The enhancement of stability of p53 in MTBP induced p53–MDM2 regulatory network

We have modeled an MTBP-MDM2–p53 regulatory network by integrating p53–MDM2 autoregulatory model (Proctor and Gray, 2008) with the effect of a cellular protein MTBP (MDM2 binding protein) which is allowed to bind with MDM2 (Brady et al., 2005). We study this model to investigate the activation of p53 and MDM2 steady state levels induced by MTBP protein under different stress conditions. Our simulation results in three approaches namely deterministic, Chemical Langevin equation and stochastic simulation of Master equation show a clear transition from damped limit cycle oscillation to fixed point oscillation during a certain time period with constant stress condition in the cell. This transition is the signature of transition of p53 and MDM2 levels from activated state to stabilized steady state levels. We present various phase diagrams to show the transition between unstable and stable states of p53 and MDM2 concentration levels and also their possible relations among critical value of the parameters at which the respective protein level reach stable steady states. In the stochastic approach, the dynamics of the proteins become noise induced process depending on the system size. We found that this noise enhances the stability of the p53 steady state level.     

Changes in protein expression in p53 deleted spontaneous thymic lymphomas

By the use of high-resolution two-dimensional gel electrophoresis and computerized image analysis we investigated and compared the expression of cellular proteins from p53 positive (+/+) mouse thymocytes, p53-/- thymocytes before neoplastic transformation, and from cell lines derived from two spontaneous p53-/- thymic lymphomas, SM5 and SM7. A total of around 1500 proteins were detected on individual gels. Only changes in protein expression by a factor of 2 or more were considered. In the thymic lymphoma cells 3-5% of the proteins were found to be differentially regulated when compared with the protein expression in p53+/+ and p53-/- thymocytes. Only a minority (13 proteins) of the quantitatively changed proteins were common for the two thymic lymphoma cell lines, suggesting that the p53 deficiency mainly results in genetic dysfunctions which are individual for a given tumor. Two of the detected proteins increased their expression levels by more than 10 times from the p53+/+ to the p53-/- thymocytes and these high expression levels were also found in thymic lymphomas. The two proteins were identified by mass spectrometry as acidic ribosomal phosphoprotein P0 and a 33-kDa protein with a primary structure containing motifs of the glyoxalase-bleomycin resistance protein family (MDR) as deduced from the cDNA.     

Enrichment of integral membrane proteins for proteomic analysis using liquid chromatography-tandem mass spectrometry

An increasing number of proteomic strategies rely on liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect and identify constituent peptides of enzymatically digested proteins obtained from various organisms and cell types. However, sample preparation methods for isolating membrane proteins typically involve the use of detergents and chaotropes that often interfere with chromatographic separation and/or electrospray ionization. To address this problem, a sample preparation method combining carbonate extraction, surfactant-free organic solvent-assisted solubilization, and proteolysis was developed and demonstrated to target the membrane subproteome of Deinococcus radiodurans. Out of 503 proteins identified, 135 were recognized as hydrophobic on the basis of their calculated hydropathy values (GRAVY index), corresponding to coverage of 15% of the predicted hydrophobic proteome. Using the PSORT algorithm, 53 of the proteins identified were classified as integral outer membrane proteins and 215 were classified as integral cytoplasmic membrane proteins. All identified integral cytoplasmic membrane proteins had from 1 to 16 mapped transmembrane domains (TMDs), and 65% of those containing four or more mapped TMDs were identified by at least one hydrophobic membrane spanning peptide. The extensive coverage of the membrane subproteome (24%) by identification of highly hydrophobic proteins containing multiple TMDs validates the efficacy of the described sample preparation technique to isolate and solubilize hydrophobic integral membrane proteins from complex protein mixtures.     

The dipole moment of the electron carrier adrenodoxin is not critical for redox partner interaction and electron transfer

Dipole moments of proteins arise from helical dipoles, hydrogen bond networks and charged groups at the protein surface. High protein dipole moments were suggested to contribute to the electrostatic steering between redox partners in electron transport chains of respiration, photosynthesis and steroid biosynthesis, although so far experimental evidence for this hypothesis was missing. In order to probe this assumption, we changed the dipole moment of the electron transfer protein adrenodoxin and investigated the influence of this on protein-protein interactions and electron transfer. In bovine adrenodoxin, the [2Fe-2S] ferredoxin of the adrenal glands, a dipole moment of 803 Debye was calculated for a full-length adrenodoxin model based on the Adx(4-108) and the wild type adrenodoxin crystal structures. Large distances and asymmetric distribution of the charged residues in the molecule mainly determine the observed high value. In order to analyse the influence of the resulting inhomogeneous electric field on the biological function of this electron carrier the molecular dipole moment was systematically changed. Five recombinant adrenodoxin mutants with successively reduced dipole moment (from 600 to 200 Debye) were analysed for their redox properties, their binding affinities to the redox partner proteins and for their function during electron transfer-dependent steroid hydroxylation. None of the mutants, not even the quadruple mutant K6E/K22Q/K24Q/K98E with a dipole moment reduced by about 70% showed significant changes in the protein function as compared with the unmodified adrenodoxin demonstrating that neither the formation of the transient complex nor the biological activity of the electron transfer chain of the endocrine glands was affected. This is the first experimental evidence that the high dipole moment observed in electron transfer proteins is not involved in electrostatic steering among the proteins in the redox chain.     

Ionic liquids as refolding additives: N'-alkyl and N'-(omega-hydroxyalkyl) N-methylimidazolium chlorides

The purpose of this work was to investigate the influence of a series of N'-alkyl and N'-(omega-hydroxy-alkyl)-N-methylimidazolium chlorides on the renaturation of two model proteins, namely hen egg white lysozyme and the single-chain antibody fragment ScFvOx. All tested ionic liquids acted as refolding enhancers, with varying efficacies and efficiencies. The results of the refolding screening could be interpreted by taking into account the effect of the studied ionic liquids on protein aggregation, together with the systematic variations of their influence on the stability of native proteins in solution. More hydrophobic imidazolium cations carrying longer alkyl chains were increasingly destabilizing, while terminal hydroxylation of the alkyl chain made the salts more compatible with protein stability. The studied ionic liquids can be classified as preferentially bound, slightly to moderately chaotropic cosolvents for proteins.     

Increasing the hydrophobic interaction between terminal W-motifs enhances the stability of Salmonella typhimurium sialidase. A general strategy for the stabilization of beta-propeller protein fold.

Protein engineering of the beta-propeller protein aimed at enhancing the structural stability of the protein was carried out using a monomeric single domain beta-propeller protein, Salmonella typhimurium sialidase, as a model. Ala53 and Ala69 each located at strands B and C of the W1 motif were mutated to Leu and Val, respectively, to increase the hydrophobic interaction between W1 and W6 motifs. The mutants showed enhanced stability towards guanidine hydrochloride and thermal unfolding. Ala53Leu showed higher stability, probably owing to the capability of the mutated Leu to interact extensively with more residues involved in the hydrophobic interactions between the terminal W-motifs. The mutations, which are located far from the active site, have no significant effect on the enzymatic properties. The strategy to enhance the stability proposed here might be applied to the other beta-propeller proteins.     

Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices

The importance of the promoter sequences in the function regulation of several important mycobacterial pathogens creates the necessity to design simple and fast theoretical models that can predict them. This work proposes two DNA promoter QSAR models based on pseudo-folding lattice network (LN) and star-graphs (SG) topological indices. In addition, a comparative study with the previous RNA electrostatic parameters of thermodynamically-driven secondary structure folding representations has been carried out. The best model of this work was obtained with only two LN stochastic electrostatic potentials and it is characterized by accuracy, selectivity and specificity of 90.87%, 82.96% and 92.95%, respectively. In addition, we pointed out the SG result dependence on the DNA sequence codification and we proposed a QSAR model based on codons and only three SG spectral moments.     

Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species

There are many of pathogen parasite species with different susceptibility profile to antiparasitic drugs. Unfortunately, almost QSAR models predict the biological activity of drugs against only one parasite species. Consequently, predicting the probability with which a drug is active against different species with a single unify model is a goal of the major importance. In so doing, we use Markov Chains theory to calculate new multi-target spectral moments to fit a QSAR model that predict by the first time a mt-QSAR model for 500 drugs tested in the literature against 16 parasite species and other 207 drugs no tested in the literature using spectral moments. The data was processed by linear discriminant analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 311 out of 358 active compounds (86.9%) and 2328 out of 2577 non-active compounds (90.3%) in training series. Overall training performance was 89.9%. Validation of the model was carried out by means of external predicting series. In these series the model classified correctly 157 out 190, 82.6% of antiparasitic compounds and 1151 out of 1277 non-active compounds (90.1%). Overall predictability performance was 89.2%. In addition we developed four types of non Linear Artificial neural networks (ANN) and we compared with the mt-QSAR model. The improved ANN model had an overall training performance was 87%. The present work report the first attempts to calculate within a unify framework probabilities of antiparasitic action of drugs against different parasite species based on spectral moment analysis.     

Mdt1/ASCIZ: A new DNA damage response protein family

DNA damage response pathways are crucial for genome stability and prevention of cancer, and are overall remarkably conserved from yeast to mammals. Two novel DNA damage response proteins, yeast Mdt1 (Modifier of DNA damage tolerance 1) and human ASCIZ (ATM/ATR-substrate Chk2-interacting Zn2+-finger protein), were recently identified based on their interactions with the N-terminal FHA domains of the conserved checkpoint kinases Rad53 and Chk2, respectively, and ASCIZ was subsequently re-isolated as an ATM-interacting protein (ATMIN). Mdt1 and ASCIZ share remarkable sequence similarity (36% highly conserved residues, 17% identity) and extended SQ/TQ cluster domains (SCDs) typical of DNA damage response proteins. However, despite their structural similarities and conserved interactions with the checkpoint machinery, the two proteins seem to respond to different DNA lesions: the strongest phenotypes of ASCIZ deficiency are increased sensitivity to DNA base damaging agents and altered immunoglobulin gene diversification following enzyme-induced base damage in B lymphocytes, whereas absence of Mdt1 leads to hypersensitivity to 3'-blocked DNA double-strand breaks and inefficient recombinational maintenance of telomeres. The Mdt1/ASCIZ family may function as structurally related scaffolds that facilitate efficient DNA repair, albeit with diverged lesion specificity.     

Structure and Stability Insights into Tumour Suppressor p53 Evolutionary Related Proteins

The p53 family of genes and their protein products, namely, p53, p63 and p73, have over one billion years of evolutionary history. Advances in computational biology and genomics are enabling studies of the complexities of the molecular evolution of p53 protein family to decipher the underpinnings of key biological conditions spanning from cancer through to various metabolic and developmental disorders and facilitate the design of personalised medicines. However, a complete understanding of the inherent nature of the thermodynamic and structural stability of the p53 protein family is still lacking. This is due, to a degree, to the lack of comprehensive structural information for a large number of homologous proteins and to an incomplete knowledge of the intrinsic factors responsible for their stability and how these might influence function. Here we investigate the thermal stability, secondary structure and folding properties of the DNA-binding domains (DBDs) of a range of proteins from the p53 family using biophysical methods. While the N- and the C-terminal domains of the p53 family show sequence diversity and are normally targets for post-translational modifications and alternative splicing, the central DBD is highly conserved. Together with data obtained from Molecular Dynamics simulations in solution and with structure based homology modelling, our results provide further insights into the molecular properties of evolutionary related p53 proteins. We identify some marked structural differences within the p53 family, which could account for the divergence in biological functions as well as the subtleties manifested in the oligomerization properties of this family.     

Dynamics of protein folding and cofactor binding monitored by single-molecule force spectroscopy

Many proteins in living cells require cofactors to carry out their biological functions. To reach their functional states, these proteins need to fold into their unique three-dimensional structures in the presence of their cofactors. Two processes, folding of the protein and binding of cofactors, intermingle with each other, making the direct elucidation of the folding mechanism of proteins in the presence of cofactors challenging. Here we use single-molecule atomic force microscopy to directly monitor the folding and cofactor binding dynamics of an engineered metal-binding protein G6-53 at the single-molecule level. Using the mechanical stability of different conformers of G6-53 as sensitive probes, we directly identified different G6-53 conformers (unfolded, apo- and Ni²⁺-bound) populated along the folding pathway of G6-53 in the presence of its cofactor Ni²⁺. By carrying out single-molecule atomic force microscopy refolding experiments, we monitored kinetic evolution processes of these different conformers. Our results suggested that the majority of G6-53 folds through a binding-after-folding mechanism, whereas a small fraction follows a binding-before-folding pathway. Our study opens an avenue to utilizing force spectroscopy techniques to probe the folding dynamics of proteins in the presence of cofactors at the single-molecule level, and we anticipated that this method can be used to study a wide variety of proteins requiring cofactors for their function.     

Neuro-fuzzy structural classification of proteins for improved protein secondary structure prediction

Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins.     

Parametric sensitivity analysis of avian pancreatic polypeptide (APP)

Computer simulations utilizing a classical force field have been widely used to study biomolecular properties. It is important to identify the key force field parameters or structural groups controlling the molecular properties. In the present paper the sensitivity analysis method is applied to study how various partial charges and solvation parameters affect the equilibrium structure and free energy of avian pancreatic polypeptide (APP). The general shape of APP is characterized by its three principal moments of inertia. A molecular dynamics simulation of APP was carried out with the OPLS/Amber force field and a continuum model of solvation energy. The analysis pinpoints the parameters which have the largest (or smallest) impact on the protein equilibrium structure (i.e., the moments of inertia) or free energy. A display of the protein with its atoms colored according to their sensitivities illustrates the patterns of the interactions responsible for the protein stability. The results suggest that the electrostatic interactions play a more dominant role in protein stability than the part of the solvation effect modeled by the atomic solvation parameters. © 1995 Wiley-Liss, Inc.