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Protein Secondary Structure (protein + secondary_structure)
Selected AbstractsProtein secondary structure from deep-UV resonance Raman spectroscopy,JOURNAL OF RAMAN SPECTROSCOPY, Issue 1-3 2006Cheng-Yen Huang Abstract Raman spectra of proteins that are obtained with deep ultraviolet excitation contain resonance-enhanced amide bands of the polypeptide backbone, as well as aromatic side chain bands. The amide bands are sensitive to conformation, and can be used to estimate the backbone secondary structure. UV Raman spectra are reported at 206.5 and 197 nm, for a set of 12 proteins with varied secondary structure content, and are used to establish quantitative signatures of secondary structure via least-squares fitting. Amide band enhancement is greater at 197 nm, where basis spectra are established for ,-turn, as well as ,-helix, ,-sheet and unordered structures; the lower signal strength at 206.5 nm does not provide a reliable spectrum for the first of these. Application of these basis spectra is illustrated for the melting of apo-myoglobin. The amide band positions and cross sections are discussed. Copyright © 2006 John Wiley & Sons, Ltd. [source] New energy terms for reduced protein models implemented in an off-lattice force fieldJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 12 2001Tommi Hassinen Abstract Parameterization and test calculations of a reduced protein model with new energy terms are presented. The new energy terms retain the steric properties and the most significant degrees of freedom of protein side chains in an efficient way using only one to three virtual atoms per amino acid residue. The energy terms are implemented in a force field containing predefined secondary structure elements as constraints, electrostatic interaction terms, and a solvent-accessible surface area term to include the effect of solvation. In the force field the main-chain peptide units are modeled as electric dipoles, which have constant directions in ,-helices and ,-sheets and variable conformation-dependent directions in loops. Protein secondary structures can be readily modeled using these dipole terms. Parameters of the force field were derived using a large set of experimental protein structures and refined by minimizing RMS errors between the experimental structures and structures generated using molecular dynamics simulations. The final average RMS error was 3.7 Å for the main-chain virtual atoms (C, atoms) and 4.2 Å for all virtual atoms for a test set of 10 proteins with 58,294 amino acid residues. The force field was further tested with a substantially larger test set of 608 proteins yielding somewhat lower accuracy. The fold recognition capabilities of the force field were also evaluated using a set of 27,814 misfolded decoy structures. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1229,1242, 2001 [source] Vibrational Spectroscopic Studies on the Disulfide Formation and Secondary Conformational Changes of Captopril,HSA Mixture after UV-B IrradiationPHOTOCHEMISTRY & PHOTOBIOLOGY, Issue 6 2005Mei-Jane Li ABSTRACT The effects of pH and ultraviolet-B (UV-B) irradiation on the secondary structure of human serum albumin (HSA) in the absence or presence of captopril were investigated by an attenuated total reflection (ATR)/Fourier transform infrared (FTIR) spectroscopy. The UV-B exposure affecting the stability of captopril before and after captopril,HSA interaction was also examined by using confocal Raman microspectroscopy. The results indicate that the transparent pale-yellow solution for captopril,HSA mixture in all pH buffer solutions, except pH 5.0,7.0, changed into a viscous form then a gel form with UV-B exposure time. The secondary structural transformation of HSA in the captopril,HSA mixture with or without UV-B irradiation was found to shift the maxima amide I peak in IR spectra from 1652 cm,1 assigned to ,-helix structure to 1622 cm,1 because of a ,-sheet structure, which was more evident in pH 3.0, 8.0 or 9.0 buffer solutions. The Raman shift from 1653 cm,1 (,-helix) to 1670 cm,1 (,-sheet) also confirmed this result. Captopril dissolved in distilled water with or without UV-B irradiation was determined to form a captopril disulfide observed from the Raman spectra of 512 cm,1, which was exacerbated by UV-B irradiation. There was little disulfide formation in the captopril,HSA mixture even with long-term UV-B exposure, but captopril might interact with HSA to change the protein secondary structure of HSA whether there was UV-B irradiation or not. The pH of the buffer solution and captopril,HSA interaction may play more important roles in transforming the secondary structure of HSA from ,-helix to ,-sheet in the corresponding captopril,HSA mixture than UV-B exposure. The present study also implies that HSA has the capability to protect the instability of captopril in the course of UV-B irradiation. In addition, a partial unfolding of HSA induced by pH or captopril-HSA interaction under UV-B exposure is proposed. [source] Functional site profiling and electrostatic analysis of cysteines modifiable to cysteine sulfenic acidPROTEIN SCIENCE, Issue 2 2008Freddie R. Salsbury Jr Abstract Cysteine sulfenic acid (Cys-SOH), a reversible modification, is a catalytic intermediate at enzyme active sites, a sensor for oxidative stress, a regulator of some transcription factors, and a redox-signaling intermediate. This post-translational modification is not random: specific features near the cysteine control its reactivity. To identify features responsible for the propensity of cysteines to be modified to sulfenic acid, a list of 47 proteins (containing 49 known Cys-SOH sites) was compiled. Modifiable cysteines are found in proteins from most structural classes and many functional classes, but have no propensity for any one type of protein secondary structure. To identify features affecting cysteine reactivity, these sites were analyzed using both functional site profiling and electrostatic analysis. Overall, the solvent exposure of modifiable cysteines is not different from the average cysteine. The combined sequence, structure, and electrostatic approaches reveal mechanistic determinants not obvious from overall sequence comparison, including: (1) pKas of some modifiable cysteines are affected by backbone features only; (2) charged residues are underrepresented in the structure near modifiable sites; (3) threonine and other polar residues can exert a large influence on the cysteine pKa; and (4) hydrogen bonding patterns are suggested to be important. This compilation of Cys-SOH modification sites and their features provides a quantitative assessment of previous observations and a basis for further analysis and prediction of these sites. Agreement with known experimental data indicates the utility of this combined approach for identifying mechanistic determinants at protein functional sites. [source] Building native protein conformation from NMR backbone chemical shifts using Monte Carlo fragment assemblyPROTEIN SCIENCE, Issue 8 2007Haipeng Gong Abstract We have been analyzing the extent to which protein secondary structure determines protein tertiary structure in simple protein folds. An earlier paper demonstrated that three-dimensional structure can be obtained successfully using only highly approximate backbone torsion angles for every residue. Here, the initial information is further diluted by introducing a realistic degree of experimental uncertainty into this process. In particular, we tackle the practical problem of determining three-dimensional structure solely from backbone chemical shifts, which can be measured directly by NMR and are known to be correlated with a protein's backbone torsion angles. Extending our previous algorithm to incorporate these experimentally determined data, clusters of structures compatible with the experimentally determined chemical shifts were generated by fragment assembly Monte Carlo. The cluster that corresponds to the native conformation was then identified based on four energy terms: steric clash, solvent-squeezing, hydrogen-bonding, and hydrophobic contact. Currently, the method has been applied successfully to five small proteins with simple topology. Although still under development, this approach offers promise for high-throughput NMR structure determination. [source] Structural composition of ,I - and ,II -proteinsPROTEIN SCIENCE, Issue 2 2003Narasimha Sreerama Abstract Circular dichroism spectra of proteins are sensitive to protein secondary structure. The CD spectra of ,-rich proteins are similar to those of model ,-helices, but ,-rich proteins exhibit CD spectra that are reminiscent of CD spectra of either model ,-sheets or unordered polypeptides. The existence of these two types of CD spectra for ,-rich proteins form the basis for their classification as ,I - and ,II -proteins. Although the conformation of ,-sheets is largely responsible for the CD spectra of ,I -proteins, the source of ,II -protein CD, which resembles that of unordered polypeptides, is not completely understood. The CD spectra of unordered polypeptides are similar to that of the poly(Pro)II helix, and the poly(Pro)II-type (P2) structure forms a significant fraction of the unordered conformation in globular proteins. We have compared the ,-sheet and P2 structure contents in ,-rich proteins to understand the origin of ,II -protein CD. We find that ,II -proteins have a ratio of P2 to ,-sheet content greater than 0.4, whereas for ,I -proteins this ratio is less than 0.4. The ,-sheet content in ,I -proteins is generally higher than that in ,II -proteins. The origin of two classes of CD spectra for ,-rich proteins appears to lie in their relative ,-sheet and P2 structure contents. [source] Probability-based protein secondary structure identification using combined NMR chemical-shift dataPROTEIN SCIENCE, Issue 4 2002Yunjun Wang Abstract For a long time, NMR chemical shifts have been used to identify protein secondary structures. Currently, this is accomplished through comparing the observed 1H,, 13C,, 13C,, or 13C, chemical shifts with the random coil values. Here, we present a new protocol, which is based on the joint probability of each of the three secondary structural types (,-strand, ,-helix, and random coil) derived from chemical-shift data, to identify the secondary structure. In combination with empirical smooth filters/functions, this protocol shows significant improvements in the accuracy and the confidence of identification. Updated chemical-shift statistics are reported, on the basis of which the reliability of using chemical shift to identify protein secondary structure is evaluated for each nucleus. The reliability varies greatly among the 20 amino acids, but, on average, is in the order of: 13C,>13C,>1H,>13C,>15N>1HN to distinguish an ,-helix from a random coil; and 1H,>13C, >1HN ,13C,,13C,,15N for a ,-strand from a random coil. Amide 15N and 1HN chemical shifts, which are generally excluded from the application, in fact, were found to be helpful in distinguishing a ,-strand from a random coil. In addition, the chemical-shift statistical data are compared with those reported previously, and the results are discussed. A JAVA User Interface program has been developed to make the entire procedure fully automated and is available via http://ccsr3150-p3.stanford.edu. [source] Neuro-fuzzy structural classification of proteins for improved protein secondary structure predictionPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 8 2003Joachim A. Hering Abstract Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins. [source] A rapid method for assessing lipid:protein and detergent:protein ratios in membrane-protein crystallizationACTA CRYSTALLOGRAPHICA SECTION D, Issue 1 2003Corrie J. B. DaCosta A simple procedure for rapidly measuring lipid:protein ratios and detergent concentrations at different stages of the solubilization, purification and crystallization of membrane proteins has been developed. Fourier-transform infrared spectra recorded from 10,µl aliquots of solution using a single-bounce diamond-attenuated total reflectance apparatus exhibit characteristic bands arising from the vibrations of lipid, protein and detergent. Lipid:protein molar ratios as low as 5:1 (for a protein with a molecular weight of 300,kDa) are determined by comparing the ratio of the integrated intensity of the lipid ester carbonyl band near 1740,cm,1 with the protein amide I band near 1650,cm,1. Detergent concentrations at levels well below the critical micellar concentration of most detergents are determined by comparing the integrated intensities of the detergent vibrations, particularly in the 1200,1000,cm,1 region, with a standard curve. Protein amide I band-shape analysis provides insight into the effects of detergents on protein secondary structure. The importance of monitoring detergent concentration changes during simple procedures, such as the concentration of a membrane protein by ultrafiltration, is demonstrated. This analytical tool has been used to rapidly establish protocols for minimizing lipid and detergent levels in solubilized membrane-protein samples. [source] Dense-core and diffuse A, plaques in TgCRND8 mice studied with synchrotron FTIR microspectroscopyBIOPOLYMERS, Issue 4 2007Margaret Rak Abstract Plaques composed of the A, peptide are the main pathological feature of Alzheimer's disease. Dense-core plaques are fibrillar deposits of A,, showing all the classical properties of amyloid including ,-sheet secondary structure, while diffuse plaques are amorphous deposits. We studied both plaque types, using synchrotron infrared (IR) microspectroscopy, a technique that allows the chemical composition and average protein secondary structure to be investigated in situ. We examined plaques in hippocampal, cortical and caudal tissue from 5- to 21-month-old TgCRND8 mice, a transgenic model expressing doubly mutant amyloid precursor protein, and displaying impaired hippocampal function and robust pathology from an early age. Spectral analysis confirmed that the congophilic plaque cores were composed of protein in a ,-sheet conformation. The amide I maximum of plaque cores was at 1623 cm,1, and unlike for in vitro A, fibrils, the high-frequency (1680,1690 cm,1) component attributed to antiparallel ,-sheet was not observed. A significant elevation in phospholipids was found around dense-core plaques in TgCRND8 mice ranging in age from 5 to 21 months. In contrast, diffuse plaques were not associated with IR detectable changes in protein secondary structure or relative concentrations of any other tissue components. © 2007 Wiley Periodicals, Inc. Biopolymers 87: 207,217, 2007. This article was originally published online as an accepted preprint. The "Published Online" date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com [source] Folding at the rhythm of the rare codon beatBIOTECHNOLOGY JOURNAL, Issue 8 2008Monica Marin Dr. Abstract The persistent difficulties in the production of protein at high levels in heterologous systems, as well as the inability to understand pathologies associated with protein aggregation, highlight our limited knowledge on the mechanisms of protein folding in vivo. Attempts to improve yield and quality of recombinant proteins are diverse, frequently involving optimization of the cell growth temperature, the use of synonymous codons and/or the co-expression of tRNAs, chaperones and folding catalysts among others. Although protein secondary structure can be determined largely by the amino acid sequence, protein folding within the cell is affected by a range of factors beyond amino acid sequence. The folding pathway of a nascent polypeptide can be affected by transient interactions with other proteins and ligands, the ribosome, translocation through a pore membrane, redox conditions, among others. The translation rate as well as the translation machinery itself can dramatically affect protein folding, and thus the structure and function of the protein product. This review addresses current efforts to better understand how the use of synonymous codons in the mRNA and the availability of tRNAs can modulate translation kinetics, affecting the folding, the structure and the biological activity of proteins. [source] Effect of Sucrose and Maltodextrin on the Physical Properties and Survival of Air-Dried Lactobacillus bulgaricus: An in Situ Fourier Transform Infrared Spectroscopy StudyBIOTECHNOLOGY PROGRESS, Issue 3 2005Harriëtte Oldenhof The effect of sucrose, maltodextrin and skim milk on survival of L. bulgaricus after drying was studied. Survival could be improved from 0.01% for cells that were dried in the absence of protectants to 7.8% for cells dried in a mixture of sucrose and maltodextrin. Fourier transform infrared spectroscopy (FTIR) was used to study the effect of the protectants on the overall protein secondary structure and thermophysical properties of the dried cells. Sucrose, maltodextrin and skim milk were found to have minor effects on the membrane phase behavior and the overall protein secondary structure of the dried cells. FTIR was also used to show that the air-dried cell/protectant solutions formed a glassy state at ambient temperature. 1-Palmitoyl 2-oleoyl phosphatidyl choline (POPC) was used in order to determine if sucrose and maltodextrin have the ability to interact with phospholipids during drying. In addition, the glass transition temperature and strength of hydrogen bonds in the glassy state were studied using this model system. Studies using poly- l -lysine were done in order to determine if sucrose and maltodextrin are able to stabilize protein structure during drying. As expected, sucrose depressed the membrane phase transition temperature (Tm) of POPC in the dried state and prevented conformational changes of poly- l -lysine during drying. Maltodextrin, however, did not depress the Tm of dried POPC and was less effective in preventing conformational changes of poly- l -lysine during drying. We suggest that when cells are dried in the presence of sucrose and maltodextrin, sucrose functions by directly interacting with biomolecules, whereas maltodextrin functions as an osmotically inactive bulking compound causing spacing of the cells and strengthening of the glassy matrix. [source] Prioritizing regions of candidate genes for efficient mutation screening,HUMAN MUTATION, Issue 2 2006Terry A. Braun Abstract The availability of the complete sequence of the human genome has dramatically facilitated the search for disease-causing sequence variations. In fact, the rate-limiting step has shifted from the discovery and characterization of candidate genes to the actual screening of human populations and the subsequent interpretation of observed variations. In this study we tested the hypothesis that some segments of candidate genes are more likely than others to contain disease-causing variations and that these segments can be predicted bioinformatically. A bioinformatic technique, prioritization of annotated regions (PAR), was developed to predict the likelihood that a specific coding region of a gene will harbor a disease-causing mutation based on conserved protein functional domains and protein secondary structures. This method was evaluated by using it to analyze 710 genes that collectively harbor 4,498 previously identified mutations. Nearly 50% of the genes were recognized as disease-associated after screening only 9% of the complete coding sequence. The PAR technique identified 90% of the genes as containing at least one mutation, with less than 40% of the screening resources that traditional approaches would require. These results suggest that prioritization strategies such as PAR can accelerate disease-gene identification through more efficient use of screening resources. Hum Mutat 27(2), 195,200, 2006. © 2006 Wiley-Liss, Inc. [source] 2D representation of protein secondary structure sequences and its applicationsJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 11 2006Liwei Liu Abstract In terms of the classification of the protein secondary structures, we propose a 2D representation of protein secondary structure sequences. The representation are used to display, analyze, and compare the secondary structure sequences. Based on this representation, we assign the structural class to the protein, and verify the advantage or disadvantage of the methods of predicted protein second structure. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1119,1124, 2006 [source] Probability-based protein secondary structure identification using combined NMR chemical-shift dataPROTEIN SCIENCE, Issue 4 2002Yunjun Wang Abstract For a long time, NMR chemical shifts have been used to identify protein secondary structures. Currently, this is accomplished through comparing the observed 1H,, 13C,, 13C,, or 13C, chemical shifts with the random coil values. Here, we present a new protocol, which is based on the joint probability of each of the three secondary structural types (,-strand, ,-helix, and random coil) derived from chemical-shift data, to identify the secondary structure. In combination with empirical smooth filters/functions, this protocol shows significant improvements in the accuracy and the confidence of identification. Updated chemical-shift statistics are reported, on the basis of which the reliability of using chemical shift to identify protein secondary structure is evaluated for each nucleus. The reliability varies greatly among the 20 amino acids, but, on average, is in the order of: 13C,>13C,>1H,>13C,>15N>1HN to distinguish an ,-helix from a random coil; and 1H,>13C, >1HN ,13C,,13C,,15N for a ,-strand from a random coil. Amide 15N and 1HN chemical shifts, which are generally excluded from the application, in fact, were found to be helpful in distinguishing a ,-strand from a random coil. In addition, the chemical-shift statistical data are compared with those reported previously, and the results are discussed. A JAVA User Interface program has been developed to make the entire procedure fully automated and is available via http://ccsr3150-p3.stanford.edu. [source] Protein structure preference, tRNA copy number, and mRNA stem/loop contentBIOPOLYMERS, Issue 6 2004Liaofu Luo Abstract From statistical analyses of protein sequences for humans and Escherichia coli we found that the messenger RNA segment of m -codons (for m=2 to 6) with average high tRNA copy number (TCN) (larger than ,10.5 for humans or ,1.95 for E. coli) preferably code for the , helix and that with low TCN (smaller than ,7.5 for humans or ,1.7 for E. coli) preferably code for coil. Between them there is an intermediate region without correlation to structure preference. For the , strand the preference/ avoidance tendency is not obvious. All strong preference-modes of TCN for protein secondary structures have been deduced. The mutual interaction between two factors,protein secondary structural type and codon TCN,is tested by F distribution. A phenomenological model on the relation between structure preference and translational efficiency or accuracy is proposed. It is pointed out that the structure preference of codons is related to the distribution of mRNA stem/loop content in three TCN regions. © 2004 Wiley Periodicals, Inc. Biopolymers, 2004 [source] | |||||||||||||