Frontiers in Protein and Peptide Sciences

Hemoglobins (Hbs) from the South American snake Liophis miliaris undergo a reversible oxygen-linked dissociation phenomenon α₂β₂ + 4O₂ ↔ 2αβ(O₂), due to substituted glutamate residues (43β and 101β) at the α₁β₂- interface, according to Matsuura et al., 1989. This work reports the oxygen-binding properties and analysis of tetrameric stability from the major hemoglobins of two snakes: a terrestrial species (Crotalus durissus terrificus), and a semiaquatic one, L. miliaris. The major hemoglobins from both species were analyzed by classic functional experimental approaches and other analytical techniques: dimer-tetramer association constant by analytical gel filtration chromatography and small angle x-ray scattering (SAXS). In addition, we performed molecular modeling of the hemoglobin from L. miliaris. The functional results display cooperative oxygen binding, alkaline Bohr Effect, and conformational transitions, a behavior which is compatible with tetrameric Hbs. Also, the estimated dimer-tetramer association constant ⁴K₂, radius of gyration, and maximum dimension exhibit similar compatibility. A molecular modeling of the structure of L. miliaris Hb, on the other hand, allows us to conclude that the residues Glu43β(CD2) and Glu101β(G3) are not essential in the maintenance of the tetrameric form, supporting our findings and allowing us to rule out the hypothesis proposed in the literature for the Hb of Liophis miliaris and other species of snakes. Therefore, the results reported in the paper suggest that the major Hbs of Liophis miliaris and Crotalus durissus terrificus are stable tetramers in vivo and in vitro.

In recent years, there have been an increasing number of investigations of the pathways involved in the metabolism of endocannabinoids (eCBs) following the discovery of cannabinoid receptors (CB) and their endogenous ligands, such as anandamide (AEA) and 2-arachidonoylglycerol (2-AG). The in vivo biosynthesis of AEA has been shown to occur through several pathways mediated by N-acylphosphatidylethanolamidephospholipase D (NAPE-PLD), a secretory PLA2; α-β-hydrolase 4 (ABH4); glycerophosphodiesterase (GDE1); PLC; and lyso-PLD. 2-AG, a second eCB, is generated through the action of selective enzymes, such as phosphatidic acid phsophohydrolase, diacylglycerol lipase (DAGL), phosphoinositide-specific PLC (PI-PLC), and lyso-PLC. In the adult brain these enzymes are localized in the postsynaptic plasma membrane, consistent with their role in generating 2-AG for use in retrograde transmission. A putative membrane transporter is involved in the cellular uptake and release of eCBs. AEA is metabolized by fatty acid amidohydrolase (FAAH), while 2-AG is metabolized by FAAH, monoacylglycerol lipase (MAGL), and serine hydrolase α-β-hydrolase domain 6 and 12 (ABHD6 and 12). The author presents an integrative overview of current research on the enzymes involved in the metabolism of eCBs and discusses possible therapeutic interventions for various diseases, including addiction.

CYP2C19 is an important member of the cytochrome P-450 enzyme superfamily and plays a significant role in the drug metabolism. In order to gain insights for developing personalized drugs, the structure-activity relationships of two SNPs, W120R and I331V, with the ligands of CEC, Fluvoxamine, Lescol and Ticlopidine were investigated through the structure-activity relationship approach. By means of a series of docking studies, the binding pockets of the two SNPs for the four compounds are explicitly defined that will be very useful for conducting mutagenesis studies, providing insights into personalization of drug treatments and stimulating novel strategies for finding desired personalized drugs.

Heat shock Proteins (HSPs) play essential role in cellular homeostasis and therefore, maintain key proteins at their native state against cellular stress to promote cell survival. ATP independent HSP27 makes a defense against stress factors to facilitate ATP dependent Hsp machinery to perform its function under stress conditions. The machinery involves HSP70, HSP40, HSP60, HSP90, and HSP100 proteins. The expression of inducible HSP27 is at basal levels in normal cells; however, HSP27 is abnormally expressed in breast cancer, ovarian cancer, osteo-sarcoma, endometrial cancer, and leukemia cells. Elevated HSP27 in oncogenic cells resists anti-cancer therapy since it protects the cell against spontaneous apoptosis. Furthermore, HSP27 inhibits apoptotic signals at regulatory points which may explain the role of HSP27 in tumor progression and resistance to therapy. Phosphorylation and oligomerization of HSP27 regulate its biochemical function. Recent literature reports on HSP27 structure, function, and its role in oncogenesis and apoptosis are discussed in this review.

The first part of this paper contains an overview of protein structures, their spontaneous formation ("folding"), and the thermodynamic and kinetic aspects of this phenomenon, as revealed by in vitro and in vivo experiments. It is stressed that universal features of the in vitro folding are observed near the point of thermodynamic equilibrium between the native and denatured states of the protein. Here the "two-state" ("denatured state" ↔ "native state") transition proceeds without accumulation of metastable intermediates; this facilitates investigation of the "transition state". This state, which is the most unstable in the folding pathway, and its structured core (a "nucleus") are distinguished by their essential influence on the folding/unfolding kinetics. In the second part of the paper, a theory of protein folding rates and related phenomena is presented. First, it is shown that the protein size determines the range of a protein’s folding rates in the vicinity of the point of thermodynamic equilibrium between the native and denatured states of the protein. Then, we present methods for calculating folding and unfolding rates of globular proteins from their sizes, stabilities and either 3D structures or amino acid sequences. Finally, we show that the same theory outlines the location of the protein folding nucleus (i.e., the structured part of the transition state) in reasonable agreement with experimental data.

Heat shock proteins (Hsps) are highly conserved proteins and have cytoprotective role for maintaining cellular protein conformation. Hsps not only keep proteins in their native state but also involve in several essential biochemical process. This review summarizes structural properties of Hsps (Hsp70, Hsp40, Hsp90, Hsp100, Hsp60, sHsps, and Nucleotide Exchange Factors) and explains their roles in aging, apoptosis, cancer, neurodegeneration, cardio-vascular diseases, obesity and diabetes mellitus, and housekeeping.

Protein secondary structure carries information about local structural arrangements. Significant majority of successful methods for predicting the secondary structure is based on multiple sequence alignment. However, the multiple alignment fails to achieve accurate results when a protein sequence is characterized by low homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation. The method is featured by employing a support vector machine (SVM) regressing system and adopting a different pseudo amino acid composition (PseAAC), which can partially take into account the sequence-order effects to represent protein samples. It was shown by both the self-consistency test and the independent-dataset test that the trained SVM has remarkable power in grasping the relationship between the PseAAC and the content of protein secondary structural elements, including α-helix, 3₁₀-helix, π-helix, β-strand, β- bridge, turn, bend and the rest random coil. Results prior to or competitive with the popular methods have been obtained, which indicate that the present method may at least serve as an alternative to the existing predictors in this area.

The Golgi apparatus plays a key role in sorting, modifying, packaging and distributing proteins. Thus, correct identification of the type of a Golgi-resident protein will provide in-depth insights into its function involved in various biological processes. In this article, we will briefly outline the prediction of protein subGolgi localizations using bioinformatics method. We introduced the available databases for training predicted models. Moreover, three kinds of methods were presented for discriminating between cis-Golgi and trans-Golgi proteins.

The membrane protein type is an important feature in characterizing the overall topological folding type of a protein or its domains therein. Many investigators have put their efforts to the prediction of membrane protein type. Here, we propose a new approach, the bootstrap aggregating method or bragging learner, to address this problem based on the protein amino acid composition. As a demonstration, the benchmark dataset constructed by K.C. Chou and D.W. Elrod (Proteins, 1999, 34, 137-153) was used to test the new method. The overall success rate thus obtained by jackknife cross-validation was over 84%, indicating that the bragging learner as presented in this paper holds a quite high potential in predicting the attributes of proteins, or at least can play a complementary role to many existing algorithms in this area. It is anticipated that the prediction quality can be further enhanced if the pseudo amino acid composition (K.C. Chou, Proteins, 2001, 43, 246-255) can be effectively incorporated into the current predictor. An online membrane protein type prediction web server developed in our lab is available at http://chemdata.shu.edu.cn/protein/protein.jsp.

In this paper, we propose a strategy to predict subcellular locations of human proteins using multi-step feature selection. Each protein is firstly coded by features derived from KEGG and GO enrichment scores. After an initial feature reduction, 9958 features remain and they are sorted by the Minimum Redundancy Maximum Relevance (mRMR) method. The sorted features are then filtered by an incremental feature selection (IFS) procedure and a compact set of features are obtained. Random forest (RF) is used as the prediction model and achieved an overall prediction accuracy of 67.72%, evaluated by ten-fold cross-validation. The corresponding KEGG pathways and GO terms of the resultant features are analyzed in-depth, and are deemed as the most important terms relating to human protein subcellular location.

Plasmodium falciparum, an obligate intracellular parasite and causative agent of malaria, exhibits an atypical metabolic organization of proteins which are diverged extensively from their homologues in other organisms. This divergence makes homology-based on structural and functional annotation of the proteins difficult. With an emphasis on determinant aspects such as domain duplication, divergence and domain splitting, we provide a comprehensive basis to understand the significance of sequence divergence observed in metabolic proteins of P. falciparum. Such a pronounced sequence divergence in proteins renders the homology-based annotation transfer nontrivial. Additionally the unavailability of function annotation for about 40% of the parasitic proteome poses a limitation to understand the physiological basis of metabolic flexibility exhibited by the parasite to facilitate its multi-host survival. Thus, detection and exploration of remotely related homologues with the help of highly sensitive sequence search techniques become indispensable. Employment of a combination of highly sensitive profile-based approaches has enabled enhanced structural and functional characterization of metabolic proteins along with identification of proteins potentially involved in metabolic pathways. An enriched function annotation of the parasitic protein repertoire not only facilitates recognition of putative pathway proteins but also paves way for prioritizing targets for chemotherapeutic interventions.