Structural and Sequence Characteristics of Long alpha Helices in Globular Proteins

Elucidation of the detailed structural features and sequence requirements for iv helices of various lengths could be very important in understanding secondary structure formation in proteins and, hence. in the protein folding mechanism. An algorithm to characterize the geometry of an alpha helix from its C-alpha coordinates has been developed and used to analyze the structures of long cu helices (number of residues greater than or equal to 25) found in globular proteins, the crystal structure coordinates of which are available from the Brookhaven Protein Data Bank, Ail long a helices can be unambiguously characterized as belonging to one of three classes: linear, curved, or kinked, with a majority being curved. Analysis of the sequences of these helices reveals that the long alpha helices have unique sequence characteristics that distinguish them from the short alpha helices in globular proteins, The distribution and statistical propensities of individual amino acids to occur in long alpha heices are different from those found in short alpha helices, with amino acids having longer side chains and/or having a greater number of functional groups occurring more frequently in these helices, The sequences of the long alpha helices can be correlated with their gross structural features, i.e., whether they are curved, linear, or kinked, and in case of the curved helices, with their curvature.

Structural mobility and transformations in globular proteins

Although globular proteins are endowed with well defined three-dimensional structures, they exhibit substantial mobility within the framework of the given threedimensional structure. The different types of mobility found in proteins by and large correspond to the different levels of organisational hierarchy in protein architecture. They are of considerable structural and functional significance, and can be broadly classified into(a) thermal and conformational fluctuations, (b) segmental mobility, (c) interdomain mobility and (d) intersubunit mobility. Protein crystallographic studies has provided a wealth of information on all of them. The temperature factors derived from X-ray diffraction studies provide a measure of atomic displacements caused by thermal and conformational fluctuations. The variation of displacement along the polypeptide chain have provided functionally significant information on the flexibility of different regions of the molecule in proteins such as myoglobin, lysozyme and prealbumin. Segmental mobility often involves the movement of a region or a segment of a molecule with respect to the rest, as in the transition between the apo and the holo structures of lactate dehydrogenase. It may also involve rigidification of a disordered region of the molecule as in the activation of the zymogens of serine proteases. Transitions between the apo and the holo structures of alcohol dehydrogenase,and between the free and the sugar bound forms of hexokinase, are good examples of interdomain mobility caused by hinge-bending. The capability of different domains to move semi-independently contributes greatly to the versatility of immunoglobulin molecules. Interdomain mobility in citrate synthase appears to be more complex and its study has led to an alternative description of domain closure. The classical and the most thoroughly studied case of intersubunit mobility is that in haemoglobin. The stereochemical mechanism of the action of this allosteric protein clearly brings out the functional subtilities that could be achieved through intersubunit movements. In addition to ligand binding and activation,environmental changes also often cause structural transformations. The reversible transformation between 2 Zn insulin and 4 Zn insulin is caused by changes in the ionic strength of the medium. Adenylate Kinase provides a good example for functionally significant reversible conformational transitions induced by variation in pH. Available evidences indicate that reversible structural transformations in proteins could also be caused by changes in the aqueous environment, including those in the amount of water surrounding protein molecules.

Cluster model of the glass transition

A cluster model of the glass transition has been developed, treating the relative size of the cluster as an order parameter. The model accounts for some of the features of the glass transition.

Cluster analysis of rainfall stations of the Indian peninsula

Principal component analysis is applied to derive patterns of temporal variation of the rainfall at fifty-three stations in peninsular India. The location of the stations in the coordinate space determined by the amplitudes of the two leading eigenvectors is used to delineate them into eight clusters. The clusters obtained seem to be stable with respect to variations in the grid of stations used. Stations within any cluster occur in geographically contiguous areas.

Reversals of polypeptide chain in globular proteins.

A simple algorithm has been developed to detect β-bends and 'loops'-chain reversals containing five amino acid residues, using only coordinates of Cα-atoms from crystal structure data of globular proteins using the above algorithm. Analysis of bends have showed that the total number of bends in each protein (TB) is linearly related to total number of non-hydrophobic residues in that protein which in turn is related linearly to total number of amino acid residues. Secondly, we found that a large number of consecutive bends occur in each protein which give rise to on an average only three independent residues per turn. Positional preference of amino acid residues in chain reversals is stressed. Consideration of pairs of amino acid residues in positions (i + 1) and (i + 2) of bends seems to provide a more reliable basis for predicting chain reversals in proteins.

High pressure transport behaviour of AgI-Ag2O-MoO3 glasses and the cluster model

The effect of pressure on the conductivity of fast ion conducting AgI-Ag2O-MoO3 glasses has been investigated down to 150 K. The observed variation of conductivities appears to support the application of cluster model to the ionic glasses.

Identification and analysis of extended strands and beta-sheets in globular proteins

A method to identify β-sheets in globular proteins from extended strands, using only α-carbon positions, has been developed. The strands that form β-sheets are picked up by means of simple distance criteria. The method has been tested by applying it to three proteins with accurately known secondary structures. It has also been applied to ten other proteins wherein only α-carbon coordinates are available, and the list of β-sheets obtained. The following points are worth noting: (i) The sheets identified by the algorithm are found to agree satisfactorily with the reported ones based on backbone hydrogen bonding, wherever this information is available. (ii) β-Strands that do not form parts of any sheet are a common feature of protein structures. (iii) Such isolated β-strands tend to be short. (iv) The conformation corresponding to the preferred right-handed twist of the sheet is overwhelmingly observed in both the sheet-forming and isolated β-strands.

Glass transition. A new approach based on cluster model of glasses

The structure of real glasses has been considered to be microheterogeneous, composed of clusters and connective tissue. Particles in the cluster are assumed to be highly correlated in positions. The tissue is considered to have a truly amorphous structure with its particles vibrating in highly anharmonic potentials. Glass transition is recognized as corresponding to the melting of clusters. A simple mathematical model has been developed which accounts for various known features associated with glass transition, such as range of glass transition temperature,T g, variation ofT g with pressure, etc. Expressions for configurational thermodynamic properties and transport properties of glass forming systems are derived from the model. The relevence and limitations of the model are also discussed.

Synthesis and characterization of a rare hemiacetalate bridged incomplete View the MathML source dicubane cluster

Reaction of 2-pyridinecarboxaldehyde [(Py)CHO] with Cu(NO3)2·2.5H2O in the presence of 4-aminopyridine and NaN3 in MeOH lead to an incomplete double-cubane [Cu4{PyCH(O)(OMe)}4(N3)4] (1) in 87% isolated yield, representing a rare type of metal cluster containing bridging hemiacetalate ligand [pyCH(O)(OMe)]−1 which was characterized by single crystal structure analysis and variable temperature magnetic behavior.

Proline-containing β-turns in peptides and proteins: Analysis of structural data on globular proteins

Tetrapeptide sequences of the type Z-Pro-Y-X were obtained from the crystal structure data on 34 globular proteins, and used in an analysis of the positional preferences of the individual amino acid residues in the β-turn conformation. The effect of fixing proline as the second position residue in the tetrapeptide sequence was studied by comparing the data obtained on the positional preferences with the corresponding data obtained by Chou and Fasman using the Z-R-Y-X sequence, where no particular residue was fixed in any of the four positions. While, in general, several amino acid residues having relatively very high or very low preferences for specific positions were found to be common to both the Z-Pro-Y-X and Z-R-Y-X sequences, many significant differences were found between the two sets of data, which are to be attributed to specific interactions arising from the presence of the proline residue.

Electrochemisorption - A Cluster Approach

A simple semiempirical quantum chemical approach (Extended Huckel Theory) is shown to give a reasonable description of the electronic structural aspects of chemisorption on the mercury model surface. Chemisorptive interaction of alkali metal atoms and cations, halogen atoms and anions, and water molecules with a charge-neutralized hexagonal close-packed cluster of seven Hg atoms is studied. Adsorption of H, C, N and O atoms on the same model cluster is studied for comparison with earlier work. Chemisorption energies, charge transfer, interaction distance and hydration effects are discussed and compared with experimental results where available.

An HI study of three long-tailed irregular galaxies in the cluster Abell 1367

We present the results on the distribution and kinematics of HI gas with higher sensitivity and in one case of higher spectral resolution as well than reported earlier, of three irregular galaxies CGCG 097073, 097079 and 097087 (UGC 06697) in the cluster Abell 1367. These galaxies are known to exhibit long (50 - 75 kpc) tails of radio continuum and optical emission lines (H alpha) pointing away from the cluster centre and arcs of starformation on the opposite sides of the tails, These features as well as the HI properties, with two of the galaxies (CGCG 097073 and 097079) exhibiting sharper gradients in HI intensity on the side of the tails, are consistent with the HI gas being affected by the ram pressure of the intracluster medium. However the HI emission in all the three galaxies extends to much smaller distances than the radio-continuum and H alpha tails, and are possibly still bound to the parent galaxies. Approximately 20 - 30 per cent of the HI mass is seen to accumulate on the downstream side due to the effects of ram pressure.

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.