模型选择中交叉验证量的改进

对模型选择中交叉验证量CV进行改进,得到新的验证模型是否合适的准则RCV,RCV包含了CV的信息,并包含了拟合程度,模型中的待估参数个数和样本容量等等,比起AIC,BIC和CV具有更好的稳定性和分辨功能.     

Model-free model elimination: A new step in the model-free dynamic analysis of NMR relaxation data

Model-free analysis is a technique commonly used within the field of NMR spectroscopy to extract atomic resolution, interpretable dynamic information on multiple timescales from the R ₁, R ₂, and steady state NOE. Model-free approaches employ two disparate areas of data analysis, the discipline of mathematical optimisation, specifically the minimisation of a χ² function, and the statistical field of model selection. By searching through a large number of model-free minimisations, which were setup using synthetic relaxation data whereby the true underlying dynamics is known, certain model-free models have been identified to, at times, fail. This has been characterised as either the internal correlation times, τ _e , τ _f , or τ _s , or the global correlation time parameter, local τ _m , heading towards infinity, the result being that the final parameter values are far from the true values. In a number of cases the minimised χ² value of the failed model is significantly lower than that of all other models and, hence, will be the model which is chosen by model selection techniques. If these models are not removed prior to model selection the final model-free results could be far from the truth. By implementing a series of empirical rules involving inequalities these models can be specifically isolated and removed. Model-free analysis should therefore consist of three distinct steps: model-free minimisation, model-free model elimination, and finally model-free model selection. Failure has also been identified to affect the individual Monte Carlo simulations used within error analysis. Each simulation involves an independent randomised relaxation data set and model-free minimisation, thus simulations suffer from exactly the same types of failure as model-free models. Therefore, to prevent these outliers from causing a significant overestimation of the errors the failed Monte Carlo simulations need to be culled prior to calculating the parameter standard deviations.     

Evaluation of the Kullback-Leibler Discrepancy for Model Selection in Open Population Capture-Recapture Models

The objective of this paper is to introduce the logical basis of AIC-based model selection to persons analyzing capture-recapture data and to explore the key theorettical aspect of AIC based model selection, for open-model capture-recapture, needed for AIC to perform well in this context. Almost all previous work on AIC assumes a Gaussian model; that assumption does not hold for capture-recapture models. Assuming the Cormack-Jolly-Seber model as the true model, we used numerical methods to evaluate the expectation of the log-likelihood relative to Akaike's target predictive log-likelihood. The use of this particular target criterion was motivated by the idea of using the Kullback-Leibler discrepancy for model selection, for which Akaike found the bias of the sample log-likelihood was asymptotically K, where K = the number of estimated (by MLE) parameters. In some sense, then, AIC is a bias-adjusted log-likelihood. For a set of 81 plausible cases, we evaluated this bias almost exactly. The ratio of this bias to the first order theory (bias of K) and to second order theory (K + a sample size adjustment) is essentially 1 for these 81 cases. Thus, AIC should be a suitable basis for model selection in open model capture-recapture.     

Computational Analysis of C-Reactive Protein for Assessment of Molecular Dynamics and Interaction Properties

Serum C-reactive protein (CRP) is used as a marker of inflammation in several diseases including autoimmune disease and cardiovascular disease. CRP, a member of the pentraxin family, is comprised of five identical subunits. CRP has diverse ligand-binding properties which depend upon different structural states of CRP. However, little is known about the molecular dynamics and interaction properties of CRP. In this study, we used SAPS, SCRATCH protein predictor, PDBsum, ConSurf, ProtScale, Drawhca, ASAView, SCide and SRide server and performed comprehensive analyses of molecular dynamics, protein–protein and residue–residue interactions of CRP. We used 1GNH.pdb file for the crystal structure of human CRP which generated two pentamers (ABCDE and FGHIJ). The number of residues involved in residue–residue interactions between A–B, B–C, C–D, D–E, F–G, G–H, H–I, I–J, A–E and F–J subunits were 12, 11, 10, 11, 12, 11, 10, 11, 10 and 10, respectively. Fifteen antiparallel β sheets were involved in β-sheet topology, and five β hairpins were involved in forming the secondary structure. Analysis of hydrophobic segment distribution revealed deviations in surface hydrophobicity at different cavities present in CRP. Approximately 33 % of all residues were involved in the stabilization centers. We show that the bioinformatics tools can provide a rapid method to predict molecular dynamics and interaction properties of CRP. Our prediction of molecular dynamics and interaction properties of CRP combined with the modeling data based on the known 3D structure of CRP is helpful in designing stable forms of CRP mutants for structure–function studies of CRP and may facilitate in silico drug design for therapeutic targeting of CRP.     

Model Construction and Model Examination on the Basis of Simulated Selection

By reason nonlinear relations founded between selection differential and realised selection response we have been made investigations about variants of the genetic-statistical model, which include this nonlinearity. The variations of the model would not only referred to the postulate pattern of the connection between phenotype, genotype and environment but also enclosed the postulate assumption about the distribution of the variates. In an investigated special case the linear model equation P = G ± e was held, however the distributions of P and G were defined over a limited range in one direction. For P we have defined a modified normal distribution and the distribution of the random vector (G, e) non normal regarded with cov (G, e) ≠ 0, By means of a solution set of an integral equation a density function of the random vector (P, G) has been received, in which the expectation of the selection response of the usual genetic-statistical model approximate is included as a special case. The genetical parameters has been derived, which result from changed model. However their representation was only possible partially as an integral function. A subsequent paper informs of the examination this mode! variants, which depend on a parameter of the nonlinearity c.     

Molecular Dynamics Simulation of Model Lipid Membranes: Structural Effects of Impurities

Abstract

The gel to fluid phase transition or ordered to disordered phase transition observed in biological membranes are simulated by using constant energy Molecular Dynamics. The surface part of the membrane is modelled as a two-dimensional matrix formed by the head groups of the phospholipid molecules. Head molecules which are modelled as three spheres fused with three force centers, interact with each other via van der Waals and Coulomb type interactions. The -so called- impurity or foreign molecule embedded in the surface represents the protein type molecule which is present in biological membranes and control its activity. It is modelled as a pentagon having one force centers in each corner. It also interacts with the surface molecules again via van der Waals and Coulomb type interactions. The surface density is kept constant in the simulations of the systems with or without impurity. Structural and orientational changes due to impurity were observed and proved by monitoring two-dimensional order parameter. It has been shown that melting of the surface or breakage of the ordering of the surface molecules becomes easier and ordered to disordered phase transition temperature was lowered by 100 K if the impurity is present.     

Molecular Dynamics Simulation of Nucleation and Growth of a Binary Quasicrystal

Abstract

The quasicrystal structure is considered to be a new type of ordered phase because its Fourier transform has Laue spots with icosahedral symmetry, which is inconsistent with crystal structure. Computer simulation of the formation process of a quasicrystal was performed by the molecular dynamics method. On the basis of the Strandburg type of quasicrystal model, we developed an algorithm of the formation process of binary quasicrystal reflecting the procedure as realistically as possible. The Fourier transform of some of the obtained structures has shown decagonal symmetry although the spots are rather diffused. It has been shown that the potential parameter and experimental condition should be limited to produce a perfect quasicrystal structure.     

Effect of Model Sorptive Phases on Phenanthrene Biodegradation: Molecular Analysis of Enrichments and Isolates Suggests Selection Based on Bioavailability

Reduced bioavailability of nonpolar contaminants due to sorption to natural organic matter is an important factor controlling biodegradation of pollutants in the environment. We established enrichment cultures in which solid organic phases were used to reduce phenanthrene bioavailability to different degrees (R. J. Grosser, M. Friedrich, D. M. Ward, and W. P. Inskeep, Appl. Environ. Microbiol. 66:2695–2702, 2000). Bacteria enriched and isolated from contaminated soils under these conditions were analyzed by denaturing gradient gel electrophoresis (DGGE) and sequencing of PCR-amplified 16S ribosomal DNA segments. Compared to DGGE patterns obtained with enrichment cultures containing sand or no sorptive solid phase, different DGGE patterns were obtained with enrichment cultures containing phenanthrene sorbed to beads of Amberlite IRC-50 (AMB), a weak cation-exchange resin, and especially Biobead SM7 (SM7), a polyacrylic resin that sorbed phenanthrene more strongly. SM7 enrichments selected for mycobacterial phenanthrene mineralizers, whereas AMB enrichments selected for a Burkholderia sp. that degrades phenanthrene. Identical mycobacterial and Burkholderia 16S rRNA sequence segments were found in SM7 and AMB enrichment cultures inoculated with contaminated soil from two geographically distant sites. Other closely related Burkholderia sp. populations, some of which utilized phenanthrene, were detected in sand and control enrichment cultures. Our results are consistent with the hypothesis that different phenanthrene-utilizing bacteria inhabiting the same soils may be adapted to different phenanthrene bioavailabilities.     

Molecular Dynamics Simulation of Alkali Silicates Based on the Quantum Mechanical Potential Surfaces

Abstract

Two potential parameter sets for alkali silicates were derived on the basis of ab-initio MO calculations. One is a model containing completely ionic alkali (model I), and another is that derived from cluster calculations (model II). These sets were tested against the crystal, glass, and liquid of metasilicates. The model II can reproduce these structures well under constant pressure conditions, and is found to be better than model I as a whole.     

Molecular Dynamics Simulation in Solvent of the Estrogen Receptor Protein DNA Binding Domain in Complex with a Non-Consensus Estrogen Response Element DNA Sequence

Abstract

We investigated protein/DNA interactions, using molecular dynamics simulations computed between a 10 Angstom water layer model of the estrogen receptor (ER) protein DNA binding domain (DBD) amino acids and DNA of a non-consensus estrogen response element (ERE) consisting of 29 nucleotide base pairs. This ERE nucleotide sequence occurs naturally upstream of the Xenopus laevis Vitelligenin AI gene. The ER DBD is encoded by three exons. Namely, exons 2 and 3 which encode the two zinc binding motifs and a sequence of exon 4 which encodes a predicted alpha helix. We generated a computer model of the ER DBD using atomic coordinates derived from the average of 30 nuclear magnetic resonance (NMR) spectroscopy coordinate sets. Amino acids on the carboxyl end of the ER DBD were disordered in both X-ray crystallography and NMR determinations and no coordinates were reported. This disordered region includes 10 amino acids of a predicted alpha helix encoded in exon 4 at the exon 3/4 splice junction. These amino acids are known to be important in DNA binding and are also believed to function as a nuclear translocation signal sequence for the ER protein. We generated a computer model of the predicted alpha helix consisting of the 10 amino acids encoded in exon 4 and attached this helix to the carboxyl end of the ER DBD at the exon 3/4 splice junction site. We docked the ER DBD model within the DNA major groove halfsites of the 29 base pair non-consensus ERE and flanking nucleotides. We constructed a solvated model with the ER DBD/ERE complex surrounded by a ten Angstrom water layer and conducted molecular dynamics simulations. Hydrogen bonding interactions were monitored. In addition, van der Waals and electrostatic interaction energies were calculated. Amino acids of the ER DBD DNA recognition helix formed both direct and water mediated hydrogen bonds at cognate codon-anticodon nucleotide base and backbone sites within the ERE DNA right major groove halfsite. Amino acids of the ER DBD exon 4 encoded predicted alpha helix formed direct and water mediated H-bonds with base and backbone sites of their cognate codon-anticodon nucleotides within the minor grooves flanking the ERE DNA major groove halfsites. These interactions together induced bending of the DNA into the protein.     

Prevalent Mutations of Human Prion Protein: A Molecular Modeling and Molecular Dynamics Study

Abstract

Point mutations in the human prion protein gene, leading to amino acid substitutions in the human prion protein contribute to conversion of PrP^C to PrP^Sc and amyloid formation, resulting in prion diseases such as familial Creutzfeldt-Jakob disease (CJD), Gerstmann-Straussler-Scheinker disease (GSS), and fatal familial insomnia. We have investigated impressions of prevalent mutations including Q217R, D202N, F198S, on the human prion protein and compared the mutant models with wild types. Structural analyses of models were performed with molecular modeling and molecular dynamics simulation methods. According to our results, frequently occurred mutations are observed in conserved and fully conserved sequences of human prion protein and the most fluctuation values occur in the Helix 1 around residues 144–152 and C-terminal end of the Helix 2. Our analysis of results obtained from MD simulation clearly shows that this long-range effect plays an important role in the conformational fluctuations in mutant structures of human prion protein. Results obtained from molecular modeling such as creation or elimination of some hydrogen bonds, increase or decrease of the accessible surface area and molecular surface, loss or accumulation of negative or positive charges on specific positions, and altering the polarity and pKa values, show that amino acid point mutations, though not urgently change the stability of PrP, might have some local impacts on the protein interactions which are required for oligomerization into fibrillar species.     

Structure and Dynamics of Ribosomal Protein L12: An Ensemble Model Based on SAXS and NMR Relaxation

Ribosomal protein L12 is a two-domain protein that forms dimers mediated by its N-terminal domains. A 20-residue linker separates the N- and C-terminal domains. This linker results in a three-lobe topology with significant flexibility, known to be critical for efficient translation. Here we present an ensemble model of spatial distributions and correlation times for the domain reorientations of L12 that reconciles experimental data from small-angle x-ray scattering and nuclear magnetic resonance. We generated an ensemble of L12 conformations in which the structure of each domain is fixed but the domain orientations are variable. The ensemble reproduces the small-angle x-ray scattering data and the optimized correlation times of its reorientational eigenmodes fit the ¹⁵N relaxation data. The ensemble model reveals intrinsic conformational properties of L12 that help explain its function on the ribosome. The two C-terminal domains sample a large volume and extend further away from the ribosome anchor than expected for a random-chain linker, indicating that the flexible linker has residual order. Furthermore, the distances between each C-terminal domain and the anchor are anticorrelated, indicating that one of them is more retracted on average. We speculate that these properties promote the function of L12 to recruit translation factors and control their activity on the ribosome.     

Mechanism of Interaction between the General Anesthetic Halothane and a Model Ion Channel Protein, III: Molecular Dynamics Simulation Incorporating a Cyanophenylalanine Spectroscopic Probe

A nitrile-derived amino acid, Phe_CN, has been used as an internal spectroscopic probe to study the binding of an inhalational anesthetic to a model membrane protein. The infrared spectra from experiment showed a blue-shift of the nitrile vibrational frequency in the presence of the anesthetic halothane. To interpret the infrared results and explore the nature of the interaction between halothane and the model protein, all-atom molecular dynamics (MD) simulations have been used to probe the structural and dynamic properties of the protein in the presence and absence of one halothane molecule. The frequency shift analyzed from MD simulations agrees well with the experimental infrared results. Decomposition of the forces acting on the nitrile probes demonstrates an indirect impact on the probes from halothane, namely a change of the protein's electrostatic local environment around the probes induced by halothane. Although the halothane remains localized within the designed hydrophobic binding cavity, it undergoes a significant amount of translational and rotational motion, modulated by the interaction of the trifluorine end of halothane with backbone hydrogens of the residues forming the cavity. This dominant interaction between halothane and backbone hydrogens outweighs the direct interaction between halothane and the nitrile groups, making it a good “spectator” probe of the halothane-protein interaction. These MD simulations provide insight into action of anesthetic molecules on the model membrane protein, and also support the further development of nitrile-labeled amino acids as spectroscopic probes within the designed binding cavity.     

From Molecular to Process Simulation: Novel Approaches to the Prediction of Phase Equilibria and PVT Behavior Based on Molecular/Quantum Mechanics and Molecular Dynamics Simulations

Abstract

Actually, in modern process simulators, more than 75% of the code implemented is dedicated to physical properties estimation, calculation and predictions. Data banks storing pure component parameters and binary interaction parameters for phase equilibrium calculations are extensively used and continuously implemented in actual process simulators. This gives an idea of the important role physical properties availability plays in process simulation.

In this paper we propose a new way for coupling molecular and process simulation. The basic machinery is to resort to molecular/quantum mechanics and molecular dynamics simulation techniques for generating the parameters of some equations of state that will subsequently be used for the prediction of phase equilibria and PVT behavior of small and polymeric molecules as well. This information, in turn, will be used as input in the process simulator, thus creating a final and well-defined bridge between molecular and process simulations in chemical engineering.     

Ligands Binding and Molecular Simulation: the Potential Investigation of a Biosensor Based on an Insect Odorant Binding Protein

Based on mimicking biological olfaction, biosensors have been applied for the detection of various ligands in complex environment, which could represent one of the most promising research fields. In this study, the basic characters of one insect odorant binding protein (OBP) as a biosensor were explored. To explore the molecular recognition process, the tertiary structure of the protein was modeled and the protein-ligand interactions with 1,536,550 chemicals were investigated by the molecular docking. The availability of large amount of recombinant SlitOBP1 overcame the difficulty to obtain biological sensing material. After obtained the purified recombinant protein, the result of fluorescence binding assays proved the candidate protein has good affinities with the majority of the tested chemicals. With the aid of simulation docking, the key conserved amino acids within the binding site were identified and then mutated to alanine. After mutation, the protein-ligand binding characteristics were recorded, and the competitive binding assays were carried out to provide experimental verification. The detailed information on its structure and affinities investigated in this study could allow the design of specific mutants with desired characteristics, which provides a solid base for tailoring OBP for biosensor and provides a role model for screening the other elements in olfactory system for different applications.     

Designing of a Functional Chimeric Protein for Production of Nanobodies Against Human CD20: Molecular Dynamics Simulation and In Vitro Verification

International Journal of Peptide Research and Therapeutics - One major issue in cancer immunotherapy is the large size of mAbs (150 kDa) which usually causes limitation in tumor...