沥青分析表征及结构模型

对从煤液化残渣中萃取出的沥青类物质进行了固体13C-CP/MAS NMR分析、元素分析、红外光谱分析(FT-IR)和光电子能谱(XPS)分析,得到煤液化沥青的芳香结构单元信息及相关结构参数信息。结果表明,煤液化沥青芳香桥碳与周碳之比为0.115,芳香碳原子的存在形式以苯结构为主;脂肪结构多以甲基和环状亚甲基形式存在;氧主要以羰基、酯基的形式存在;氮主要以吡咯的形式存在。利用结构参数和分析表征结果构建了煤液化沥青的大分子结构模型,并运用13C-NMR预测软件ACD/CNMR Predictor计算了煤精制沥青大分子结构模型的13C化学位移。根据计算结果对大分子结构模型进行了修正,获得了与实验谱图吻合较好的大分子结构模型。     

Methods for refining interactively established models of ribosomal RNA towards a physico‐chemically plausible structure

A computational multiscale modeling approach that was used for the refinement of the structure of the bacterial ribosome is presented. Though designed for the ribosome, the methods are applicable to other large biomolecules as well. Algorithms were developed, allowing defined groups of atoms to be clustered into rigid objects, which greatly reduces the number of parameters in the molecular dynamics approach and thus speeds up the computational process considerably (clustered molecular dynamics). The energy potential function, which is used in molecular dynamics to describe structural details of a particle, was extended to include terms that describe high‐level biochemical constraints resulting from crosslinking techniques and cryo‐electron microscopy. High‐ and low‐level features of the potential function were specified, and the clustered molecular dynamics technique was integrated into the interactive model‐building process, to establish a physico‐chemically plausible structure of the bacterial ribosomal RNA. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 407–417, 2001     

GPCR structure-based virtual screening approach for CB2 antagonist search

The potential for therapeutic specificity in regulating diseases has made cannabinoid (CB) receptors one of the most important G-protein-coupled receptor (GPCR) targets in search for new drugs. Considering the lack of related 3D experimental structures, we have established a structure-based virtual screening protocol to search for CB2 bioactive antagonists based on the 3D CB2 homology structure model. However, the existing homology-predicted 3D models often deviate from the native structure and therefore may incorrectly bias the in silico design. To overcome this problem, we have developed a 3D testing database query algorithm to examine the constructed 3D CB2 receptor structure model as well as the predicted binding pocket. In the present study, an antagonist-bound CB2 receptor complex model was initially generated using flexible docking simulation and then further optimized by molecular dynamic and mechanical (MD/MM) calculations. The refined 3D structural model of the CB2-ligand complex was then inspected by exploring the interactions between the receptor and ligands in order to predict the potential CB2 binding pocket for its antagonist. The ligand-receptor complex model and the predicted antagonist binding pockets were further processed and validated by FlexX-Pharm docking against a testing compound database that contains known antagonists. Furthermore, a consensus scoring (CScore) function algorithm was established to rank the binding interaction modes of a ligand on the CB2 receptor. Our results indicated that the known antagonists seeded in the testing database can be distinguished from a significant amount of randomly chosen molecules. Our studies demonstrated that the established GPCR structure-based virtual screening approach provided a new strategy with a high potential for in silico identifying novel CB2 antagonist leads based on the homology-generated 3D CB2 structure model.     

Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships III: Modeling hydrophobic interactions

In an earlier article⁸ the need was demonstrated for atomic physicochemical properties for three dimensional structure directed quantitative structure-activity relationships, and it was shown how atomic parameters can be developed for successfully evaluating the molecular octanol-water partition coefficient, which is a measure of hydrophobicity. In this work we report more refined atomic values of octanol-water partition coefficients derived from nearly twice the number of compounds. Carbon, hydrogen, oxygen, nitrogen, sulfur and halogens are divided into 110 atom types of which 94 atomic values are evaluated from 830 molecules by least squares. These values gave a standard deviation of 0.470 and a correlation coefficient of 0.931. These parameters predicted the octanol-water partition coefficient of 125 compounds with a standard deviation of 0.520 and a correlation coefficient of 0.870. There is only a correlation coefficient of 0.432 between the atomic octanol-water partition coefficients and the atomic contributions to molar refractivity over the 93 atom types used for both the properties. This suggests that both parameters can be used simultaneously to model intermolecular interactions. We evaluated the CNDO/2 gross atomic charge distribution over several molecules to check the validity of our classification. We found that the charge density on the heteroatoms in conjugated systems is strongly affected by the presence of similar atoms in the conjugation which suggests it should be incorporated as a separate parameter in evaluating the partition coefficient.     

In silico structural and functional characterization and phylogenetic study of alkaline phosphatase in bacterium,Rhizobium leguminosarum (Frank 1879)

Phosphorus is one of the primary macronutrient of plants, which is present in soil. It is essential for normal growth and development of plants. Plants use inorganic form of phosphate but organic form can also be assimilated with the help of soil inhabiting bacteria. Alkaline phosphatase is an enzyme present in Rizobium bacteria. This enzyme is responsible for solubilization and mineralization of organic phosphate and makes it readily available for plants. In the present study, nine different strains of Rhizobium leguminosarum were selected for a detailed computational structural and functional characterization and phylogenetic studies of alkaline phosphatase. Amino acid sequences were retrieved from UniProt and saved in FASTA format for use in analysis. Phylogenetic analysis of these strains was done by using MEGA7. 3D structure prediction was performed by using online server I-Tasser. Galaxy Web and 3D Refine were used for structure refinement. The refined structures were evaluated using two validation servers, QMEAN and SAVES. Protein-protein interaction analysis was done by using STRING. For detailed functional characterization, Cofactor, Coach, RaptorX, PSORT and MEME were used. Overall quality of predicted protein models was above 80%. Refined and validated models were submitted into PMDB. Seven out of nine strains were closely related and other two were distantly related. Protein-Protein interaction showed no significant co-expression among the interaction partners.