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Porin of Haemophilus influenzae type b (341 amino acids; M(r) 37782) determines the permeability of the outer membrane to low molecular mass compounds. Purified Hib porin was subjected to chemical modification of lysine residues by succinic anhydride. Electrospray ionization mass spectrometry identified up to 12 modifications per porin molecule. Tryptic digestion of modified Hib porin followed by reverse phase chromatography and matrix assisted laser desorption ionization time-of-flight mass spectrometry mapped the succinylation sites. Most modified lysines are positioned in surface-located loops, numbers 1 and 4 to 7. Succinylated porin was reconstituted into planar lipid bilayers, and biophysical properties were analyzed and compared to Hib porin: there was an increased average single channel conductance compared to Hib porin (1.24 +/- 0.41 vs. 0.85 +/- 0.40 nanosiemens). The voltage-gating activity of succinylated porin differed considerably from that of Hib porin. The threshold voltage for gating was decreased from 75 to 40 mV. At 80 mV, steady-state conductance for succinylated porin was 50-55% of the instantaneous conductance. Hib porin at 80 mV showed a decrease to 89-91% of the instantaneous current levels. We propose that surface-located lysine residues are determinants of voltage gating for porin of Haemophilus influenzae type b. [ABSTRACT FROM AUTHOR]

One important problem when calculating structures of biomolecules from NMR data is distinguishing converged structures from outlier structures. This paper describes how Principal Components Analysis (PCA) has the potential to classify calculated structures automatically, according to correlated structural variation across the population. PCA analysis has the additional advantage that it highlights regions of proteins which are varying across the population. To apply PCA, protein structures have to be reduced in complexity and this paper describes two different representations of protein structures which achieve this. The calculated structures of a 28 amino acid peptide are used to demonstrate the methods. The two different representations of protein structure are shown to give equivalent results, and correct results are obtained even though the ensemble of structures used as an example contains two different protein conformations. The PCA analysis also correctly identifies the structural differences between the two conformations. [ABSTRACT FROM AUTHOR]

S-layer proteins have a wide range of application potential due to their characteristic features concerning self-assembling, assembling on various surfaces, and forming of isoporous structures with functional groups located on the surface in an identical position and orientation. Although considerable knowledge has been experimentally accumulated on the structure, biochemistry, assemble characteristics, and genetics of S-layer proteins, no structural model at atomic resolution has been available so far. Therefore, neither the overall folding of the S-layer proteins—their tertiary structure—nor the exact amino acid or domain allocations in the lattices are known. In this paper, we describe the tertiary structure prediction for the S-layer protein SbsB from Geobacillus stearothermophilus PV72/p2. This calculation was based on its amino acid sequence using the mean force method (MF method) achieved by performing molecular dynamic simulations. This method includes mainly the thermodynamic aspects of protein folding as well as steric constraints of the amino acids and is therefore independent of experimental structure analysis problems resulting from biochemical properties of the S-layer proteins. Molecular dynamic simulations were performed in vacuum using the simulation software NAMD. The obtained tertiary structure of SbsB was systematically analyzed by using the mean force method, whereas the verification of the structure is based on calculating the global free energy minimum of the whole system. This corresponds to the potential of mean force, which is the thermodynamically most favorable conformation of the protein. Finally, an S-layer lattice was modeled graphically using CINEMA4D and compared with scanning force microscopy data down to a resolution of 1 nm. The results show that this approach leads to a thermodynamically favorable atomic model of the tertiary structure of the protein, which could be verified by both the MF Method and the lattice model. [ABSTRACT FROM AUTHOR]

For a given DNA sequence, it is well known that pair wise alignment schemes are used to determine the similarity with the DNA sequences available in the databanks. The efficiency of the alignment decides the type of amino acids and its corresponding proteins. In order to evaluate the given DNA sequence for its proteomic identity, a pattern matching approach is proposed in this paper. A block based semi-global alignment scheme is introduced to determine the similarity between the DNA sequences (known and given). The two DNA sequences are divided into blocks of equal length and alignment is performed which minimizes the computational complexity. The efficiency of the alignment scheme is evaluated using the parameter, percentage of similarity (POS). Four essential DNA version of the amino acids that emphasize the importance of proteomic functionalities are chosen as patterns and matching is performed with the known and given DNA sequences to determine the similarity between them. The ratio of amino acid counts between the two sequences is estimated and the results are compared with that of the POS value. It is found from the experimental results that higher the POS value and the pattern matching higher are the similarity between the two DNA sequences. The optimal block is also identified based on the POS value and amino acids count. [ABSTRACT FROM AUTHOR]

Not all proteins form well defined three-dimensional structures in their native states. Some amino-acid sequences appear to strongly favour the disordered state, whereas some can apparently transition between disordered and ordered states under the influence of changes in the biological environment, thereby playing an important role in processes such as signalling. Although important biologically, for the structural biologist disordered regions of proteins can be disastrous even preventing successful structure determination. The accurate prediction of disorder is therefore important, not least for directing the design of expression constructs so as to maximize the chances of successful structure determination. Such design criteria have become integral to the construct-design strategies of laboratories within the Structural Proteomics In Europe (SPINE) consortium. This paper assesses the current state of the art in disorder prediction in terms of prediction reliability and considers how best to use these methods to guide construct design. Finally, it presents a brief discussion as to how methods of prediction might be improved in the future. [ABSTRACT FROM AUTHOR]

The validity of complexity simplifications for proteins with different structural features may be different. In this paper, the simplification for proteins is studied using the ratios of successful prediction of structural class under a presumed amino-acid-grouping scheme with a composition-coupled method. It is found that for the α-class proteins, a two-letter alphabet may cover the degree of freedom to characterize the complexity of the class; for the β-class proteins, a 7-letter alphabet might indicate the minimal number of residue types to reconstruct the class feature of the natural proteins; for the α + β-class proteins and the α/β-class proteins, the redundancy of the compositions is weak and the simplification leads to a great loss of the information related to the corresponding structural classes. [ABSTRACT FROM AUTHOR]

Disordered regions of proteins are highly abundant in various biological processes, involving regulation and signaling and also in relation with cancer, cardiovascular, autoimmune diseases and neurodegenerative disorders. Hence, recognizing disordered regions in proteins is a critical task. In this paper, we presented a new feature encoding technique built from physicochemical properties of residues selected as per the chaotic structure of related protein sequence. Our feature vector has been tested with various classification algorithms on an up-to-date data set and also compared to other methods. The proposed method shows better classification performance than many methods in terms of accuracy, sensitivity and specificity. Our results suggest that the new method that links the residues and their physicochemical properties using Lyapunov exponents is highly effective in recognition of disordered regions. [ABSTRACT FROM AUTHOR]

Highly selective nucleocytoplasmic molecular transport is critical to eukaryotic cells, which is illustrated by size-filtering diffusion and karyopherin-mediated passage mechanisms. However, a considerable number of large proteins without nuclear localization signals are localized to the nucleus. In this paper, we provide evidence for the spontaneous migration of large proteins in a karyopherin-independent manner. Time-lapse observation of a nuclear transport assay revealed that several large molecules spontaneously and independently pass through the nuclear pore complex (NPC). The amphiphilic motifs were sufficient to overcome the selectivity barrier of the NPC. Furthermore, the amphiphilic property of these proteins enables altered local conformation in hydrophobic solutions so that elevated surface hydrophobicity facilitates passage through the nuclear pore. The molecular dynamics simulation revealed the conformational change of the amphiphilic structure that exposes the hydrophobic amino acid residues to the outer surface in a hydrophobic solution. These results contribute to the understanding of nucleocytoplasmic molecular sorting and the nature of the permeability barrier. [ABSTRACT FROM AUTHOR]

Up to now, various approaches for phylogenetic analysis have been developed. Almost all of them put stress on analyzing nucleic acid sequences or protein primary sequences. In this paper, we propose a new sequence distance for efficient reconstruction of phylogenetic trees based on the distribution of length about common subsequences between two sequences. We describe some applications of this method, which not only show the validity of the method, but also suggest a number of novel phylogenetic insights. [ABSTRACT FROM AUTHOR]

Background: The covariation of two sites in a protein is often used as the degree of their coevolution. To quantify the covariation many methods have been developed and most of them are based on residues position-specific frequencies by using the mutual information (MI) model. Results: In the paper, we proposed several new measures to incorporate new biological constraints in quantifying the covariation. The first measure is the mutual information with the amino acid background distribution (MIB), which incorporates the amino acid background distribution into the marginal distribution of the MI model. The modification is made to remove the effect of amino acid evolutionary pressure in measuring covariation. The second measure is the mutual information of residues physicochemical properties (MIP), which is used to measure the covariation of physicochemical properties of two sites. The third measure called MIBP is proposed by applying residues physicochemical properties into the MIB model. Moreover, scores of our new measures are applied to a robust indicator conn(k) in finding the covariation signal of each site. Conclusions: We find that incorporating amino acid background distribution is effective in removing the effect of evolutionary pressure of amino acids. Thus the MIB measure describes more biological background information for the coevolution of residues. Besides, our analysis also reveals that the covariation of physicochemical properties is a new aspect of coevolution information. [ABSTRACT FROM AUTHOR]

Surface Enhanced Raman Spectroscopy (SERS) has demonstrated significant benefit in the identification of biological molecules. In this paper we have examined how to identify and differentiate the 150 kDa protein myeloperoxidase (MPO) from its corresponding antibody (Ab) and their immunocomplex through the use of SERS. The SERS signal of these biological molecules was enabled by 40 nm gold nanoparticles. The SERS spectra for both MPO and the Ab (an IgG molecule) demonstrated results consistent with previous published work on the Raman spectra of MPO and IgG antibodies. The immunocomplex SERS spectra showed peak shifts and intensity variations that could be attributed to conformational changes that occur during immunocomplex formation. Several key spectral areas have been identified which correspond to specific amino acids being shielded from undergoing resonance while new amino acid residues are made visible in the SERS spectrum of the immunocomplex and could be a result of conformational binding. These results indicate that SERS can be used to identify binding events and distinguish an immunocomplex from its individual components. [ABSTRACT FROM AUTHOR]

Background: Ever since the ground-breaking work of Anfinsen et al. in which a denatured protein was found to refold to its native state, it has been frequently stated by the protein fold prediction community that all the information required for protein folding lies in the amino acid sequence. Recent in vitro experiments and in silico computational studies, however, have shown that cotranslation may affect the folding pathway of some proteins, especially those of ancient folds. In this paper aspects of cotranslational folding have been incorporated into a protein structure prediction algorithm by adapting the Rosetta program to fold proteins as the nascent chain elongates. This makes it possible to conduct a pairwise comparison of folding accuracy, by comparing folds created sequentially from each end of the protein. Results: A single main result emerged: in 94% of proteins analyzed, following the sense of translation, from N-terminus to C-terminus, produced better predictions than following the reverse sense of translation, from the C-terminus to N-terminus. Two secondary results emerged. First, this superiority of N-terminus to C-terminus folding was more marked for proteins showing stronger evidence of cotranslation and second, an algorithm following the sense of translation produced predictions comparable to, and occasionally better than, Rosetta. Conclusions: There is a directionality effect in protein fold prediction. At present, prediction methods appear to be too noisy to take advantage of this effect; as techniques refine, it may be possible to draw benefit from a sequential approach to protein fold prediction. [ABSTRACT FROM AUTHOR]

Physicochemcial properties of amino acids are important factors in determining protein structure and function. Most approaches make use of averaged properties over entire domains or even proteins to analyze their structure or function. This level of coarseness tends to hide the richness of the variability in the different properties across functional domains. This paper studies the conservation of physicochemical properties in a functionally similar family of proteins using a novel wavelet-based technique known as multiresolution analysis. Such an analysis can help uncover characteristics that can otherwise remain hidden. We have studied the protein kinase family of sequences and our findings are as follows: (a) a number of different properties are conserved over the functional catalytic domain irrespective of the sequence identities; (b) conservation of properties can be observed at different frequency levels and they agree well with the known structural/functional properties of the subdomains for the protein kinase family; (c) structural differences between the different kinase family members are reflected in the waveforms; and (d) functionally important mutations show distortions in the waveforms of conserved properties. The potential usefulness of the above findings in identifying functionally similar sequences in the twilight and midnight zones is demonstrated through a simple prediction model for the protein kinase family which achieved a recall of 93.7% and a precision of 96.75% in cross-validation tests. [ABSTRACT FROM AUTHOR]

It is known that several naturally occurring substances known as osmolytes increase the conformational stability of proteins. Bolen and co-worker proposed the osmophobic theory, which asserts the osmolyte effect occurs because of an unfavorable interaction of osmolytes mainly with the protein backbone, based on the results on the transfer Gibbs energy of amino acids (Δg) [Bolen and Baskakov (2001) J. Mol. Biol. 310, 955–963]. In this paper, we report the effect of sarcosine on the conformational stability (ΔG) of RNase Sa (96 residues and one disulfide bond) and four mutant proteins. The thermal denaturation curves for RNase Sa in sarcosine fitted a two-state model on nonlinear least-squares analysis. All the RNase Sa proteins were stabilized by sarcosine. For example, the increase in stability of the wild-type protein in 4 M sarcosine due to the osmolyte effect (ΔoΔG) is 3.2 kcal/mol. Mutational analysis of the osmolyte effect indicated that the changed ΔoΔG values upon mutation (ΔmΔoΔG), as estimated from the Δg values, are similar to the experimental values. Structural-based analysis of the osmolyte effect was also performed using model denatured structures: (a) a fully extended model (single chain) with no disulfide bond, (b) two-part, unfolded models (two chains) with a disulfide bond constructed through molecular dynamic (MD) simulation, and (c) a two-part, folded model (two chains). The two-part, unfolded models were expected to be more suitable as denatured structures. The ΔoΔG values calculated using the two-part, unfolded models were more consistent with experimental values than those calculated using the fully extended and two-part, folded models. This suggests that MD simulation is useful for testing denatured structures. These results indicate that the osmophobic theory can explain the osmolyte effect on protein stability. [ABSTRACT FROM PUBLISHER]

The complete primary structure of the constant part of the μ-chain-disease protein, BOT, was established. It includes the whole CH2, CH3 and CH4 domains. Two amino acid changes were found, at positions 309 (Ser ↵ Gly) and 333 (Val ↵ Gly) (GAL numbering). In two additional monoclonal n chains (SCO and CO), the same positions showed an amino acid variability. From these data it may be concluded that four types of μ chains exist in the human: (1) GAL type with Ser-309 and Val-333; (2) OU type with Gly-309 and Val-333; (3) SCO type with Ser-309 and Gly-333; (4) BOT/CO type with Gly-309 and Gly-333. The meaning of this molecular polymorphism is discussed. [ABSTRACT FROM AUTHOR]

Abstract: Chirality is one of the basic, unique, and most appealing features of biological molecules; however, many intriguing chiral phenomena in biological world remains insufficiently revealed yet. In this research, we fabricated chiral surfaces by assembling natural chiral amino acids-cysteine of opposite configurations (D- and L-) onto gold surfaces, respectively, and investigated the adhesion of the L929 fibroblast on them. No significant differences were observed in the density of adherent cells under serum-free culture condition; while in serum-containing condition, significantly more cells adhered on the L-Cys assembled surfaces. This phenomenon suggested that serum protein might play an important role in mediating the selective adhesion of cells on chiral surfaces. Hence, we adopted both radiolabeling and surface plasmon resonance (SPR) techniques to monitor protein adsorption onto the above surfaces. The results evidently showed more proteins adsorbed onto surfaces assembled with L-Cys. We propose that the difference in protein adsorption on chiral surfaces as demonstrated in this paper might not only shed light on the ensuing investigation of bio-related chirality phenomena, but also provide a novel strategy for the rational design and fabrication of novel biomaterials and bio-related devices based on chiral effects. [Copyright &y& Elsevier]

The discovery of novel peptide drugs could he simplified by a new protocol for building diverse, messenger RNA (mRNA)-encoded peptide libraries. This strategy has been hindered previously by the difficulty of generating sufficient amounts of tRNAs bearing diverse, non-standard amino acid building blocks. However, the recent paper in the journal "Chemistry and Biology" describes how a simple chemical transformation can he used to generate pools of methylated, non-standard aminoacyl-tRNA5 for the convenient synthesis of diverse libraries of drug-like peptides. Libraries of mRNA-encoded proteins and peptides have been a popular choice for identifying functional peptides that modulate a variety of biological targets. The nature of ribosomal synthesis enables peptides to he encoded with mRNA, making it relatively simple to identify library members with a desired activity.

Abstract: Three-dimensional structures of proteins are the support of their biological functions. Their folds are stabilized by contacts between residues. Inner protein contacts are generally described through direct atomic contacts, i.e. interactions between side-chain atoms, while contact prediction methods mainly used inter-Cα distances. In this paper, we have analyzed the protein contacts on a recent high quality non-redundant databank using different criteria. First, we have studied the average number of contacts depending on the distance threshold to define a contact. Preferential contacts between types of amino acids have been highlighted. Detailed analyses have been done concerning the proximity of contacts in the sequence, the size of the proteins and fold classes. The strongest differences have been extracted, highlighting important residues. Then, we studied the influence of five different side-chain conformation prediction methods (SCWRL, IRECS, SCAP, SCATD and SCCOMP) on the distribution of contacts. The prediction rates of these different methods are quite similar. However, using a distance criterion between side chains, the results are quite different, e.g. SCAP predicts 50% more contacts than observed, unlike other methods that predict fewer contacts than observed. Contacts deduced are quite distinct from one method to another with at most 75% contacts in common. Moreover, distributions of amino acid preferential contacts present unexpected behaviours distinct from previously observed in the X-ray structures, especially at the surface of proteins. For instance, the interactions involving Tryptophan greatly decrease. [Copyright &y& Elsevier]

Methylation of lysine 27 on histone H3 (H3K27me) by the Polycomb complex (PRC2) proteins is associated with gene silencing in many developmental processes. A cluster of recent papers () identify the JmjC-domain proteins UTX and JMJD3 as H3K27-specific demethylases that remove this methyl mark, enabling the activation of genes involved in animal body patterning and the inflammatory response. [Copyright &y& Elsevier]

Abstract: This paper focuses on the prediction of the dimensionless retention time of proteins (DRT) in hydrophobic interaction chromatography (HIC) by means of mathematical models based on characteristics of the surface hydrophobicity distribution. We introduce a new parameter, called hydrophobic imbalance (HI), obtained from the three-dimensional structure of proteins. This parameter quantifies the displacement of the superficial geometric centre of the protein when the effect of the hydrophobicity of each amino acid is considered. This parameter is simpler and less expensive than those reported previously. We use HI as a way to incorporate information about the surface hydrophobicity distribution in order to improve the prediction of DRT. We tested the performance of our DRT predictive models in a set of 15 proteins. This set includes four proteins whose DRTs are known as very difficult to predict. By means of the variable HI, it was possible to improve the predictive characteristics obtained by models based on the average surface hydrophobicity (ASH) by 9.1%. Also, we studied linear multivariable models based on characteristics determined from the HI. By using this multivariable model, a correlation coefficient of 0.899 was obtained. With this model, we managed to improve the predictive characteristics shown by previous models based on ASH by 31.8%. [Copyright &y& Elsevier]

The ability to rationally engineer a protein with altered stability depends upon the detailed understanding of the role of noncovalent interactions in defining thermodynamic properties of proteins. In this paper, we used T. celer L30e as a model to address the question of the role of charge—charge interactions in defining the stability of this protein. A total of 26 single-site charge-to-alanine variants of this protein were generated, and the stability of these proteins was determined using thermal- and denaturant-induced unfolding. It was found that, although L30e is isolated from a thermophilic organism and is highly thermostable, some of the substitutions lead to a further increase in the transition temperature. Analysis of the effects of high ionic strength on the stabilities of L30e variants shows that the long-range charge—charge interactions are as important as the short-range (salt bridge) interactions. The changes in stabilities of the T. celer L30e protein variants were compared with the changes in the energy of charge—charge interactions calculated using different computational models. It was found that there is a good qualitative agreement between experimental and calculated data: for 70-80% (19-21 of 26, confidence p < 0.003) of the variants, computational models predict correctly the sign of the stability changes. In particular, computational models identify correctly those charged amino acid residue substitutions of which led to enhancement in thermostability. Thus, optimization of the charge—charge interactions might be a useful approach for the rational increase in protein stability. [ABSTRACT FROM AUTHOR]

Abstract: This paper focuses on the prediction of the dimensionless retention time of proteins (DRT) in hydrophobic interaction chromatography (HIC) by means of mathematical models based, essentially, only on aminoacidic composition. The results show that such prediction is indeed possible. Our main contribution was the design of models that predict the DRT using the minimal information concerning a protein: its aminoacidic composition. The performance is similar to that observed in models that use much more sophisticated information such as the three-dimensional structure of proteins. Three models that, in addition to the amino acid composition, use different assumptions about the amino acids tendency to be exposed to the solvent, were evaluated in 12 proteins with known experimental DRT. In all the cases analyzed, the model that obtained the best results was the one based on a linear estimation of the aminoacidic surface composition. The models were adjusted using a collection of 74 vectors of aminoacidic properties plus a set of 6388 vectors derived from these using two mathematical tools: k-means and self-organizing maps (SOM) algorithms. The best vector was generated by the SOM algorithm and was interpreted as a hydrophobicity scale based partly on the tendency of the amino acids to be hidden in proteins. The prediction error (MSEJK) obtained by this model was almost 35% smaller than that obtained by the model that supposes that all the amino acids are completely exposed and 40% smaller than that obtained by the model that uses a simple correction factor considering the general tendency of each amino acid to be exposed to the solvent. In fact, the performance of the best model based on the aminoacidic composition was 5% better than that observed in the model based on the three-dimensional structure of proteins. [Copyright &y& Elsevier]

Abstract: The subcellular location of a protein is closely correlated with it biological function. In this paper, two new pattern classification methods termed as Nearest Feature Line (NFL) and Tunable Nearest Neighbor (TNN) have been introduced to predict the subcellular location of proteins based on their amino acid composition alone. The simulation experiments were performed with the jackknife test on a previously constructed data set, which consists of 2427 eukaryotic and 997 prokaryotic proteins. All protein sequences in the data set fall into four eukaryotic subcellular locations and three prokaryotic subcellular locations. The NFL classifier reached the total prediction accuracies of 82.5% for the eukaryotic proteins and 91.0% for the prokaryotic proteins. The TNN classifier reached the total prediction accuracies of 83.6 and 92.2%, respectively. It is clear that high prediction accuracies have been achieved. Compared with Support Vector Machine (SVM) and Nearest Neighbor methods, these two methods display similar or even higher prediction accuracies. Hence, we conclude that NFL and TNN can be used as complementary methods for prediction of protein subcellular locations. [Copyright &y& Elsevier]

We have shown that covalent conjugation of ubiquitin to proteins is temperature-sensitive in the mouse cell cycle mutant ts85 due to a specifically thermo-labile ubiquitin-activating enzyme (accompanying paper). We show here that degradation of short-lived proteins is also temperature sensitive in ts85, in contrast to wild-type and revertant cells. While more than 70% of the prelabeled abnormal proteins (containing amino acid analogs) or puromycyl peptides are degraded within 4 hr at the permissive temperature in both ts85 and wild-type cells, less than 15% are degraded in ts85 cells at the nonpermissive temperature. Degradation of abnormal proteins and puromycyl peptides in both ts85 cells and wild-type cells is nonlysosomal and ATP-dependent. Immunochemical analysis shows a strong and specific reduction in the levels of in vivo labeled ubiquitin-protein conjugates at the nonpermissive temperature in ts85 cells. Degradation of normal, short- lived proteins is also specifically temperature sensitive in ts85. We suggest that the contribution of ubiquitin-independent pathways to the degradation of short-lived proteins in this higher eucaryotic cell is no more than 10%, and possibly less. [ABSTRACT FROM AUTHOR]

Hydrophobic interaction chromatography (HIC) is widely used in the downstream processing of proteins. Resolution of HIC is very good, but sometimes not as high as expected. Resolution values could be increased if good operating conditions were selected. In this paper we present a methodology for selecting good operating conditions. First, it is necessary to predict the dimensionless retention time (DRT) of each protein in the mixture. We use a correlation such as DRT=A+Bφ+Cφ2, where φ is the superficial hydrophobicity of the protein, which is calculated considering the hydrophobicity of the superficial amino acids using the Miyazawa–Jernigan scale. Considering that there was little interaction amongst proteins in a mixture at the concentrations investigated (2 g/l of each protein), the behaviour of the proteins in the mixture was considered to be similar to that of the individual proteins. Using simulations it was possible to test different operating conditions for the purification of a target protein from a mixture of proteins and it was possible to select ideal conditions. The methodology developed was also tested for the purification of a recombinant protein from a fermentation extract of yeast producing human superoxide dismutase and the results have been satisfactory. [Copyright &y& Elsevier]

Radioiodine labeling of peptides and proteins is routinely performed by using various oxidizing agents such as Chloramine T, Iodobeads, and Iodogen reagent and radioactive iodide (I−), although some other oxidizing agents were also investigated. The main objective of the present study was to develop and test a novel reagent, inorganic monochloramine (NH2Cl), for radioiodine labeling of new chemical entities and biomolecules which is cost-effective, easy to make and handle, and is selective to label amino acids, peptides, and proteins. The data presented in this report demonstrate that the yields of the non-radioactive iodine labeling reactions using monochloramine are >70% for an amino acid (tyrosine) and a cyclic peptide (cyclo Arg-Gly-Asp-d-Tyr-Lys, cRGDyK). No evidence of the formation of N-chloro derivatives in cRGDyK was observed, suggesting that the reagent is selective in iodinating the tyrosine residue in the biomolecules. The method was successfully translated into radioiodine labeling of amino acid, a peptide, and a protein, Bovine Serum Albumin (BSA). [ABSTRACT FROM AUTHOR]

This paper experimentally verifies the idea presented earlier that the contact of nonpolar clusters located on the surface of protein molecules with water destabilizes proteins. It is demonstrated that protein stabilization can be achieved by artificial hydrophilization of the surface area of protein globules by chemical modification. Two experimental systems are studied for the verification of the hydrophilization approach. 1. The surface tyrosine residues of trypsin are transformed to aminotyrosines using a two-step modification procedure: nitration by tetranitromethane followed by reduction with sodium dithionite. The modified enzyme is much more stable against irreversible thermoinactivation: the stabilizing effect increases with the number of aminotyrosine residues in trypsin and the modified enzyme can become even 100 times more stable than the native one. 2. α-Chymotrypsin is covalently modified by treatment with anhydrides or chloroanhydrides of aromatic carboxytic acids. As a result, different numbers of additional carboxylic groups (up to five depending on the structure of the modifying reagent) are introduced into each Lys residue modified. Acylation of all available amino groups of α-chymotrypsin by cyclic anhydrides of pyromellitic and mellitic acids results in a substantial hydrophilization of the protein as estimated by partitioning in an aqueous Ficoll-400/Dextran-70 biphasic system. These modified enzyme preparations are extremely stable against irreversible thermal inactivation at elevated temperatures (65-98 °C); their thermostability is practically equal to the stability of proteolytic enzymes from extremely thermophilic bacteria, the most stable proteinases known to date. [ABSTRACT FROM AUTHOR]

1. Different types of bacteriorhodopsin chromophores and their reactions are described. This includes intermediates of the reconstitution reaction of the purple complex, intermediates of the photochemical cycle and a photochemically active 500-nm chromophore. In contrast to the native chromophore (purple complex) some of these species are reducible by borohydride yielding stable retinyl proteins. 2. Hydrolysis and/or extraction of the retinyl proteins reveals that in the corresponding non reduced parent chromophores the retinal is bound either noncovalently or covalently to lysyl residues of the polypeptide chain. 3. Retinol, retinyl lysine and their retro isomers isolated from the various reduced chromophores are identified by thin-layer chromatography and mass spectrometry. 4. The absorption spectra of the retinyl proteins and binding studies with retinol and retinal indicate that the cyclohexene ring and the side chain of the retinyl moiety are forced into a coplanar conformation by interaction with the protein. The three peaked absorption band of the reduced chromophores is due to this planarized conformation and not to a retro configuration of the retinyl moiety. 5. Isomerization to retro compounds can be achieved by HCl as is known to be the case for retinyl compounds in solution. In addition photochemical isomerization is observed in the case of planarized retinyl moieties. Thus the native protein structure is responsible not only for a specific conformation of the retinyl moiety but also for its specific reactivity. [ABSTRACT FROM AUTHOR]

The primary structure of the most acidic (pI = 4.50) of the two major parvalbumins from frog (Rana esculenta) has been determined from a study of its trypsic peptides and of overlapping peptides generated by limited trypsic digestion, chymotrypsic digestion and N-bromosuccinimide cleavage of the protein. The amino acid sequence so obtained is considered in comparison with those know for other parvalbumins and for rabbit troponin-C. [ABSTRACT FROM AUTHOR]

• Supercritical fluid chromatography and enhanced fluidity liquid chromatography. • Free amino acids, peptides, proteins and nucleic acid bricks. • Mobile phases of CO 2 and co-solvent, comprising water and additives. • Detection issues and hyphenation to mass spectrometry. • Applications in foodomics, metabolomics, clinical and pharmaceutical areas. Biomolecules like proteins, peptides and nucleic acids widely emerge in pharmaceutical applications, either as synthetic active pharmaceutical ingredients, or from natural products as in traditional Chinese medicine. Liquid-phase chromatographic methods (LC) are widely employed for the analysis and/or purification of such molecules. On another hand, to answer the ever-increasing requests from scientists involved in biomolecules projects, other chromatographic methods emerge as useful complements to LC. In particular, there is a growing interest for chromatography with a mobile phase comprising pressurized carbon dioxide, which can be named either (i) supercritical (or subcritical) fluid chromatography (SFC) when CO 2 is the major constituent of the mobile phase, or (ii) enhanced fluidity liquid chromatography (EFLC) when hydro-organic or purely organic solvents are the major constituents of the mobile phase. Despite the low polarity of CO 2 , supposedly inadequate to solubilize such biomolecules, SFC and EFLC were both employed in many occasions for this purpose. This paper specifically reviews the literature related to the SFC/EFLC analysis of free amino acids, peptides, proteins, nucleobases, nucleosides and nucleotides. The analytical conditions employed for specific molecular families are presented, with a focus on the nature of the stationary phase and the mobile phase composition. We also discuss the potential benefits of combining SFC/EFLC to LC in a single gradient elution, a method sometimes designated as unified chromatography (UC). Finally, detection issues are presented, and more particularly hyphenation to mass spectrometry. [ABSTRACT FROM AUTHOR]

Water has many roles in the context of life on Earth, however throughout the universe, other liquids may be able to support the emergence of life. We looked at the ability of amino acids, peptides, a depsipeptide, and proteins to partition into a non-polar decanol phase, with and without the addition of a phase transfer agent. Partitioning evaluated using UV detection, or with HPLC coupled to either charged aerosol detection or ESI-MS. For amino acids and short peptides, phase transfer agents were used to move the biomolecules to the decanol phase, and this transfer was pH dependent. For larger molecules, phase transfer agents did not seem to affect the transfer. Both the depsipetide, valinomycin, and the protein Taq DNA polymerase had solubility in the decanol phase. Additionally, valinomycin appeared to retain its biological ability to bind to potassium ions. These results show that most terrestrial biological molecules are not compatible with non-polar solvents, but it is possible to find and perhaps evolve polymers that are functional in such phases. [ABSTRACT FROM AUTHOR]

The biological function of protein depends mainly on its tertiary structure which is determined by its amino acid sequence via the process of protein folding. Prediction of protein structure from its amino acid sequence is one of the most prominent problems in computational biology. Two basic methodologies on protein structure prediction are combined: ab initio method (3-D space lattice) and fold recognition method (hidden Markov model). The primary structure of proteins and 3-D coordinates of amino acid residues are put together in one hidden Markov model to learn the path of amino acid residues in 3-D space from the first atom to the last atom of each protein of each fold. Therefore, each model has the information of 3-D path of amino acids of each fold. The proposed method is compared to fold recognition methods which have hidden Markov model as a base of their algorithms having approaches on only amino acid sequence or secondary structure. To validate the proposed method, the models are assessed with three datasets. Results show that the proposed models outperform 7-HMM and 3-HMM in the same dataset. The face-centered cubic lattice which is the most compacted 3-D lattice reached the maximum classification accuracy in all experiments in comparison with the performance of the most effective version of optimized 3-HMM as well as the performance of the latest version of SAM 3.5. Results show that 3-D coordinates of atoms of amino acids in proteins have an important role in prediction. It also has great hidden information as compared to secondary structure of proteins in fold classification. [ABSTRACT FROM AUTHOR]

One of the most attractive areas in inorganic chemistry is the synthesis of polyoxometalates (POMs) exhibiting new properties and applications. Since the impact of POMs in biochemistry and related fields of research has increased in the last few years, there has been a special interest in this topic. Significant progress in biological applications has been made where the interaction of POMs with amino acids, peptides and proteins is relevant. Versatile POMs play a series of different roles in the interaction with these biomolecules as described in this review. Various types of interactions are established, depending on the POM shape and charge, the amino acid side chain, peptide sequence or protein structure. Experimental conditions such as temperature, acidity, solvent, etc. are also important factors that influence the binding/reactivity of POM with biomolecules, as described herein. This understanding allows the adequate design of the POM-biomolecule couple for tailoring and controlling mechanisms of action such as catalysis, inhibition, and aggregation, or the crystallising agent. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this study was to composite maize, a cereal grain with low protein and lysine content, with groundnut a rich source of protein, to improve the nutritional quality of maize–groundnut composite flours and their resultant porridges.Design/methodology/approach Defatted and full fat groundnut flours were used to prepare maize–groundnut composite flours and porridges at the ratio of 100:0, 55:45, 70:30 and 85:15, respectively. They were analyzed for proximate composition, energy value, amino acid and fatty acid profiles.Findings Compositing maize with groundnut significantly (p ≤ 0.05) increased proteins from 10 per cent in maize flour to up to 21 per cent in composite porridge (denoted DFC1). The energy values for composite porridges were 434 Kcal/100 g when compared with 398 Kcal/100 g established for maize porridge alone. Lysine content was three times higher in composite flours than for maize flour, while for composite porridges, lysine was four times higher than in maize porridge. There was an increase of 35 per cent in oleic acid content when maize flour was composited with groundnut flour.Research limitations/implications Further research is required to evaluate the properties of full fat and defatted maize–groundnut porridges and their effects on consumer acceptability.Originality/value It can be concluded that compositing maize with full fat and defatted groundnut has the capability of improving the nutritional quality of cereal-based diets consequently contributing to a significant increase in nutritional security of African populations and those of other developing countries of the world. [ABSTRACT FROM AUTHOR]

How cuticular proteins (CPs) interact with chitin and with each other in the cuticle remains unresolved. We employed LC-MS/MS to identify CPs from 5–6 day-old adults of Anopheles gambiae released after serial extraction with PBS, EDTA, 2-8M urea, and SDS as well as those that remained unextracted. Results were compared to published data on time of transcript abundance, localization of proteins within structures and within the cuticle, as well as properties of individual proteins, length, pI, percent histidine, tyrosine, glutamine, and number of AAP[A/V/L] repeats. Thirteen proteins were solubilized completely, all were CPRs, most belonging to the RR-1 group. Eleven CPs were identified in both soluble fractions and the final pellet, including 5 from other CP families. Forty-three were only detected from the final pellet. These included CPRs and members of the CPAP1, CPF, CPFL, CPLCA, CPLCG, CPLCP, and TWDL families, as well as several low complexity CPs, not assigned to families and named CPLX. For a given protein, many histidines or tyrosines or glutamines appear to be potential participants in cross-linking since we could not identify any peptide bearing these residues that was consistently absent. We failed to recover peptides from the amino-terminus of any CP. Whether this implicates that location in sclerotization or some modification that prevents detection is not known. Soluble CPRs had lower isoelectric points than those that remained in the final pellet; most members of other CP families had isoelectric points of 8 or higher. Obviously, techniques beyond analysis of differential solubility will be needed to learn how CPs interact with each other and with chitin. [ABSTRACT FROM AUTHOR]

The article presents information on an ultrafast excited-state deactivation process in peptides, revealed with the help of combined spectroscopic measurements and theoretical calculations, which may affect the ultraviolet (UV)photostability of proteins. It refers to a paper, published in the "Journal of the American Chemical Society" by a team of laser spectroscopists and computational chemists led by Michel Mons and Ivan Ljubic, which discusses the dynamics of a dipeptide that had been subjected to UV excitation.

Exerting control over the size, morphology, and complexity of metal and semiconductor nanoparticles and nanostructures is a requisite for exploring novel phenomena, and the potential applications of these nanomaterials. Bottom-up colloidal chemistry syntheses can benefit from using biomolecules as active elements to influence the formation of inorganic nanoparticles. In this review, we will discuss how three main biomolecule types, (namely DNA; amino acids, peptides, and proteins; and enzymes), can affect the growth of metal and semiconductor nanoparticles. We will present and discuss the templating and non-templating roles of those biomolecules, featuring key aspects and prospects of biomolecule-assisted metal and semiconductor nanoparticle growth. [ABSTRACT FROM AUTHOR]

Although the formation mechanism of biogenically metallic nanoparticles is broadly associated to enzyme mediation, major attention has been given to the role of proteins and peptides in oxido‐reduction of metallic ions leading to these nanostructures. Among the wide range of biomolecules that can act not only as capping agents but also as non‐enzymatic agents to form nanoparticles, disulphide bridge‐containing peptides and amino acids particularly stand out. The literature proposes that they actively participate in the process of nanoparticles' synthesis, with thiols groups and disulphide bridge moieties as the reaction catalytic sites. Similarly, denaturated enzymes containing exposed S–S or S–H moieties are also able to reduce metallic ions to form nanoparticles. This mini‐review is focused on the biogenic synthesis of metallic nanoparticles such as gold, silver, copper, platinum, palladium, lead and selenium, in which proteins, peptides, reductases and even oxido‐reductases act as non‐enzymatic catalysts of the reduction reaction, opening economically and ecologically favourable perspectives in the nanoparticles synthesis field. [ABSTRACT FROM AUTHOR]

Background Codon degeneracy and codon usage by organisms is an interesting and challenging problem. Researchers demonstrated the relation between codon usage and various functions or properties of genes and proteins, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Researchers usually represent segments of proteins responsible for specific functions or structures in a family of proteins as sequence patterns or motifs. We asked the question if organisms use the same codons in pattern segments as compared to the rest of the sequence. Methods We used the likelihood ratio test, Pearson's chi-squared test, and mutual information to compare these two codon usages. Results We showed that codon usage, in segments of genes that code for a given pattern or motif in a group of proteins, varied from the rest of the gene. The codon usage in these segments was not random. Amino acids with larger number of codons used more specific codon ratios in these segments. We studied the number of amino acids in the pattern (pattern length). As patterns got longer, there was a slight decrease in the fraction of patterns with significant different codon usage in the pattern region as compared to codon usage in the gene region. We defined a measure of specificity of protein patterns, and studied its relation to the codon usage. The difference in the codon usage between pattern region and gene region, was less for the patterns with higher specificity. Conclusions We provided a hypothesis that there are segments on genes that affect the codon usage and thus influence protein translation speed, and these regions are the regions that code protein pattern regions. [ABSTRACT FROM AUTHOR]

In this article, we categorize presently available experimental and theoretical knowledge of various physicochemical and biochemical features of amino acids, as collected in the AAindex database of known 544 amino acid (AA) indices. Previously reported 402 indices were categorized into six groups using hierarchical clustering technique and 142 were left unclustered. However, due to the increasing diversity of the database these indices are overlapping, therefore crisp clustering method may not provide optimal results. Moreover, in various large-scale bioinformatics analyses of whole proteomes, the proper selection of amino acid indices representing their biological significance is crucial for efficient and error-prone encoding of the short functional sequence motifs. In most cases, researchers perform exhaustive manual selection of the most informative indices. These two facts motivated us to analyse the widely used AA indices. The main goal of this article is twofold. First, we present a novel method of partitioning the bioinformatics data using consensus fuzzy clustering, where the recently proposed fuzzy clustering techniques are exploited. Second, we prepare three high quality subsets of all available indices. Superiority of the consensus fuzzy clustering method is demonstrated quantitatively, visually and statistically by comparing it with the previously proposed hierarchical clustered results. The processed AAindex1 database, supplementary material and the software are available at . [ABSTRACT FROM AUTHOR]

Olfactory receptors (Ors) convert chemical signals-the binding of odors and pheromones-to electrical signals through the depolarization of olfactory sensory neurons. Vertebrates Ors are G-protein-coupled receptors, stimulated by odors to produce intracellular second messengers that gate ion channels. Insect Ors are a heteromultimeric complex of unknown stoichiometry of two seven transmembrane domain proteins with no sequence similarity to and the opposite membrane topology of G-protein-coupled receptors. The functional insect Or comprises an odor- or pheromone-specific Or subunit and the Orco co-receptor, which is highly conserved in all insect species. The insect Or-Orco complex has been proposed to function as a novel type of ligand-gated nonselective cation channel possibly modulated by G-proteins. However, the Or- Orco proteins lack homology to any known family of ion channel and lack known functional domains. Therefore, the mechanisms by which odors activate the Or-Orco complex and how ions permeate this complex remain unknown. To begin to address the relationship between Or-Orco structure and function, we performed site-directed mutagenesis of all 83 conserved Glu, Asp, or Tyr residues in the silkmoth BmOr-1-Orco pheromone receptor complex and measured functional properties of mutant channels expressed in Xenopus oocytes. 13 of 83 mutations in BmOr-1 and BmOrco altered the reversal potential and rectification index of the BmOr-1-Orco complex. Three of the 13 amino acids (D299 and E356 in BmOr-1 and Y464 in BmOrco) altered both current-voltage relationships and K+ selectivity. We introduced the homologous Orco Y464 residue into Drosophila Orco in vivo, and observed variable effects on spontaneous and evoked action potentials in olfactory neurons that depended on the particular Or-Orco complex examined. Our results provide evidence that a subset of conserved Glu, Asp and Tyr residues in both subunits are essential for channel activity of the heteromeric insect Or-Orco complex. [ABSTRACT FROM AUTHOR]

Background: The tumor microenvironment contains a vast array of pro- and anti-inflammatory cytokines that alter myelopoiesis and lead to the maturation of immunosuppressive cells known as myeloid-derived suppressor cells (MDSCs). Incubating bone marrow (BM) precursors with a combination of granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin-6 (IL-6) generated a tumor-infiltrating MDSC-like population that impaired anti-tumor specific T-cell functions. This in vitro experimental approach was used to simulate MDSC maturation, and the cellular metabolic response was then monitored. A complementary experimental model that inhibited L-arginine (L-Arg) metabolizing enzymes in MSC-1 cells, an immortalized cell line derived from primary MDSCs, was used to study the metabolic events related to immunosuppression. Results: Exposure of BM cells to GM-CSF and IL-6 activated, within 24 h, L-Arg metabolizing enzymes which are responsible for the MDSCs immunosuppressive potential. This was accompanied by an increased uptake of L-glutamine (L-Gln) and glucose, the latter being metabolized by anaerobic glycolysis. The up-regulation of nutrient uptake lead to the accumulation of TCA cycle intermediates and lactate as well as the endogenous synthesis of LArg and the production of energy-rich nucleotides. Moreover, inhibition of L-Arg metabolism in MSC-1 cells down-regulated central carbon metabolism activity, including glycolysis, glutaminolysis and TCA cycle activity, and led to a deterioration of cell bioenergetic status. The simultaneous increase of cell specific concentrations of ATP and a decrease in ATP-to-ADP ratio in BM-derived MDSCs suggested cells were metabolically active during maturation. Moreover, AMP-activated protein kinase (AMPK) was activated during MDSC maturation in GM-CSF and IL-6-treated cultures, as revealed by the continuous increase of AMP-to-ATP ratios and the phosphorylation of AMPK. Likewise, AMPK activity was decreased in MSC-1 cells when L-Arg metabolizing enzymes were inhibited. Finally, inhibition of AMPK activity by the specific inhibitor Compound C (Comp-C) resulted in the inhibition of L-Arg metabolizing enzyme activity and abolished MDSCs immunosuppressive activity. Conclusions: We anticipate that the inhibition of AMPK and the control of metabolic fluxes may be considered as a novel therapeutic target for the recovery of the immunosurveillance process in cancer-bearing hosts. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to lipid recognition propensities of amino acids in membrane proteins. The study showed that the lipophilicity of amino acid residues determines the amino acid preferences for lipid tail groups in both membrane and water-soluble proteins, suggesting that tightly-bound lipid molecules and lipids in the annular shell interact with membrane proteins in a similar manner.

Genes that enable crops to limit Na+ accumulation in shoot tissues represent potential sources of salinity tolerance for breeding. In barley, the HvNax4 locus lowered shoot Na+ content by between 12% and 59% (g−1 DW), or not at all, depending on the growth conditions in hydroponics and a range of soil types, indicating a strong influence of environment on expression. HvNax4 was fine-mapped on the long arm of barley chromosome 1H. Corresponding intervals of ∼200 kb, containing a total of 34 predicted genes, were defined in the sequenced rice and Brachypodium genomes. HvCBL4, a close barley homologue of the SOS3 salinity tolerance gene of Arabidopsis, co-segregated with HvNax4. No difference in HvCBL4 mRNA expression was detected between the mapping parents. However, genomic and cDNA sequences of the HvCBL4 alleles were obtained, revealing a single Ala111Thr amino acid substitution difference in the encoded proteins. The known crystal structure of SOS3 was used as a template to obtain molecular models of the barley proteins, resulting in structures very similar to that of SOS3. The position in SOS3 corresponding to the barley substitution does not participate directly in Ca2+ binding, post-translational modifications or interaction with the SOS2 signalling partner. However, Thr111 but not Ala111 forms a predicted hydrogen bond with a neighbouring α-helix, which has potential implications for the overall structure and function of the barley protein. HvCBL4 therefore represents a candidate for HvNax4 that warrants further investigation. [ABSTRACT FROM PUBLISHER]

Background: The automation of objectively selecting amino acid residue ranges for structure superpositions is important for meaningful and consistent protein structure analyses. So far there is no widely-used standard for choosing these residue ranges for experimentally determined protein structures, where the manual selection of residue ranges or the use of suboptimal criteria remain commonplace. Results: We present an automated and objective method for finding amino acid residue ranges for the superposition and analysis of protein structures, in particular for structure bundles resulting from NMR structure calculations. The method is implemented in an algorithm, CYRANGE, that yields, without protein-specific parameter adjustment, appropriate residue ranges in most commonly occurring situations, including low-precision structure bundles, multi-domain proteins, symmetric multimers, and protein complexes. Residue ranges are chosen to comprise as many residues of a protein domain that increasing their number would lead to a steep rise in the RMSD value. Residue ranges are determined by first clustering residues into domains based on the distance variance matrix, and then refining for each domain the initial choice of residues by excluding residues one by one until the relative decrease of the RMSD value becomes insignificant. A penalty for the opening of gaps favours contiguous residue ranges in order to obtain a result that is as simple as possible, but not simpler. Results are given for a set of 37 proteins and compared with those of commonly used protein structure validation packages. We also provide residue ranges for 6351 NMR structures in the Protein Data Bank. Conclusions: The CYRANGE method is capable of automatically determining residue ranges for the superposition of protein structure bundles for a large variety of protein structures. The method correctly identifies ordered regions. Global structure superpositions based on the CYRANGE residue ranges allow a clear presentation of the structure, and unnecessary small gaps within the selected ranges are absent. In the majority of cases, the residue ranges from CYRANGE contain fewer gaps and cover considerably larger parts of the sequence than those from other methods without significantly increasing the RMSD values. CYRANGE thus provides an objective and automatic method for standardizing the choice of residue ranges for the superposition of protein structures. [ABSTRACT FROM AUTHOR]

The article presents information on E. coli.'s protein expression and solubility affected by amino acids. There is a strong correlation between the two parameters of protein expression and solubility. Logistic regression analysis was used to determine if they are influenced by amino acids or bulk sequence parameters like sidechain entropy and hydrophobicity. Irrespective of codon usage, translation efficiency in E.coli. may be reduced by positively charged amino acids.

The article presents information on a study on over 9,500 human proteins and developed and optimized a system for proteome-wide identification of novel methylation events that was catalyzed by the protein lysine methyltransferase (PKMT) SETD6. The study identified novel candidate substrates for SETD6 by using two independent detection approaches The study also verified that all targets tested in vitro as well as in cells were genuine substrates. The study described a novel proteome-wide methodology for identifying the new PKMT substrates.

The article reports on a study on the molecular evolution of A-, B-, D-, E-type cyclin proteins in animals and fungi. It states amino acid replacements patterns were analyzed by construction of phylogenetic trees for these proteins, their ancestral sequences. It states the analysis revealed that accelerated evolution proceeded predominantly during paralog duplication or after it in animals and fungi.