Burak Erman

Direct evaluation of thermal fluctuations in proteins using a single-parameter harmonic potential

BACKGROUND An elastic network model is proposed for the interactions between closely (< or = 7.0 A) located alpha-carbon pairs in folded proteins. A single-parameter harmonic potential is adopted for the fluctuations of residues about their mean positions in the crystal structure. The model is based on writing the Kirchhoff adjacency matrix for a protein defining the proximity of residues in space. The elements of the inverse of the Kirchhoff matrix give directly the auto-correlations or cross-correlations of atomic fluctuations. RESULTS The temperature factors of the C alpha atoms of 12 X-ray structures, ranging from a 41 residue subunit to a 633 residue dimer, are accurately predicted. Cross-correlations are also efficiently characterized, in close agreement with results obtained with a normal mode analysis coupled with energy minimization. CONCLUSIONS The simple model and method proposed here provide a satisfactory description of the correlations between atomic fluctuations. Furthermore, this is achieved within computation times at least one order of magnitude shorter than commonly used molecular approaches.

Electrospinning of polyurethane fibers

A segmented polyurethaneurea based on poly(tetramethylene oxide)glycol, a cycloaliphatic diisocyanate and an unsymmetrical diamine were prepared. Urea content of the copolymer was 35 wt%. Electrospinning behavior of this elastomeric polyurethaneurea copolymer in solution was studied. The effects of electrical field, temperature, conductivity and viscosity of the solution on the electrospinning process and morphology and property of the fibers obtained were investigated. Results of observations made by optical microscope, atomic force microscope and scanning electron microscope were interpreted and compared with literature data available on the electrospinning behavior of other polymeric systems.

Understanding the recognition of protein structural classes by amino acid composition

Knowledge of amino acid composition, alone, is verified here to be sufficient for recognizing the structural class, α, β, α+β, or α/β of a given protein with an accuracy of 81%. This is supported by results from exhaustive enumerations of all conformations for all sequences of simple, compact lattice models consisting of two types (hydrophobic and polar) of residues. Different compositions exhibit strong affinities for certain folds. Within the limits of validity of the lattice models, two factors appear to determine the choice of particular folds: 1) the coordination numbers of individual sites and 2) the size and geometry of non‐bonded clusters. These two properties, collectively termed the distribution of non‐bonded contacts, are quantitatively assessed by an eigenvalue analysis of the so‐called Kirchhoff or adjacency matrices obtained by considering the non‐bonded interactions on a lattice. The analysis permits the identification of conformations that possess the same distribution of non‐bonded contacts. Furthermore, some distributions of non‐bonded contacts are favored entropically, due to their high degeneracies. Thus, a competition between enthalpic and entropic effects is effective in determining the choice of a distribution for a given composition. Based on these findings, an analysis of non‐bonded contacts in protein structures was made. The analysis shows that proteins belonging to the four distinct folding classes exhibit significant differences in their distributions of non‐bonded contacts, which more directly explains the success in predicting structural class from amino acid composition. Proteins 29:172–185, 1997. Published 1997 Wiley‐Liss, Inc. This article is a US Goverment work and, as such, is in the public domain in the United States of America.

Theory of elasticity of polymer networks. II. The effect of geometric constraints on junctions

The effects of junction–chain interactions in a real network are analyzed in terms of a model in which the entanglements restricting fluctuations of the junctions are represented by vertical‐wall potential domains. Within these domains the junctions are allowed to fluctuate freely. The domains are assumed to transform linearly with macroscopic strain. The additional stress that arises due to the restrictions on the fluctuations of junction points accounts for the principal departures of experimental stress–strain curves from phantom‐network theory. The size of the entanglement domain, which is the only arbitrary parameter introduced, measures the deviations of the real network from phantom network theory. Calculations based on this model show the reduced force to be approximately independent of strain in the compression region (α<1) and to decrease approximately linearly with the reciprocal of the elongation α in tension (α≳1) over the range accessible to experiment.

Relationships Between Amino Acid Sequence and Backbone Torsion Angle Preferences

Statistical averages and correlations for backbone torsion angles of chymotrypsin inhibitor 2 are calculated by using the Rotational Isomeric States model of chain statistics. Statistical weights of torsional states of ϕψ pairs, needed for the statistics of the full chain, are obtained in two different ways: 1) by using knowledge‐based pairwise dependent ϕψ energy maps from Protein Data Bank (PDB) and 2) by collecting torsion angle data from a large number of random coil configurations of an all‐atom protein model with volume exclusion. Results obtained by using PDB data show strong correlations between adjacent torsion angle pairs belonging to both the same and different residues. These correlations favor the choice of the native‐state torsion angles, and they are strongly context dependent, determined by the specific amino acid sequence of the protein. Excluded volume or steric clashes, only, do not introduce context‐dependent ϕψ correlations into the chain that would affect the choice of native‐state torsional angles. Proteins 2004;55:000–000.

Dynamic mechanical study of amorphous phases in poly(ethylene terephthalate) /nylon-6 blends

The changes in the thermomechanical behaviour of a poly(ethylene terephthalate)/nylon-6 (PET/PA) blend (1:1 by weight) subjected to mechanical and thermal treatments are examined by means of dynamic mechanical measurements. It is established from previous studies that PET/PA blends are incompatible in the isotropic state, but form so-called microfibrillar-reinforced composites upon extrusion, drawing and suitable annealing. This study focuses mainly on the amorphous component of these blends and thus complements that recently performed ( Polymer 1993, 34 , 4669) in which the crystalline phases were analysed. The orientation and crystallization of the homopolymers induced by drawing improve the dispersion of components and induce some compatibility as far as one glass transition temperature is observed. Yet, by annealing the drawn blend at temperatures below the melting temperatures of both components (220°C, for instance) the biphasic character of the composite is enhanced in as much as the microstructures of both the crystalline and amorphous phases are improved and the reorganization of species within separate phases is favoured. The components of the heterogeneous blend become compatible provided that the annealing is performed at a sufficiently high temperature (240°C). This temperature is intermediate between the melting temperature of the two components and allows for the isotropization of the low-melting component PA. The increase of compatibility is attributed to transreactions producing compatibilizing layers of PET/PA copolymers at phase boundaries between microfibrils and the amorphous matrix. Prolonged annealing (25 h) leads to the randomization of the original block copolymers and results in the complete participation of PA in the copolymer, which is evidenced by the disappearance of the glass transition peak of PA.

Property optimization in nitrile rubber composites via hybrid filler systems

Nitrile rubber–PVC composites having carbon black and mica fillers in different compositions as hybrid reinforcements were studied. The effect of the silane treatment of mica, the degree of replacement, and the molecular architecture of nitrile rubbers on static-dynamic mechanical, swelling, and curing behavior of the resultant composites are discussed. The results showed that an increase in unsilanized and silanized mica total filler resulted in increased toughness values and decreased swelling in organic solvents together with increased vibrational damping capacity for all types of nitrile rubber composites, depending on the polyacrylonitrile content.

Predicting important residues and interaction pathways in proteins using Gaussian Network Model: binding and stability of HLA proteins.

A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed.

Molecular Recognition of H3/H4 Histone Tails by the Tudor Domains of JMJD2A: A Comparative Molecular Dynamics Simulations Study

Background Histone demethylase, JMJD2A, specifically recognizes and binds to methylated lysine residues at histone H3 and H4 tails (especially trimethylated H3K4 (H3K4me3), trimethylated H3K9 (H3K9me3) and di,trimethylated H4K20 (H4K20me2, H4K20me3)) via its tandem tudor domains. Crystal structures of JMJD2A-tudor binding to H3K4me3 and H4K20me3 peptides are available whereas the others are not. Complete picture of the recognition of the four histone peptides by the tandem tudor domains yet remains to be clarified. Methodology/Principal Findings We report a detailed molecular dynamics simulation and binding energy analysis of the recognition of JMJD2A-tudor with four different histone tails. 25 ns fully unrestrained molecular dynamics simulations are carried out for each of the bound and free structures. We investigate the important hydrogen bonds and electrostatic interactions between the tudor domains and the peptide molecules and identify the critical residues that stabilize the complexes. Our binding free energy calculations show that H4K20me2 and H3K9me3 peptides have the highest and lowest affinity to JMJD2A-tudor, respectively. We also show that H4K20me2 peptide adopts the same binding mode with H4K20me3 peptide, and H3K9me3 peptide adopts the same binding mode with H3K4me3 peptide. Decomposition of the enthalpic and the entropic contributions to the binding free energies indicate that the recognition of the histone peptides is mainly driven by favourable van der Waals interactions. Residue decomposition of the binding free energies with backbone and side chain contributions as well as their energetic constituents identify the hotspots in the binding interface of the structures. Conclusion Energetic investigations of the four complexes suggest that many of the residues involved in the interactions are common. However, we found two receptor residues that were related to selective binding of the H3 and H4 ligands. Modifications or mutations on one of these residues can selectively alter the recognition of the H3 tails or the H4 tails.

Gaussian model of protein folding

The thermodynamics and kinetics of protein folding depend on the sequence of monomer units along the chain. To explore the sequence dependence, current modeling—all-atom simulations and lattice models, for example—require time-consuming computer simulations. There are currently no analytical models by which folding properties can be computed directly from the monomer sequence. Here we introduce a simple analytical model of folding, based on assuming springlike forces for covalent and noncovalent interactions. Thermodynamic and kinetic properties of folding can be obtained directly for specific sequences in Go-like models. Remarkably, although it is a continuum model, some choices of parameters give the same stable conformations as in the corresponding lattice model. The main point of elasticity-based folding models is that their properties can be understood in complete detail, and with little computational investment. This may be useful for understanding how the shapes of energy landscapes, including stab...