Computational prediction of protein ubiquitination sites mapping on Arabidopsis thaliana

Among the protein post-translational modifications (PTMs), ubiquitination is considered as one of the most significant processes which can regulate the cellular functions and various diseases. Identification of ubiquitination sites becomes important for understanding the mechanisms of ubiquitination-related biological processes. Both experimental and computational approaches are available for identifying ubiquitination sites based on protein sequences of different species. The experimental approaches are time-consuming, laborious and costly. In silico prediction is an alternative time saving, easier and cost-effective approach for identifying ubiquitination sites. Moreover, the sequence patterns in the different species around the ubiquitination sites are not similar which demands species-specific predictors. Therefore, in this study, we have proposed a novel computational method for identifying ubiquitination sites based on protein sequences of A. thaliana species which will be robust against outlying observations also. Through the comparative study of two encoding schemes and three classifiers, the random forest (RF) based predictor was selected as the best predictor under the CKSAAP encoding scheme with 1:1 ratio of positive and negative samples (i.e. ubiquitinated and non-ubiquitinated) in training dataset. The proposed predictor produced the area under the ROC curve (AUC score) as 0.91 and 0.86 for 5-fold cross-validation test with the training dataset and the independent test dataset of A. thaliana respectively. The proposed RF based predictor also performed much better than the other existing ubiquitination sites predictors for A. thaliana.     

Simultaneous determination of acidic,basic and alcoholic substances relating to monoamine hormones and metabolites in biological material by mass fragmentography (GC/MF)

A method is described for the simultaneous quantitative determination of monoamines and related compounds from urine and brain tissue samples in the pg-range, using a GC/MF instrument LKB-2091 provided with a multiple ion detection (MID) system and capillary columns. The simultaneous detection of “fingerprints” with fourteen and more compounds during one single GC run was achieved after the intoduction of “time gates” for the detection of the different characteristic masses. Several modifications to the LKB equipment permitted exact reproducibility of retention times, which is essential for the use of “time gates”. The detection of “fingerprints” with these acidic, basic and alcoholic substances was achieved by the extraction of the dried biological samples with silylating agents.     

Do Anti‐Bredt Natural Products Exist? Olefin Strain Energy as a Predictor of Isolability

Bredt’s rule holds a special place in the realm of physical organic chemistry, but its application to natural products chemistry—the field in which the rule was originally formulated—is not well defined. Herein, the use of olefin strain (OS) energy as a readily calculated predictor of the stability of natural products containing a bridgehead alkene is introduced. Schleyer first used OS energies to classify parent bridgehead alkenes into “isolable”, “observable”, and “unstable” classes. OS calculations on natural products, using contemporary forcefield methods, unequivocally predict all structurally verified bridgehead alkene natural products to be “isolable”. Thus, when one assigns the structure of a putative bridgehead alkene natural product, an OS in the “observable” or “unstable” ranges is a red flag for error.     

Do Anti‐Bredt Natural Products Exist? Olefin Strain Energy as a Predictor of Isolability

Bredt’s rule holds a special place in the realm of physical organic chemistry, but its application to natural products chemistry—the field in which the rule was originally formulated—is not well defined. Herein, the use of olefin strain (OS) energy as a readily calculated predictor of the stability of natural products containing a bridgehead alkene is introduced. Schleyer first used OS energies to classify parent bridgehead alkenes into “isolable”, “observable”, and “unstable” classes. OS calculations on natural products, using contemporary forcefield methods, unequivocally predict all structurally verified bridgehead alkene natural products to be “isolable”. Thus, when one assigns the structure of a putative bridgehead alkene natural product, an OS in the “observable” or “unstable” ranges is a red flag for error.     

A New Kinetic Model for Water Sorption Isotherms of Cellulosic Materials

Summary: Some natural fibres like flax, hemp and others show excellent mechanical properties which make them a promising choice for the reinforcement of polymers. For natural fibre reinforced composites, hydrophilicity is a problem with respect to dimensional changes, fibre to matrix adhesion and long term stability. The interaction of differently prepared and modified fibres with water vapour has been investigated by dynamic vapour sorption. It has been found that the sorption and desorption kinetics of cellulosic fibres can be excellently fitted by assuming two parallel, independent first order processes. This empirical model, defined here as the “Parallel Exponential Kinetics” model (PEK-model), reveals two distinct mechanisms with slow and fast exchange of water vapour respectively, related to different sorption sites. The specific sorption mechanisms are represented by individual sorption-desorption isotherms as components of the total isotherms. The results suggest a relation to the differing types of amorphous regions in the fibres and/or to the different states of “bound” or “free” water, discussed for hydrophilic materials. The PEK-model proved to be consistently applicable for sorption and desorption over the whole humidity range, and also for all tested cellulose fibres. It is especially useful for a clearer distinction of different fibre types or modifications and can be successfully used for an extended fibre characterization.     

GPCR‐CA: A cellular automaton image approach for predicting G‐protein–coupled receptor functional classes

Given an uncharacterized protein sequence, how can we identify whether it is a G‐protein–coupled receptor (GPCR) or not? If it is, which functional family class does it belong to? It is important to address these questions because GPCRs are among the most frequent targets of therapeutic drugs and the information thus obtained is very useful for “comparative and evolutionary pharmacology,” a technique often used for drug development. Here, we present a web‐server predictor called “GPCR‐CA,” where “CA” stands for “Cellular Automaton” (Wolfram, S. Nature 1984, 311, 419), meaning that the CA images have been utilized to reveal the pattern features hidden in piles of long and complicated protein sequences. Meanwhile, the gray‐level co‐occurrence matrix factors extracted from the CA images are used to represent the samples of proteins through their pseudo amino acid composition (Chou, K.C. Proteins 2001, 43, 246). GPCR‐CA is a two‐layer predictor: the first layer prediction engine is for identifying a query protein as GPCR on non‐GPCR; if it is a GPCR protein, the process will be automatically continued with the second‐layer prediction engine to further identify its type among the following six functional classes: (a) rhodopsin‐like, (b) secretin‐like, (c) metabotrophic/glutamate/pheromone; (d) fungal pheromone, (e) cAMP receptor, and (f) frizzled/smoothened family. The overall success rates by the predictor for the first and second layers are over 91% and 83%, respectively, that were obtained through rigorous jackknife cross‐validation tests on a new‐constructed stringent benchmark dataset in which none of proteins has ≥40% pairwise sequence identity to any other in a same subset. GPCR‐CA is freely accessible at http://218.65.61.89:8080/bioinfo/GPCR‐CA , by which one can get the desired two‐layer results for a query protein sequence within about 20 seconds. © 2008 Wiley Periodicals, Inc. J Comput Chem 2009     

Multireference basis-set reduction

We review “Hilbert space basis-set reduction” (BSR) as an approach to reduce the computational effort of accurate correlation calculations for large basis sets. We partition the single-particle basis into a small “internal” and a large “external” set. We use the MRCI method for the calculation for that part of configuration space in which only internal orbitals are occupied and perturbatively correct for the remaining configurations using a method similar to Shavitt's B_k method. The present implementation approximates the MRCI result for the unpartitioned basis set, with a significantly reduced computational effort. To demonstrate the viability of the method, we present results for selected states of small molecules (Be₂, CH₂, O₃). For the examples investigated, we find that relative energy differences can be reproduced to an accuracy of approximately 1 kcal/mol with a significant computational saving. © 1996 John Wiley & Sons, Inc.     

Strong activation of MgCl2‐supported Ziegler‐Natta catalysts by treatments with BCl3: Evidence and application of the “cluster” model of active sites

Heterogeneous Ziegler‐Natta precatalysts (with phthalate as internal donor) were modified by treatments with BCl₃ (2 h in heptane; T = 20–90 °C; B/Ti = 0.1–5) before their use in the polymerization of propylene to modify the active sites distribution. If performed on previously “detitanated” precatalysts, the treatment leads to a strong increase of productivity (up to one order of magnitude) without drastic modifications of polypropylenes properties (tacticity, molecular weight distribution). In addition, these findings are in good agreement with the hypothesis of a “cluster” organization of active sites allowing to rationalize activation by BCl₃ by formation of heteronuclear B‐Ti clusters. The activation method was also applied to unmodified precatalysts and gave a significant gain of productivity. The simple and versatile activation process can also be performed under mild conditions (low T and low [BCl₃]). © 2009 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 47: 5784–5791, 2009     

Computer modeling of the dynamic properties of the cAMP-dependent protein kinase catalytic subunit

The structural dynamics of the cAMP-dependent protein kinase catalytic subunit were modeled using molecular dynamics computational methods. It was shown that the structure of this protein as well as its complexes with ATP and peptide ligand PKI(5-24) consisted of a large number of rapidly inter-converting conformations which could be grouped into subsets proceeding from their similarity. This cluster analysis revealed that conformations which correspond to the “opened” and “closed” structures of the protein were already present in the free enzyme, and most surprisingly co-existed in enzyme–ATP and enzyme–PKI(5-24) complexes as well as in the ternary complex, which included both of these ligands. The results also demonstrated that the most mobile structure segments of the protein were located in the regions of substrate binding sites and that their dynamics were most significantly affected by the binding of the ATP and peptide ligand.     

Multivariate statistical interpretation of coastal sediment monitoring data

Multivariate statistical analysis of sediment data (input matrix 122 × 15) collected from 122 sampling sites from the western coastline of the USA and analyzed for 15 analytes indicates that the data structure could be explained by four latent factors. These factors are conditionally named “anthropogenic”, “organic”, “natural”, and “hot spots”. They explain over 85% of the total variance of the data system, which is an acceptable value for the PCA model. The receptor models obtained after regression of the mass on the absolute principal components scores ensures reliable estimation of the contribution of each possible natural or anthropogenic source to the mass of each chemical component. It can be concluded that the region of interest reveals a different pattern of pollution compared with the eastern coastline treated statistically in a previous study.     

Matrices with Heterogeneous Distribution of the Binding Sites for Immobilization of Biomacromolecules

The coupling of photosensitive reagents has been carried out with the goal of obtaining the predetermined distribution of binding sites either for “surface” or “spacial” immobilization of biomacromolecules. The correlation holds between light intensity and the number of readant groups emerged in a matrix.     

The cationization of synthetic polymers in matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry: Investigations of the salt‐to‐analyte ratio

Matrix‐assisted laser desorption/ionization (MALDI) is a soft ionization technique that when used to analyze synthetic polymer analytes often requires the addition of a metal cationization agent (herein termed the “salt”). The choice of both the matrix and the cationization agent needs to be taken into account when considering the polymer under study; different polymers have shown different affinities toward different cationization agents, and their selectivity can change as the matrix changes. Salt‐to‐analyte ratio (S/A) plots are used in this work to investigate the effect of the quantity of cationization agent employed in the analysis of a poly (methylmethacrylate) (PMMA) analyte with different MALDI matrices. The point at which analyte signal stops increasing with the added cationization agent is termed the “cation saturation point,” and it was found to occur around a S/A of 1. When the analyte signal after this point remains constant, it is termed an “ideal case.” The “non‐ideal case” occurs when the analyte signal decreases after the cation saturation point. The amount of matrix present (measured as the matrix‐to‐analyte molar ratio, M/A) and the use of different counterions for the salt are also found to affect the intensity of the analyte signal. In non‐ideal cases, changes in the counterion or an increase in the M/A are found to increase the analyte signal, often converting an initially observed non‐ideal case into an ideal case. Several experiments attempting to uncover the reason for observation of the non‐ideal S/A behavior are also described.     

Photo‐initiated thiol–ene “click” hydrogels from RAFT‐synthesized poly(N‐isopropylacrylamide)

Despite the efficiency and robustness of the widely used copper‐catalyzed 1,3‐dipolar cycloaddition reaction, the use of copper as a catalyst is often not attractive, particularly for materials intended for biological systems. The use of photo‐initiated thiol‐ene as an alternative “click” reaction to synthesize “model networks” is investigated here. Poly(N‐isopropylacrylamide) precursors were synthesized by reversible addition fragmentation chain transfer (RAFT) polymerization and were designed to have trithiocarbonate moieties as end groups. This structure design provides opportunity for subsequent end‐group modifications in preparation for thiol‐ene “click.” Two reaction routes have been proposed and studied to yield thiol and ene moieties. The advantages and disadvantages of each reaction path were investigated to propose a simple but efficient route to prepare copper‐free “click” hydrogels. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013 , 51, 4626–4636     

Computational Design,Synthesis, and Mechanochromic Properties of New Thiophene‐Based π‐Conjugated Chromophores

The possibility of exploiting supramolecular architectures for the preparation of innovative mechanochromic devices has been extended by designing novel thienyl‐substituted 1,4‐bis(ethynyl)benzene dyes, which are characterized by a conjugated, rigid, rodlike core structure. This new family of chromophores was synthesized according to a simple two‐step sequential cross‐coupling reaction, and the optical properties were investigated in solution and in a polymeric matrix. To tune the mechanochromic performances in smart polymer materials, a virtual screening was set up that was able to select a derivative with optimal spectral features. The effective combination of experimental and computational investigations allowed us to spot those homologues with already potential anisotropic and aggregachromic features and characterized by the best spectral properties and luminescent response. The best candidate was synthesized and dispersed into a polyethylene matrix, indeed achieving an “in silico designed” mechanochromic material. Besides the specific applications of this novel material, the integration of computational and experimental techniques reported here defines an efficient protocol that can be applied to make a selection among similar dye candidates, which constitute the essential responsive part of such supramolecular devices.     

Multiple-site ligand binding to flexible macromolecules: Separation of global and local conformational change and an iterative mobile clustering approach

This article concerns the calculation of equilibria of ligand binding to multiple sites in macromolecules in the presence of conformational flexibility and conformation-dependent interaction among the sites. A formulation of this problem is presented in which global conformational changes are distinguished from conformational changes that are confined to “locally flexible regions.” The formalism is quite general in that ligands of different types, multivalent binding sites, tautomeric binding sites, and sites that bind more than one type of ligand can be accommodated. Strictly speaking, the separation of the conformational problem into global and local parts does not impose any loss of generality, although in practice it is necessary to restrict the number of global and local conformers. Because of the combinatorics of binding and conformational states, the computational complexity of a problem having only local conformational flexibility grows exponentially with the number of sites and the number of locally flexible regions. An iterative mobile clustering method for cutting off this exponential growth and obtaining approximate solutions with low computational cost is presented and tested. In this method, a binding site is selected, and a “cluster” of strongly interacting sites is set up around it; within the cluster, the binding and conformational states are fully enumerated, whereas the influences of sites outside the cluster on the sites inside are treated by a mean field approximation. The procedure then moves to the next site around which another (possibly overlapping) cluster is formed and the calculation is repeated. The procedure iterates through the list of sites in this way, using the results of previous iterations for the mean-field terms of current iterations until a convergence criterion is met. The method is tested on a large set of randomly generated problems of varying size, whose geometries are chosen to have protein-like statistical properties. It is found that the method is accurate and rapid with the computational cost scaling linearly to quadratically with the number of sites, except for a minority of cases in which large clusters occur by chance. The new method is more accurate than a Monte Carlo method, and may be faster or slower depending on the clustering criteria and details of the macromolecule. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1091–1111, 1999     

Intracellular Delivery of Native Proteins Facilitated by Cell‐Penetrating Poly(disulfide)s

Intracellular delivery of therapeutic proteins is highly challenging and in most cases requires chemical or genetic modifications. Herein, two complementary approaches for endocytosis‐independent delivery of proteins to live mammalian cells are reported. By using either a “glycan” tag naturally derived from glycosylated proteins or a “traceless” tag that could reversibly label native lysines on non‐glycosylated proteins, followed by bioorthogonal conjugation with cell‐penetrating poly(disulfide)s (CPDs), we achieved intracellular delivery of proteins (including antibodies and enzymes) which, upon spontaneous degradation of CPDs, led to successful release of their “native” functional forms with immediate bioavailability.     

Rung 3.5 density functionals: Another step on Jacob's ladder

Applications of density functional theory (DFT) to computational chemistry and solid‐state physics rely on a “Jacob's Ladder” of progressively more complicated approximations to the many‐body exchange‐correlation (XC) density functional. Accurate, computationally tractable DFT calculations on large and periodic systems remain challenging for existing XC functionals. Simple XC functionals on the three lowest rungs of Jacob's Ladder are insufficiently accurate for many properties, while fourth‐rung hybrid functionals incorporating nonlocal information can be prohibitively expensive. This perspective presents our work toward a compromise, a new class of “Rung 3.5” functionals that incorporate a linear dependence on the nonlocal one‐particle density matrix. This work reviews these functionals' formal underpinning, numerical performance, and prospects for modeling solids and surfaces. © 2012 Wiley Periodicals, Inc.     

Tunneling in the presence of fluctuations: the stochastic liouville equation approach

The stochastic Liouville equation is used to discuss the role of fluctuations in tunneling dynamics. Emphasis is given to the case where the matrix elements of the hamiltonian are continuous-time Markov chains, since in this case the computational scheme is shown to be very simple, being based on matrix manipulations. The utility of the method for arbitrary correlation times is illustrated in two examples concerning two-level proton tunneling. In the first the role of a fluctuating electric field created by the solvent is discussed and the results are interpreted in terms of “motional narrowing”. In the second example the influence of a strong electromagnetic field (which determines jumps between two potential energy curves) is analyzed for a concrete case, i.e. the tropolone molecule.     

General methods of analysing molecular vibrations

An acute need may arise to develop for the complete analysis of molecular vibrations practically convenient general methods based on coordinates other than “chemical coordinates”. One reason is the proven proposition: Among independent internal coordinates corresponding to a molecule, there cannot be one which describes a small displacement of a chemical group as a whole relative to a certain molecular plane, provided this group contains more than two linearly or three non-linearly arranged atoms. Two methods are presented in some detail. The first is based on the use of X⁰_δ coordinates which are components of “bond vectors” in the “sown” (for each “bond”) Cartesian coordinate system. The second method utilizes X⁰ coordinates, i.e. the components of atomic displacements in the “down” (for each atom) Cartesian coordinate system. Computation of the torsional vibration of transdichloroethane is given as an example illustrating the first method. The Mayants treatment of the symmetry of a molecule, proceeding from elementary considerations which do not use the group theory explicitly and are valid for any coordinates, is expounded in a somewhat improved version. The peculiarities arising when considering the mean-square amplitude matrix, Σ, in X⁰_δ and X⁰ coordinates are also discussed.