Generation and enumeration of compact conformations on the two-dimensional triangular and three-dimensional fcc lattices

We enumerated all compact conformations within simple geometries on the two-dimensional (2D) triangular and three-dimensional (3D) face centered cubic (fcc) lattice. These compact conformations correspond mathematically to Hamiltonian paths and Hamiltonian circuits and are frequently used as simple models of proteins. The shapes that were studied for the 2D triangular lattice included m×n role= presentation style= display: inline; line-height: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3em×nm×n parallelograms, regular equilateral triangles, and various hexagons. On the 3D fcc lattice we generated conformations for a limited class of skewed parallelepipeds. Symmetries of the shape were exploited to reduce the number of conformations. We compared surface to volume ratios against protein length for compact conformations on the 3D cubic lattice and for a selected set of real proteins. We also show preliminary work in extending the transfer matrix method, previously developed by us for the 2D square and the 3D cubic lattices, to the 2D triangular lattice. The transfer matrix method offers a superior way of generating all conformations within a given geometry on a lattice by completely avoiding attrition and reducing this highly complicated geometrical problem to a simple algebraic problem of matrix multiplication

Prediction of protein secondary structure by mining structural fragment database

A new method for predicting protein secondary structure from amino acid sequence has been developed. The method is based on multiple sequence alignment of the query sequence with all other sequences with known structure from the protein data bank (PDB) by using BLAST. The fragments of the alignments belonging to proteins from the PBD are then used for further analysis. We have studied various schemes of assigning weights for matching segments and calculated normalized scores to predict one of the three secondary structures: α-helix, β-sheet, or coil. We applied several artificial intelligence techniques: decision trees (DT), neural networks (NN) and support vector machines (SVM) to improve the accuracy of predictions and found that SVM gave the best performance. Preliminary data show that combining the fragment mining approach with GOR V (Kloczkowski et al, Proteins 49 (2002) 154–166) for regions of low sequence similarity improves the prediction accuracy

Predicting the order in which contacts are broken during single molecule protein stretching experiments

We combine two methods to enable the prediction of the order in which contacts are broken under external stretching forces in single molecule experiments. These two methods are Gô-like models and elastic network models. The Gô-like models have shown remarkable success in representing many aspects of protein behavior, including the reproduction of experimental data obtained from atomic force microscopy. The simple elastic network models are often used successfully to predict the fluctuations of residues around their mean positions, comparing favorably with the experimentally measured crystallographic B-factors. The behavior of biomolecules under external forces has been demonstrated to depend principally on their elastic properties and the overall shape of their structure. We have studied in detail the muscle protein titin and green fluorescent protein and tested for ten other proteins. First, we stretch the proteins computationally by performing stochastic dynamics simulations with the Gô-like model. We obtain the force–displacement curves and unfolding scenarios of possible mechanical unfolding. We then use the elastic network model to calculate temperature factors (B-factors) and compare the slowest modes of motion for the stretched proteins and compare them with the predicted order of breaking contacts between residues in the Gô-like model. Our results show that a simple Gaussian network model is able to predict contacts that break in the next time stage of stretching. Additionally, we have found that the contact disruption is strictly correlated with the highest force exerted by the backbone on these residues. Our prediction of bond-breaking agrees well with the unfolding scenario obtained with the Gô-like model. We anticipate that this method will be a useful new tool for interpreting stretching experiments

Evaluation of left ventricular systolic function with pulsed wave tissue Doppler in rheumatic mitral stenosis

Background: Mitral stenosis (MS) is still the most common complication of acute rheumatic fever in Turkey. Rheumatic carditis affects not only cardiac valves but also myocardium. In this study, we aimed to evaluate the subclinical left ventricular (LV) systolic dysfunction and contraction of short and long axial circumferential and longitudinal fibers by pulsed wave tissue Doppler in rheumatic MS patients who have preserved LV systolic function in 2D echocardiography.Methods: Fifteen severe, 20 moderate rheumatic MS patients hospitalized for mitral balloon valvuloplasty, and 15 patients who had normal echocardiographic findings were included in the study. After routine conventional transthoracic echocardiographic examination, LV myocardial systolic velocities were evaluated with pulsed wave tissue Doppler in the short and long axis with simultaneous electrocardiographic monitoring.Results: Long axis first systolic velocity (SW1) of mild-moderate and severe MS was much lower than normal group (10.7 ± 2.3 in normal group vs. 7.9 ± 1.3 in mild-moderate MS group vs. 6.2 ± 1.4 in severe MS group, p < 0.001). Long axis Q-SW1 duration was longer in mild-moderate MS group (145 ± 32 in normal group vs. 199 ± 43 in mild-moderate MS group, p = 0.001). Short axis Q-SW2 duration was longer in normal group compared to mild-moderate and severe MS groups (298 ± 41 in normal group vs. 245 ± 37 in mild-moderate MS group vs. 234 ± 26 in severe MS group, p < 0.001). Significant correlation between mitral valve area and SW1, Q-SW1 was determined (p = 0.01).Conclusions: Even if LV functions are normal with conventional 2D echocardiography, subclinical systolic dysfunction exists in MS. Also, there is a dyssynchrony between contraction of longitudinal and circumferential myofibrils

Thermostability in endoglucanases is fold-specific

<p>Abstract</p> <p>Background</p> <p>Endoglucanases are usually considered to be synergistically involved in the initial stages of cellulose breakdown-an essential step in the bioprocessing of lignocellulosic plant materials into bioethanol. Despite their economic importance, we currently lack a basic understanding of how some endoglucanases can sustain their ability to function at elevated temperatures required for bioprocessing, while others cannot. In this study, we present a detailed comparative analysis of both thermophilic and mesophilic endoglucanases in order to gain insights into origins of thermostability. We analyzed the sequences and structures for sets of endoglucanase proteins drawn from the Carbohydrate-Active enZymes (CAZy) database.</p> <p>Results</p> <p>Our results demonstrate that thermophilic endoglucanases and their mesophilic counterparts differ significantly in their amino acid compositions. Strikingly, these compositional differences are specific to protein folds and enzyme families, and lead to differences in intramolecular interactions in a fold-dependent fashion.</p> <p>Conclusions</p> <p>Here, we provide fold-specific guidelines to control thermostability in endoglucanases that will aid in making production of biofuels from plant biomass more efficient.</p

The ribosome structure controls and directs mRNA entry, translocation and exit dynamics

The protein-synthesizing ribosome undergoes large motions to effect the translocation of tRNAs and mRNA; here the domain motions of this system are explored with a coarse-grained elastic network model using normal mode analysis. Crystal structures are used to construct various model systems of the 70S complex with/without tRNA, elongation factor Tu and the ribosomal proteins. Computed motions reveal the well-known ratchet-like rotational motion of the large subunits, as well as the head rotation of the small subunit and the high flexibility of the L1 and L7/L12 stalks, even in the absence of ribosomal proteins. This result indicates that these experimentally observed motions during translocation are inherently controlled by the ribosomal shape and only partially dependent upon GTP hydrolysis. Normal mode analysis further reveals the mobility of A- and P-tRNAs to increase in the absence of the E-tRNA. In addition, the dynamics of the E-tRNA is affected by the absence of the ribosomal protein L1. The mRNA in the entrance tunnel interacts directly with helicase proteins S3 and S4, which constrain the mRNA in a clamp-like fashion, as well as with protein S5, which likely orients the mRNA to ensure correct translation. The ribosomal proteins S7, S11 and S18 may also be involved in assuring translation fidelity by constraining the mRNA at the exit site of the channel. The mRNA also interacts with the 16S 3’ end forming the Shine-Dalgarno complex at the initiation step; the 3’ end may act as a ‘hook’ to reel in the mRNA to facilitate its exit

GOR V server for protein secondary structure prediction

We have created the GOR V web server for protein secondary structure prediction. The GOR V algorithm combines information theory, Bayesian statistics and evolutionary information. In its fifth version, the GOR method reached (with the full jack-knife procedure) an accuracy of prediction Q3 of 73.5%. Although GOR V has been among the most successful methods, its online unavailability has been a deterrent to its popularity. Here, we remedy this situation by creating the GOR V server

The Extent of Cooperativity of Protein Motions Observed with Elastic Network Models Is Similar for Atomic and Coarser-Grained Models

Coarse-grained elastic network models have been successful in determining functionally relevant collective motions. The level of coarse-graining, however, has usually focused on the level of one point per residue. In this work, we compare the applicability of elastic network models over a broader range of representational scales. We apply normal mode analysis for multiple scales on a highresolution protein data set using various cutoff radii to define the residues considered to be interacting, or the extent of cooperativity of their motions. These scales include the residue-, atomic-, proton-, and explicit solvent-levels. Interestingly, atomic, proton, and explicit solvent level calculations all provide similar results at the same cutoff value, with the computed mean-square fluctuations showing only a slightly higher correlation (0.61) with the experimental temperature factors from crystallography than the results of the residue-level coarse-graining. The qualitative behavior of each level of coarse graining is similar at different cutoff values. The correlations between these fluctuations and the number of internal contacts improve with increased cutoff values. Our results demonstrate that atomic level elastic network models provide an improved representation for the collective motions of proteins compared to the coarse-grained models