Protein Interaction Between p53 and △113p53 Is Required for the Anti-Apoptotic Function of △113p53

Zebrafish △113p53, an N-terminal truncated p53 isoform, is a p53-target gene that antagonises p53-mediated apoptotic activity.Interestingly, △113p53 does not act on p53 in a dominant-negative manner, but rather interferes with the p53 function by differentially modulating p53-target gene expression to protect cells from apoptosis. Previous studies showed that over-expressed △113p53 and p53proteins formed a complex. However, it is not known whether endogenous p53 and △113p53 proteins also interact with each other, and if this interaction is required for △113p53 to inhibit the apoptotic activity of full-length p53. In this study, we used two available zebrafish p53 antibodies to address these questions. One, Zfp53-N, only recognises full-length p53, whereas the other, Zfp53-A7C10, detects both full-length p53 and △113p53. Using Zfp53-N for immunoprecipitation and Zfp53-A7C10 for detection, we demonstrated that endogenous △113p53 and full-length p53 induced by a DNA-damaging drug formed a complex in vivo. Furthermore, of the six △113p53 mutants we generated with different point mutations in the oligomerisation domain, two failed to interact with p53 and lost the ability to modulate p53-target gene expression and inhibit p53-induced cell apoptosis. However, those △113p53 mutants that could interact with p53 retained the ability to antagonise the apoptotic activity of p53. Therefore, our data demonstrated that proteineprotein interaction between △113p53and p53 is essential for the anti-apoptotic function of △113p53. In addition, the two △113p53 mutants that failed to interact with p53 are also useful for the study of the mechanisms of other functions of △113p53.     

Protein Interaction Between p53 and △113p53 Is Required for the Anti-Apoptotic Function of △113p53

Zebrafish △113p53, an N-terminal truncated p53 isoform, is a p53-target gene that antagonises p53-mediated apoptotic activity. Interestingly, △113p53 does not act on p53 in a dominant-negative manner, but rather interferes with the p53 function by differentially modulating p53-target gene expression to protect cells from apoptosis. Previous studies showed that over-expressed △113p53 and p53 proteins formed a complex. However, it is not known whether endogenous p53 and △113p53 proteins also interact with each other, and if this interaction is required for △113p53 to inhibit the apoptotic activity of full-length p53. In this study, we used two available zebrafish p53 antibodies to address these questions. One, Zfp53-N, only recognises full-length p53, whereas the other, Zfp53-A7C10, detects both full-length p53 and △113p53. Using Zfp53-N for immunoprecipitation and Zfp53-A7C 10 for detection, we demonstrated that endogenous △113p53 and full-length p53 induced by a DNA-damaging drug formed a complex in vivo. Furthermore, of the six △113p53 mutants we generated with different point mutations in the oligomerisation domain, two failed to interact with p53 and lost the ability to modulate p53-target gene expression and inhibit p53-induced cell apoptosis. However, those △113p53 mutants that could interact with p53 retained the ability to antagonise the apoptotic activity of p53. Therefore, our data demonstrated that protein--protein interaction between △113p53 and p53 is essential for the anti-apoptotic function of △113p53. In addition, the two △113p53 mutants that failed to interact with p53 are also useful for the study of the mechanisms of other functions of △113p53.     

Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.     

The Structural Dynamics of the Flavivirus Fusion Peptide–Membrane Interaction

Membrane fusion is a crucial step in flavivirus infections and a potential target for antiviral strategies. Lipids and proteins play cooperative roles in the fusion process, which is triggered by the acidic pH inside the endosome. This acidic environment induces many changes in glycoprotein conformation and allows the action of a highly conserved hydrophobic sequence, the fusion peptide (FP). Despite the large volume of information available on the virus-triggered fusion process, little is known regarding the mechanisms behind flavivirus–cell membrane fusion. Here, we evaluated the contribution of a natural single amino acid difference on two flavivirus FPs, FLA_G (⁹⁸DRGWGNGCGLFGK¹¹⁰) and FLA_H (⁹⁸DRGWGNHCGLFGK¹¹⁰), and investigated the role of the charge of the target membrane on the fusion process. We used an in silico approach to simulate the interaction of the FPs with a lipid bilayer in a complementary way and used spectroscopic approaches to collect conformation information. We found that both peptides interact with neutral and anionic micelles, and molecular dynamics (MD) simulations showed the interaction of the FPs with the lipid bilayer. The participation of the indole ring of Trp appeared to be important for the anchoring of both peptides in the membrane model, as indicated by MD simulations and spectroscopic analyses. Mild differences between FLA_G and FLA_H were observed according to the pH and the charge of the target membrane model. The MD simulations of the membrane showed that both peptides adopted a bend structure, and an interaction between the aromatic residues was strongly suggested, which was also observed by circular dichroism in the presence of micelles. As the FPs of viral fusion proteins play a key role in the mechanism of viral fusion, understanding the interactions between peptides and membranes is crucial for medical science and biology and may contribute to the design of new antiviral drugs.     

A Second-generation Protein–Protein Interaction Network of Helicobacter pylori

Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein–protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.Helicobacter pylori is a Gram-negative, microaerophilic bacterium that colonizes the stomach, an unusual highly acidic niche for microorganisms. In 1983, Warren and Marshall found it to be associated with gastric inflammation and duodenal ulcer disease (1, 2). A chronic infection with H. pylori can lead to development of stomach carcinoma and MALT lymphoma (reviewed in (3)). Hence, the World Health Organization has classified H. pylori as a class I carcinogen (4). It is estimated that half of the world′s population harbors H. pylori but with large variations in the geographical and socioeconomic distribution while causing annually 700,000 deaths worldwide (reviewed in (5)).The pathogenesis of H. pylori has been extensively studied, including the effector CagA, cytotoxin VacA, its adhesins and urease (reviewed in (3, 5–7)). The latter allows the bacterium to neutralize the stomach acid through ammonia production. However, H. pylori is not a classical model organism and thus many gaps in our knowledge still exist.The genome of H. pylori reference strain 26695 was completely sequenced in 1997 (8) and encodes 1587 proteins of which about 950 (61%) have been assigned functions (excluding “putatives”; Uniprot, CMR (9)). These numbers indicate that a large fraction of the proteins of H. pylori has not been functionally characterized.Protein–protein interactions (PPIs)¹ are required for nearly all biological processes. Unbiased interactomes are helpful to understand proteins or pathways and how they are linking poorly or uncharacterized proteins via their interactions. For instance, our study of the Treponema pallidum interactome (10) has led to the characterization of several previously “unknown” proteins such as YbeB, a ribosomal silencing factor (11), or TP0658, a regulator of flagellar translation and assembly (12, 13). However, only a few other comprehensive bacterial interactome studies have been published to date, including Campylobacter jejuni (14), Synechocystis sp. (15), Mycobacterium tuberculosis (16), Mesorhizobium loti (17), and recently Escherichia coli (18). In addition, partial interactomes are available for Bacillus subtilis (19) and H. pylori (20). Most of them used the yeast two-hybrid (Y2H) screening technology (21) which allows the pairwise detection of PPIs. Furthermore, a few other studies (22–25) systematically identified protein complexes and their compositions in bacteria.In 2001, Rain and colleagues have established a partial interactome of H. pylori, the first published protein interaction network of a bacterium (20). In this study, 261 bait constructs were screened against a random prey pool library resulting in the detection of over 1500 PPIs. Although this network likely represents a small fraction of all PPIs that occur in H. pylori, many downstream studies were motivated by these results (see below).Recent studies have disproved the notion that Y2H data sets are of poor quality (26, 27). Similarly, a high false-negative rate can be avoided by multiple Y2H expression vector systems (28–30) or protein fragments as opposed to full-length constructs (31). The aim of this study was to systematically screen the H. pylori proteome for binary protein interactions using a complementary approach to that of Rain et al. to produce an extended protein–protein interaction map of H. pylori. As a result, we have roughly doubled the number of known binary protein–protein interactions for H. pylori in this study.     

Physicochemical Properties and Biological Activity of the Peptide–Protein Complex from Bovine Scleral Tissue

The peptide–protein complex from bovine sclera was studied. It is shown that it contained a protein with a molecular weight of 66387 Da with the partial N-terminal amino acid sequence DTHKSEIAHRFKDLG-, which is homologous to the mature molecule of bovine serum albumin, and polypeptides with molecular weights of 1300–5080 Da. With a model of the organotypic cultivation of posterior eye tissues of the newt Pleurodeles waltl in vitro, it was shown that the effect of this peptide–protein complex in low doses increased the viability of scleral fibroblasts.     

Characterization and Evaluation of Key Sites in the Peptide Inhibitor of TAB1/p38α Interaction

A combination of computation techniques and peptide mutants have been used to determine the binding site and amino acid residues on the inhibitor peptide that are critical for binding to Mitogen-activated protein kinase 14 (p38α). In our previous research work, the functional peptide, named as PT5, target to p38α, was obtained based on the theoretical complex structure of p38α and [transforming growth factor-β (TGF-β)-activated protein kinase 1 (TAK1)-binding protein 1] (TAB1). Based on the computer-guided ab initio modeling method, the inhibitor peptide PT5 and its mutants were modeled. Furthermore, the 3-D complex structures of PT5 or its mutants and p38α were constructed using molecular docking and dynamics simulation methods. The key residues in the peptide PT5 involved in binding interaction to p38α were predicted. According to the 3-D theoretical complex structure PT5/ p38α, the interaction binding mode between PT5 and p38α was analyzed using distance geometry technology. Mutants of the peptide PT5 was used to evaluate the bio-function when the critical residues were mutated. The mutant experimental results identified the key residues in PT5, i.e. Thr¹¹ and Asp¹² and determined the core sequence of PT5 binding to p38α. Based on the results, optimized peptides compounds could be developed for treating myocardial ischemia/reperfusion (I/R) injury in clinical.     

LRP-1 Mediated Endocytosis of EFE Across the Blood–Brain Barrier; Protein–Protein Interaction and Molecular Dynamics Analysis

International Journal of Peptide Research and Therapeutics - Additional biological protection; blood brain barrier (BBB) to neuronal tissue is essential against invading infections and unwanted...     

Protein–Protein and Protein–Membrane Associations in the Lignin Pathway

Supramolecular organization of enzymes is proposed to orchestrate metabolic complexity and help channel intermediates in different pathways. Phenylpropanoid metabolism has to direct up to 30% of the carbon fixed by plants to the biosynthesis of lignin precursors. Effective coupling of the enzymes in the pathway thus seems to be required. Subcellular localization, mobility, protein–protein, and protein–membrane interactions of four consecutive enzymes around the main branch point leading to lignin precursors was investigated in leaf tissues of Nicotiana benthamiana and cells of Arabidopsis thaliana. CYP73A5 and CYP98A3, the two Arabidopsis cytochrome P450s (P450s) catalyzing para- and meta-hydroxylations of the phenolic ring of monolignols were found to colocalize in the endoplasmic reticulum (ER) and to form homo- and heteromers. They moved along with the fast remodeling plant ER, but their lateral diffusion on the ER surface was restricted, likely due to association with other ER proteins. The connecting soluble enzyme hydroxycinnamoyltransferase (HCT), was found partially associated with the ER. Both HCT and the 4-coumaroyl-CoA ligase relocalized closer to the membrane upon P450 expression. Fluorescence lifetime imaging microscopy supports P450 colocalization and interaction with the soluble proteins, enhanced by the expression of the partner proteins. Protein relocalization was further enhanced in tissues undergoing wound repair. CYP98A3 was the most effective in driving protein association.     

Prediction of Protein–Protein Interaction Sites in Sequences and 3D Structures by Random Forests

Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i) a combination of sequence- and structure-derived parameters and (ii) sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras–Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.     

Investigation of the inhibitory mechanism of apomorphine against MDM2–p53 interaction

Mirror-image screening using d-proteins is a powerful approach to provide mirror-image structures of chiral natural products for drug screening. During the course of our screening study for novel MDM2–p53 interaction inhibitors, we identified that NPD6878 (R-(?)-apomorphine) inhibited both the native l-MDM2–l-p53 interaction and the mirror-image d-MDM2–d-p53 interaction at equipotent doses. In addition, both enantiomers of apomorphine showed potent inhibitory activity against the native MDM2–p53 interaction. In this study, we investigated the inhibitory mechanism of both enantiomers of apomorphine against the MDM2–p53 interaction. Achiral oxoapomorphine, which was converted from chiral apomorphines under aerobic conditions, served as the reactive species to form a covalent bond at Cys77 of MDM2, leading to the inhibitory effect against the binding to p53.     

Design and synthesis of new substituted spirooxindoles as potential inhibitors of the MDM2–p53 interaction

The designed compounds, 4a–p, were synthesized using a simple and smooth method with an asymmetric 1,3-dipolar reaction as the key step. The chemical structures for all synthesized compounds were elucidated and confirmed by spectral analysis. The molecular complexity and the absolute stereochemistry of 4b and 4e designed analogs were determined by X-ray crystallographic analysis. The anticancer activities of the synthesized compounds were tested against colon (HCT-116), prostate (PC-3), and hepatocellular (HepG-2) cancer cell lines. Molecular modeling revealed that the compound 4d binds through hydrophobic–hydrophobic interactions with the essential amino acids (LEU: 57, GLY: 58, ILE: 61, and HIS: 96) in the p53-binding cleft, as a standard p53-MDM2 inhibitor (6SJ). The mechanism underlying the anticancer activity of compound 4d was further evaluated, and the study showed that compound 4d inhibited colony formation, cell migration, arrested cancer cell growth at G2/M, and induced apoptosis through intrinsic and extrinsic pathways. Transactivation of p53 was confirmed by flow cytometry, where compound 4d increased the level of activated p53 and induced mRNA levels of cell cycle inhibitor, p21.     

Cystatin B and SOD1: Protein–Protein Interaction and Possible Relation to Neurodegeneration

Cystatin B (CSTB), an inhibitor of the cysteine proteases, belongs to the cathepsin family and it is known to interact with a number of proteins involved in cytoskeletal organization. CSTB has an intrinsic tendency to form aggregates depending on the redox environment. The gene encoding for CSTB is frequently mutated in association with the rare neurodegenerative condition progressive myoclonus epilepsy. Increased levels of CSTB have been observed in the spinal cord of transgenic mice modeling SOD1-linked familial amyotrophic lateral sclerosis, a fatal neurodegenerative disease affecting motoneurons. In the present study, we have investigated the relationship occurring between the expression of SOD1 and CSTB either wild-type or double-cysteine substitution mutant (Cys 3 and Cys 64). Whether or not there is a physical interaction between the two proteins was also investigated in overexpression experiments using a human neuroblastoma cell line and mouse-immortalized motoneurons. Here we report evidences for a reciprocal influence of CSTB and SOD1 at the gene expression level and for a direct interaction of the two proteins.