Survey of the year 2009: applications of isothermal titration calorimetry

Isothermal titration calorimetry (ITC) is now an established and invaluable method for determining the thermodynamic constants, association constant and stoichiometry of molecular interactions in aqueous solutions. The technique has become widely used by biochemists to study protein interaction with other proteins, small molecules, metal ions, lipids, nucleic acids and carbohydrates; and nucleic acid interaction with small molecules. The drug discovery industry has utilized this approach to measure protein (or nucleic acid) interaction with drug candidates. ITC has been used to screen candidates, guide the design of potential drugs and validate the modelling used in structure-based drug design. Emerging disciplines including nanotechnology and drug delivery could benefit greatly from ITC in enhancing their understanding and control of nano-particle assembly, and drug binding and controlled release.     

Virtual screening using molecular simulations

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery.     

Finessing atlas data for species distribution models

Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This study outlines the incorporation of existing knowledge into a conventional approach to predict the distribution of Bonelli’s eagle (Aquila fasciata) at a resolution 100 times finer than available atlas data. Location Malaga province, Andalusia, southern Spain. Methods A Bayesian expert system was proposed to utilize the knowledge from distribution models to yield the probability of a species being recorded at a finer resolution (1 × 1 km) than the original atlas data (10 × 10 km). The recorded probability was then used as a weight vector to generate a sampling scheme from the species atlas to enhance the accuracy of the modelling procedure. The maximum entropy for species distribution modelling (MaxEnt) was used as the species distribution model. A comparison was made between the results of the MaxEnt using the enhanced and, the random sampling scheme, based on four groups of environmental variables: topographic, climatic, biological and anthropogenic. Results The models with the sampling scheme enhanced by an expert system had a higher discriminative capacity than the baseline models. The downscaled (i.e. finer scale) species distribution maps using a hybrid MaxEnt/expert system approach were more specific to the nest locations and were more contrasted than those of the baseline model. Main conclusions The proposed method is a feasible substitute for comprehensive field work. The approach developed in this study is applicable for predicting the distribution of Bonelli’s eagle at a local scale from a national‐level occurrence data set; however, the usefulness of this approach may be limited to well‐known species.     

Sequential analysis of the social behavior of infants in groups of Japanese monkeys (Macaca fuscata fuscata)

We employed techniques of behavioral entropy to carry out a quantitative analysis of sequences of behavioral patterns evident in the interaction between infants and other members of a group of Japanese monkeys (Macaca fuscata fuscata). The group concerned included examples both of monkeys in captivity and in the wild state. The results were examined as a function of the animal age and environmental differences (cage-field). An example is given to illustrate the use of information theory. Findings partially confirmed that the variability of social behavior decreases as the age of the animals increases.     

Detecting differentially expressed genes by relative entropy

DNA microarray experiments have generated large amount of gene expression measurements across different conditions. One crucial step in the analysis of these data is to detect differentially expressed genes. Some parametric methods, including the two-sample t-test (T-test) and variations of it, have been used. Alternatively, a class of non-parametric algorithms, such as the Wilcoxon rank sum test (WRST), significance analysis of microarrays (SAM) of Tusher et al. (2001), the empirical Bayesian (EB) method of Efron et al. (2001), etc., have been proposed. Most available popular methods are based on t-statistic. Due to the quality of the statistic that they used to describe the difference between groups of data, there are situations when these methods are inefficient, especially when the data follows multi-modal distributions. For example, some genes may display different expression patterns in the same cell type, say, tumor or normal, to form some subtypes. Most available methods are likely to miss these genes. We developed a new non-parametric method for selecting differentially expressed genes by relative entropy, called SDEGRE, to detect differentially expressed genes by combining relative entropy and kernel density estimation, which can detect all types of differences between two groups of samples. The significance of whether a gene is differentially expressed or not can be estimated by resampling-based permutations. We illustrate our method on two data sets from Golub et al. (1999) and Alon et al. (1999). Comparing the results with those of the T-test, the WRST and the SAM, we identified novel differentially expressed genes which are of biological significance through previous biological studies while they were not detected by the other three methods. The results also show that the genes selected by SDEGRE have a better capability to distinguish the two cell types.     

Measuring diversity from dissimilarities with Rao's quadratic entropy: are any dissimilarities suitable?

Rao has developed quadratic entropy to measure diversity in a set of entities divided up among a fixed set of categories. This index depends on a chosen matrix of dissimilarities among categories and a frequency distribution of these categories. With certain choices of dissimilarities, this index could be maximized over all frequency distributions by eliminating several categories. This unexpected result is radically opposite to those obtained with usual diversity indices. We demonstrate that the elimination of categories to maximize the quadratic entropy depends on mathematical properties of the chosen dissimilarities. In particular, when quadratic entropy is applied to ultrametric dissimilarities, all categories are retained in order to reach its maximal value. Three examples, varying from simple one-dimensional to ultrametric dissimilarity matrices, are provided. We conclude that, as far as diversity measurement is concerned, quadratic entropy is most relevant when applied to ultrametric dissimilarities.     

High-resolution aliphatic side-chain assignments in 3D HCcoNH experiments with joint H–C evolution and non-uniform sampling

We describe an efficient NMR triple resonance approach that correlates, at high resolution, protein side-chain and backbone resonances. It relies on the combination of two strategies: joint evolution of aliphatic side-chain proton/carbon coherences using a backbone N–H based HCcoNH reduced dimensionality (RD) experiment and non-uniform sampling (NUS) in two indirect dimensions. A typical data set containing such correlation information can be acquired in 2 days, at very high resolution unfeasible for conventional 4D HCcoNH-TOCSY experiments. The resonances of the aliphatic side-chain protons are unambiguously assigned to their attached carbons through the analysis of the ‘sum’ and ‘difference’ spectra. This approach circumvents the tedious process of manual resonance assignments using HCcH-TOCSY data, while providing additional resolving power of backbone N–H signals. A simple peak-list based algorithm has been implemented in the IBIS software for rapid automated backbone and side-chain assignments.     

Nanosecond dynamics of a mimicked membrane-water interface observed by time-resolved stokes shift of LAURDAN

We studied the dipolar relaxation of the surfactant-water interface in reverse micelles of AOT-water in isooctane in the nanosecond and subnanosecond time ranges by incorporating the amphipathic solvatochromic fluorescent probes LAURDAN and TOE. A negative component was observed in the fluorescence decays in the red edge of the emission spectrum-the signature of an excited state reaction-with LAURDAN but not for TOE. The deconvolution of the transient reconstructed spectra of LAURDAN based on a model constructed by adding together three log-normal Gaussian equations made it possible to separate the specific dynamic solvent response from the intramolecular excited state reactions of the probe. The deconvoluted spectrum of lowest energy displayed the largest Stokes shift. This spectral shift was described by unimodal kinetics on the nanosecond timescale, whereas the relaxation kinetics of water-soluble probes have been reported to be biphasic (on the subnanosecond and nanosecond timescales) due to the heterogeneous distribution of these probes in the water pool. Most of this spectral shift probably resulted from water relaxation as it was highly sensitive to the water to surfactant molar ratio (w(0)) (60-65 nm at w(0) = 20-30). A small part of this spectral shift (9 nm at w(0) = 0) probably resulted from dipolar interaction with the AOT polar headgroup. The measured relaxation time values were in the range of the rotational motion of the AOT polar headgroup region as assessed by LAURDAN and TOE fluorescence anisotropy decays.     

Thermodynamics of phosphorylcholine and lysophosphatidylcholine binding to the major protein of bovine seminal plasma, PDC-109

PDC-109 binds to sperm plasma membranes by specific interaction with choline phospholipids and induces cholesterol efflux, a necessary event before capacitation - and subsequent fertilization - can occur. The binding of phosphorylcholine (PrC) and lysophosphatidylcholine (Lyso-PC) with PDC-109 was investigated by monitoring the ligand-induced changes in the absorption spectrum of PDC-109. At 20 degrees C, the association constants (K(a)), for PrC and Lyso-PC were obtained as 81.4M(-1) and 2.02 x 10(4) M(-1), respectively, indicating that the binding of Lyso-PC to PDC-109 is 250-fold stronger than that of PrC. From the temperature dependence of the K(a) values, enthalpy of binding (DeltaH(0)) and entropy of binding (DeltaS(0)), were obtained as -79.7 and -237.1 J mol(-1)K(-1) for PrC and -73.0 kJ mol(-1) and -167.3 J mol(-1)K(-1) for Lyso-PC, respectively. These results demonstrate that although the binding of these two ligands is driven by enthalpic forces, smaller negative entropy of binding associated with Lyso-PC results in its significantly stronger binding.     

粽管巢蛛和拟水狼蛛对稻纵卷叶螟和稻褐飞虱捕食作用研究

应用二次正交旋转组合设计方法建立粽管巢蛛和拟水狼蛛对稻纵卷叶螟和稻褐飞虱捕食作用的数学模型。结果表明,粽管巢蛛是稻纵卷叶螟的重要天敌,粽管巢蛛和拟水狼蛛均是稻褐飞虱的重要天敌。当稻褐飞虱密度较高时,随着蜘蛛密度的增加,由于蜘蛛之间的干扰作用,导致稻褐飞虱被捕食量下降。