Nutation frequency modulation on NMR signal of nuclear spins in chemical exchange with solvent water under the BEST conditions

Solvent exchange properties of protein backbone amide protons provide valuable residue‐specific information on protein solvent accessibility, structure stability and flexibility and hence are of significant interest in structural biology. NMR has served as a unique means for the characterization of chemical exchange including proton amide exchange with solvent water at residue‐specific levels across a broad range of exchange rates. One of the methods used for the characterization of protein backbone amide exchange by NMR involves the use of progressive selective irradiation of the water resonance. Here, we report the experimental observation of the nutation frequency (strength of RF field used for the irradiation of water resonance) modulation on amide proton signals for those in exchange with the solvent water under the band‐selective excitation short transient (BEST) conditions. Compared with conventional saturation transfer of water magnetization experiments, this nutation frequency modulation observed on signal of nuclear spins under the BEST conditions potentially offers a quick identification of protein backbone amides in rapid exchange with solvent water. Copyright © 2014 John Wiley & Sons, Ltd.     

Competitive adsorption of bacteriophage T4 lysozyme stability variants at hydrophilic glass surfaces

The competitive adsorption behavior exhibited by the wild-type T4 lysozyme and two of its structural stability variants was studied by 125I radioisotope labeling. The mutant lysozymes were produced by substitution of the isoleucine residue at position 3 in the wild type with a tryptophan residue, resulting in a protein with lower structural stability, or with a cysteine residue, resulting in a protein with higher structural stability. Adsorption kinetics were recorded for binary protein mixtures in contact with a clean glass surface, in which one variant had been radiolabeled and the other had not. All pair permutations were tested. The kinetic data show that in instances in which exchange reactions between adsorbed protein and dissolved protein occur, they occur such that more stable variants are removed from the surface by less stable variants. The less stable proteins thus exhibited an advantage in competitive adsorption over the more stable proteins, in these tests.     

Hybrid proteins with organophosphorus hydrolase activity and fluorescence of deGFP4 protein

New genetic constructs encoding synthesis of hybrid proteins possessing organophosphorus hydrolase activity and properties of the pH sensitive analog of the green fluorescent protein were developed. It was established that 0.1 mM of the biosynthesis inducer and cultivation for 10 h after the induction were necessary for the maximum yield of the hybrid proteins in the soluble and active form in E. coli cells. The demonstrated synthesis level for one of the new proteins was 2- to 25-fold higher than the yield of the soluble hybrid protein analogs known from the literature. It was found that the organophosphorus hydrolase within hybrid proteins demonstrated characteristics (pH optimum, thermal stability and catalytic efficiency) different from the respective characteristics known for the native enzyme. It was shown that the fluorescence of the green fluorescent protein within the hybrid proteins depended on the pH of the medium in a manner similar to the individual protein. Interrelation of the fluorescent characteristics and OPH activity that manifested itself in the hydrolysis of organophosphorus compounds was shown by example of one of the hybrid proteins.     

Sequential adsorption of bacteriophage T4 lysozyme stability variants at solid–water interfaces

The sequential adsorption of the wild type T4 lysozyme and one of its structural stability variants was studied, using ellipsometry and ¹²⁵I radioisotope labeling techniques. The mutant lysozyme was produced by substitution of the isoleucine residue at position 3 in the wild type with a tryptophan residue, resulting in a protein with lower structural stability. The mutant protein was more resistant to surfactant-mediated elution, and apparently adsorbed at the interfaces with a greater interfacial area/molecule than the wild typeT4 lysozyme. However, the results of each type of experiment suggested that sequential adsorption and exchange of proteins occurred only in the case of the less stable mutant followed by the wild type. This suggests that, in these exchange reactions, properties of the adsorbing protein (e.g. its ability to adsorb when a relatively small amount of unoccupied area is present) were more important than the apparent binding strength of the adsorbed protein molecules.     

A fluorescence-based assay for nanogram quantification of proteins using a protein binding ligand

Fluorescence emission has been investigated in the context of estimation of proteins at nanogram levels. A Schiff base ligand with donor-acceptor substituents has been utilized as a fluorescent probe. The potency of this ligand is that it possesses the binding sites for both hydrophobic as well as hydrophilic groups in the proteins. The fluorescence emission of the probe was enhanced in the presence of nanogram levels of protein, which clearly signifies that even the least concentration of the protein is sufficient to perturb the environment around the probe. We demonstrate here that the fluorescence characteristic of the probe can be utilized to estimate even nanogram levels (66 ng-1 microgram mL(-1)) of protein. The major limitation of the currently available standard methods is the range of protein estimation, which terminates at microgram level and the interference due to the specificity of the amino acids, which vary from proteins to proteins. This fluorescence emission-based method is free from interference from any type of buffers, ionic strength of the medium and any specific amino acid residue and is a simple, rapid, single-step, sensitive method of estimation which can be applied to different classes of proteins.     

Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography

Artificial Neural Networks (ANNs) present a powerful tool for the modeling of chromatographic retention. In this paper, the main objective was to use ANNs as a tool in modeling of atorvastatin and its impurities?? retention in a micellar liquid chromatography (MLC) protocol. Factors referred to MLC were evaluated through 30 experiments defined by the Central Composite Design. In this manner, 5?Cx?C3 topology as a starting point for ANNs?? optimization was defined too. In the next step, in order to set the network with the best performance, network optimization was done. In the first part, the number of nodes in the hidden layer and the number of experimental data points in training set were simultaneously varied, and their importance was estimated with suitable statistical parameters. Furthermore, a series of training algorithms was applied to the current network. The Back Propagation, Conjugate Gradient-descent, Quick Propagation, Quasi-Newton, and Delta-bar-Delta algorithms were used to obtain the optimal network. Finally, the predictive ability of the optimized neural network was confirmed through several statistical tests. The obtained network showed high ability to predict chromatographic retention of atorvastatin and its impurities in MLC.     

An eight residue fragment of an acyl carrier protein suffices for post-translational introduction of fluorescent pantetheinyl arms in protein modification in vitro and in vivo

Genetically encoded tags for tracking a given protein continue to be of great interest in a multitude of in vitro and in vivo contexts. Acyl carrier proteins, both free-standing and as embedded 80-100 residue domains, contain a specific serine side chain that undergoes post-translational pantetheinylation from CoASH as donor substrate. We have previously used phage display methods to select a 12 residue fragment that retains recognition for modification by the Escherichia coli phosphopantetheinyltransferase (PPTase) AcpS. In this work, we have used (15)N-HSQC based NMR titration experiments of a 12-residue peptide substrate with AcpS to identify six specifically interacting residues (S3, L4, D5, M6, W9, and L11) without the formation of any notable secondary structure. Synthesis of a corresponding octapeptide containing 5 of the 6 interacting residues generated a minimal fragment capable of efficient post-translational phosphopantetheinylation. Genetic insertion of this eight residue coding sequence into the proteins sonic hedgehog and transferrin receptor enabled good in vitro and in vivo PPTase-mediated modification by a series of fluorescent CoAs, leading to a set of fluorescent proteins with a peptide tag minimally perturbant to protein folds.     

Conversion of red fluorescent protein into a bright blue probe

We used a red chromophore formation pathway, in which the anionic red chromophore is formed from the neutral blue intermediate, to suggest a rational design strategy to develop blue fluorescent proteins with a tyrosine-based chromophore. The strategy was applied to red fluorescent proteins of the different genetic backgrounds, such as TagRFP, mCherry, HcRed1, M355NA, and mKeima, which all were converted into blue probes. Further improvement of the blue variant of TagRFP by random mutagenesis resulted in an enhanced monomeric protein, mTagBFP, characterized by the substantially higher brightness, the faster chromophore maturation, and the higher pH stability than blue fluorescent proteins with a histidine in the chromophore. The detailed biochemical and photochemical analysis indicates that mTagBFP is the true monomeric protein tag for multicolor and lifetime imaging, as well as the outstanding donor for green fluorescent proteins in F?rster resonance energy transfer applications.     

Protein recognition by bivalent, ‘turn-on’ fluorescent molecular probes

We show that the conversion of a known intercalating dye (i.e., thiazole orange) into a bivalent protein binder could lead to the realization of a novel class of ‘turn-on’ fluorescent molecular probes that detect proteins with high affinity, selectivity, and a high signal-to-noise (S/N) ratio. The feasibility of the approach is demonstrated with monomolecular probes that light-up in the presence of three different proteins: acetylcholinesterase (AChE), glutathione-s-transferase (GST), or avidin (Av) at low concentrations and with minimal background signal. The way by which such probes can be used to detect individual protein isoforms and be applied in inhibitor screening, cell imaging, and biomarker detection is described.     

Machine learning algorithms for predicting protein folding rates and stability of mutant proteins: comparison with statistical methods

Machine learning algorithms have wide range of applications in bioinformatics and computational biology such as prediction of protein secondary structures, solvent accessibility, binding site residues in protein complexes, protein folding rates, stability of mutant proteins, and discrimination of proteins based on their structure and function. In this work, we focus on two aspects of predictions: (i) protein folding rates and (ii) stability of proteins upon mutations. We briefly introduce the concepts of protein folding rates and stability along with available databases, features for prediction methods and measures for prediction performance. Subsequently, the development of structure based parameters and their relationship with protein folding rates will be outlined. The structure based parameters are helpful to understand the physical basis for protein folding and stability. Further, basic principles of major machine learning techniques will be mentioned and their applications for predicting protein folding rates and stability of mutant proteins will be illustrated. The machine learning techniques could achieve the highest accuracy of predicting protein folding rates and stability. In essence, statistical methods and machine learning algorithms are complimenting each other for understanding and predicting protein folding rates and the stability of protein mutants. The available online resources on protein folding rates and stability will be listed.     

Characterization of N-palmitoylated human growth hormone by in situ liquid-liquid extraction and MALDI tandem mass spectrometry

Acylation is a common post-translational modification found in secreted proteins and membrane-associated proteins, including signal transducing and regulatory proteins. Acylation is also explored in the pharmaceutical and biotechnology industry to increase the stability and lifetime of protein-based products. The presence of acyl moieties in proteins and peptides affects the physico-chemical properties of these species, thereby modulating protein stability, function, localization and molecular interactions. Characterization of protein acylation is a challenging analytical task, which includes the precise definition of the acylation sites in proteins and determination of the identity and molecular heterogeneity of the acyl moiety at each individual site. In this study, we generated a chemically modified human growth hormone (hGH) by incorporation of a palmitoyl moiety on the N(epsilon) group of a lysine residue. Monoacylation of the hGH protein was confirmed by determination of the intact molecular weight by mass spectrometry. Detailed analysis of protein acylation was achieved by analysis of peptides derived from hGH by protease treatment. However, peptide mass mapping by MALDI MS using trypsin and AspN proteases and standard sample preparation methods did not reveal any palmitoylated peptides. In contrast, in situ liquid-liquid extraction (LLE) performed directly on the MALDI MS metal target enabled detection of acylated peptide candidates by MALDI MS and demonstrated that hGH was N-palmitoylated at multiple lysine residues. MALDI MS and MS/MS analysis of the modified peptides mapped the N-palmitoylation sites to Lys158, Lys172 and Lys140 or Lys145. This study demonstrates the utility of LLE/MALDI MS/MS for mapping and characterization of acylation sites in proteins and peptides and the importance of optimizing sample preparation methods for mass spectrometry-based determination of substoichiometric, multi-site protein modifications.     

A General Mechanism of Photoconversion of Green‐to‐Red Fluorescent Proteins Based on Blue and Infrared Light Reduces Phototoxicity in Live‐Cell Single‐Molecule Imaging

Photoconversion of fluorescent proteins by blue and complementary near‐infrared light, termed primed conversion (PC), is a mechanism recently discovered for Dendra2. We demonstrate that controlling the conformation of arginine at residue 66 by threonine at residue 69 of fluorescent proteins from Anthozoan families (Dendra2, mMaple, Eos, mKikGR, pcDronpa protein families) represents a general route to facilitate PC. Mutations of alanine 159 or serine 173, which are known to influence chromophore flexibility and allow for reversible photoswitching, prevent PC. In addition, we report enhanced photoconversion for pcDronpa variants with asparagine 116. We demonstrate live‐cell single‐molecule imaging with reduced phototoxicity using PC and record trajectories of RNA polymerase in Escherichia coli cells.     

Painting Proteins with Covalent Labels: What's In the Picture?

Knowledge about the structural and biophysical properties of proteins when they are free in solution and/or in complexes with other molecules is essential for understanding the biological processes that proteins regulate. Such knowledge is also important to drug discovery efforts, particularly those focused on the development of therapeutic agents with protein targets. In the last decade a variety of different covalent labeling techniques have been used in combination with mass spectrometry to probe the solution-phase structures and biophysical properties of proteins and protein—ligand complexes. Highlighted here are five different mass spectrometry—based covalent labeling strategies including: continuous hydrogen/deuterium (H/D) exchange labeling, hydroxyl radical-mediated footprinting, SUPREX (stability of unpurified proteins from rates of H/D exchange), PLIMSTEX (protein-ligand interaction by mass spectrometry, titration, and H/D exchange), and SPROX (stability of proteins from rates of oxidation). The basic experimental protocols used in each of the above-cited methods are summarized along with the kind of biophysical information they generate. Also discussed are the relative strengths and weaknesses of the different methods for probing the wide range of conformational states that proteins and protein-ligand complexes can adopt when they are in solution.     

Efficient machine learning model for predicting drug-target interactions with case study for Covid-19

BackgroundDiscover possible Drug Target Interactions (DTIs) is a decisive step in the detection of the effects of drugs as well as drug repositioning. There is a strong incentive to develop effective computational methods that can effectively predict potential DTIs, as traditional DTI laboratory experiments are expensive, time-consuming, and labor-intensive. Some technologies have been developed for this purpose, however large numbers of interactions have not yet been detected, the accuracy of their prediction still low, and protein sequences and structured data are rarely used together in the prediction process.MethodsThis paper presents DTIs prediction model that takes advantage of the special capacity of the structured form of proteins and drugs. Our model obtains features from protein amino-acid sequences using physical and chemical properties, and from drugs smiles (Simplified Molecular Input Line Entry System) strings using encoding techniques. Comparing the proposed model with different existing methods under K-fold cross validation, empirical results show that our model based on ensemble learning algorithms for DTI prediction provide more accurate results from both structures and features data.ResultsThe proposed model is applied on two datasets:Benchmark (feature only) datasets and DrugBank (Structure data) datasets. Experimental results obtained by Light-Boost and ExtraTree using structures and feature data results in 98 % accuracy and 0.97 f-score comparing to 94 % and 0.92 achieved by the existing methods. Moreover, our model can successfully predict more yet undiscovered interactions, and hence can be used as a practical tool to drug repositioning.A case study of applying our prediction model on the proteins that are known to be affected by Corona viruses in order to predict the possible interactions among these proteins and existing drugs is performed. Also, our model is applied on Covid-19 related drugs announced on DrugBank. The results show that some drugs like DB00691 and DB05203 are predicted with 100 % accuracy to interact with ACE2 protein. This protein is a self-membrane protein that enables Covid-19 infection. Hence, our model can be used as an effective tool in drug reposition to predict possible drug treatments for Covid-19.     

Characterization of cysteine residues and disulfide bonds in proteins by liquid chromatography/electrospray ionization tandem mass spectrometry

Cysteine residues and disulfide bonds are important for protein structure and function. We have developed a simple and sensitive method for determining the presence of free cysteine (Cys) residues and disulfide bonded Cys residues in proteins (<100 pmol) by liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) in combination with protein database searching using the program Sequest. Free Cys residues in a protein were labeled with PEO-maleimide biotin immediately followed by denaturation with 8 M urea. Subsequently, the protein was digested with trypsin or chymotrypsin and the resulting products were analyzed by capillary LC/ESI-MS/MS for peptides containing modified Cys and/or disulfide bonded Cys residues. Although the MS method for identifying disulfide bonds has been routinely employed, methods to prevent thiol-disulfide exchange have not been well documented. Our protocol was found to minimize the occurrence of the thiol-disulfide exchange reaction. The method was validated using well-characterized proteins such as aldolase, ovalbumin, and beta-lactoglobulin A. We also applied this method to characterize Cys residues and disulfide bonds of beta 1,4-galactosyltransferase (five Cys), and human blood group A and B glycosyltransferases (four Cys). Our results demonstrate that beta 1,4-galactosyltransferase contains one free Cys residue and two disulfide bonds, which is in contrast to work previously reported using chemical methods for the characterization of free Cys residues, but is consistent with recently published results from x-ray crystallography. In contrast to the results obtained for beta 1,4-galactosyltransferase, none of the Cys residues in A and B glycosyltransferases were found to be involved in disulfide bonds.     

Detection of S-palmitoylated Proteins in Mouse Heart Tissue Based on Different Precipitation Methods

The acyl-biotinyl exchange (ABE) is widely used for detection of S-palmitoylated proteins by replacing palmitic acid with biotin, which is a common method for detecting S-palmitoylated proteins. In this study, the effects of acetone precipitation and methanol-chloroform precipitation on the detection of S-palmitoylation proteins in acyl-biotin exchange method were compared, and the S-palmitoylated proteins in mouse cardiac tissue were analyzed. First, N-ethylmaleimide (NEM) was used to block free sulfhydryls within protein molecules. Then, biotinylation reagent (HPDP-Biotin) was used to label the newly produced cysteine thiols that were resulted from treatment by hydroxylamine (HA) in mouse heart tissue. During the ABE reaction, excess unreacted NEM, HA and HPDP-Biotin were removed by precipitation of the proteins. Then, the S-palmitoylated proteins from heart tissue were labeled with ABE reaction based on different precipitation methods, and the S-palmitoylated proteins labeled with biotin were enriched by streptavidin agarose beads. The enriched proteins were analyzed by mass spectrometry, and 50 S-palmitoylated proteins were identified. Specifically, 23 S-palmitoylated proteins were identified in acetone precipitation assay group, and 37 S-palmitoylated proteins in the methanol-chloroform precipitation assay group were identified. 10 palmitoylated proteins were identified in both groups. The results showed that the combination of different precipitation methods could be helpful for the identification of palmitoylated proteins.     

Changes in solvent exposure reveal the kinetics and equilibria of adsorbed protein unfolding in hydrophobic interaction chromatography

Hydrogen exchange has been a useful technique for studying the conformational state of proteins, both in bulk solution and at interfaces, for several decades. Here, we propose a physically based model of simultaneous protein adsorption, unfolding and hydrogen exchange in HIC. An accompanying experimental protocol, utilizing mass spectrometry to quantify deuterium labeling, enables the determination of both the equilibrium partitioning between conformational states and pseudo-first order rate constants for folding and unfolding of adsorbed protein. Unlike chromatographic techniques, which rely on the interpretation of bulk phase behavior, this methodology utilizes the measurement of a molecular property (solvent exposure) and provides insight into the nature of the unfolded conformation in the adsorbed phase. Three model proteins of varying conformational stability, α-chymotrypsinogen A, β-lactoglobulin B, and holo α-lactalbumin, are studied on Sepharose™ HIC resins possessing assorted ligand chemistries and densities. α-Chymotrypsinogen, conformationally the most stable protein in the set, exhibits no change in solvent exposure at all the conditions studied, even when isocratic pulse-response chromatography suggests nearly irreversible adsorption. Apparent unfolding energies of adsorbed β-lactoglobulin B and holo α-lactalbumin range from −4 to 3 kJ/mol and are dependent on resin properties and salt concentration. Characteristic pseudo-first order rate constants for surface-induced unfolding are 0.2–0.9 min⁻¹. While poor protein recovery in HIC is often associated with irreversible unfolding, this study documents that non-eluting behavior can occur when surface unfolding is reversible or does not occur at all. Further, this hydrogen exchange technique can be used to assess the conformation of adsorbed protein under conditions where the protein is non-eluting and chromatographic methods are not applicable.     

Prediction of protein structural classes by a new measure of information discrepancy

Since it was observed that the structural class of a protein is related to its amino acid composition, various methods based on amino acid composition have been proposed to predict protein structural classes. Though those methods are effective to some degree, their predictive quality is confined because amino acid composition cannot sufficiently include the information of protein sequences. In this paper, a measure of information discrepancy is applied to the prediction of protein structural classes; different from the previous methods, this new approach is based on the comparisons of subsequence distributions; therefore, the effect of residue order on protein structure is taken into account. The predictive results of the new approach on the same data set are better than those of the previous methods. As to a data set of 1401 sequences with no more than 30% redundancy, the overall correctness rates of resubstitution test and Jackknife test are 99.4 and 75.02%, respectively, and to other data sets the similar results are also obtained. All tests demonstrate that the residue order along protein sequences plays an important role on recognition of protein structural classes, especially for alpha/beta proteins and alpha+beta proteins. In addition, the tests also show that the new method is simple and efficient.     

Protein dynamics studies on a wheat type 2 lipid transfer protein

Plant non specific lipid transfer proteins form a superfamily of related proteins composed of type 1 and type 2 LTPs. Type 2 LTPs have been less extensively studied than type 1 and differ in term of primary sequence, molecular mass and transfer efficiency. We have undertaken NMR studies of the wheat 7 kDa type 2 LTP. Whilst the 3D structure determination is in progress, we have studied the protein dynamics. Two zones have been defined within the protein. One remains unperturbed, the LTP being liganded or not; the other one exists in different states, depending on the ligandation, and on the kind of lipid interacting with the protein. S² determination showed a rigid backbone. Multifield analysis allowed the calculation of the chemical exchange rate for each residue.