Structural Studies Of Proteins Research Articles

High-throughput strategy for identification of Mycobacterium tuberculosis membrane protein expression conditions using folding reporter GFP

Mycobacterium tuberculosis membrane protein biochemistry and structural biology studies are often hampered by challenges in protein expression and selection for well-expressing protein candidates, suitable for further investigation. Here we present a folding reporter GFP (frGFP) assay, adapted for M. tuberculosis membrane protein screening in Escherichia coli Rosetta 2 (DE3) and Mycobacterium smegmatis mc24517. This method allows protein expression condition screening for multiple protein targets simultaneously by monitoring frGFP fluorescence in growing cells. We discuss the impact of common protein expression conditions on 42 essential M. tuberculosis H37Rv helical transmembrane proteins and establish the grounds for their further analysis. We have found that the basal expression of the lac operon in the T7-promoter expression system generally leads to high recombinant protein yield in M. smegmatis, and we suggest that a screening condition without the inducer is included in routine protein expression tests. In addition to the general observations, we describe conditions allowing high-level expression of more than 25 essential M. tuberculosis membrane proteins, containing 2 to 13 transmembrane helices. We hope that these findings will stimulate M. tuberculosis membrane protein research and aid the efforts in drug development against tuberculosis.

Innovative in Silico Approaches for Characterization of Genes and Proteins.

Bioinformatics is an amalgamation of biology, mathematics and computer science. It is a science which gathers the information from biology in terms of molecules and applies the informatic techniques to the gathered information for understanding and organizing the data in a useful manner. With the help of bioinformatics, the experimental data generated is stored in several databases available online like nucleotide database, protein databases, GENBANK and others. The data stored in these databases is used as reference for experimental evaluation and validation. Till now several online tools have been developed to analyze the genomic, transcriptomic, proteomics, epigenomics and metabolomics data. Some of them include Human Splicing Finder (HSF), Exonic Splicing Enhancer Mutation taster, and others. A number of SNPs are observed in the non-coding, intronic regions and play a role in the regulation of genes, which may or may not directly impose an effect on the protein expression. Many mutations are thought to influence the splicing mechanism by affecting the existing splice sites or creating a new sites. To predict the effect of mutation (SNP) on splicing mechanism/signal, HSF was developed. Thus, the tool is helpful in predicting the effect of mutations on splicing signals and can provide data even for better understanding of the intronic mutations that can be further validated experimentally. Additionally, rapid advancement in proteomics have steered researchers to organize the study of protein structure, function, relationships, and dynamics in space and time. Thus the effective integration of all of these technological interventions will eventually lead to steering up of next-generation systems biology, which will provide valuable biological insights in the field of research, diagnostic, therapeutic and development of personalized medicine.

Microfluidics delivery of DARPP-32 into HeLa cells maintains viability for in-cell NMR spectroscopy

High-resolution structural studies of proteins and protein complexes in a native eukaryotic environment present a challenge to structural biology. In-cell NMR can characterize atomic resolution structures but requires high concentrations of labeled proteins in intact cells. Most exogenous delivery techniques are limited to specific cell types or are too destructive to preserve cellular physiology. The feasibility of microfluidics transfection or volume exchange for convective transfer, VECT, as a means to deliver labeled target proteins to HeLa cells for in-cell NMR experiments is demonstrated. VECT delivery does not require optimization or impede cell viability; cells are immediately available for long-term eukaryotic in-cell NMR experiments. In-cell NMR-based drug screening using VECT was demonstrated by collecting spectra of the sensor molecule DARPP32, in response to exogenous administration of Forskolin.

When molecules come to life – Using Augmented reality for studying protein structure in Cell Biology class

Most Undergraduate Biology courses cover an incredibly large range of topics integrating complex information at molecular, cellular, genetic and at the organismal level. Translating concepts from one level of thought to another and crossing disciplines equally and fluidly largely depends on how well students understand the structure‐function relationship at the micro and macro level. A survey of the literature shows that despite having encountered these structures of biomolecules in their earlier courses, students lack an ability to visualize molecules and interactions. Most classroom curriculums use textbooks and lecture slides with straightforward two‐dimensional structures that make it hard for students to visualize these macromolecules. To improve motivation and to promote student interactivity, in Cell Biology classes I have used molecular models in Augmented reality to reform content delivery by using interactive active learning techniques. This presentation will discuss ways for instructors to implement Augmented reality in their classes to help students better understand concepts of structure and function of Biomolecules.

Glyco-Steroidal Amphiphiles (GSAs) for Membrane Protein Structural Study.

Integral membrane proteins pose considerable challenges to high resolution structural analysis. Maintaining membrane proteins in their native state during protein isolation is essential for structural study of these bio-macromolecules. Detergents are the most commonly used amphiphilic compounds for stabilizing membrane proteins in solution outside a lipid bilayer. We previously introduced a glyco-diosgenin (GDN) detergent that was shown to be highly effective at stabilizing a wide range of membrane proteins. This steroidal detergent has additionally gained attention due to its compatibility with membrane protein structure study via cryo-EM. However, synthetic inconvenience limits widespread use of GDN in membrane protein study. To improve its synthetic accessibility and to further enhance detergent efficacy for protein stabilization, we designed a new class of glyco-steroid-based detergents using three steroid units: cholestanol, cholesterol and diosgenin. These new detergents were efficiently prepared and showed marked efficacy for protein stabilization in evaluation with a few model membrane proteins including two G protein-coupled receptors. Some new agents were not only superior to a gold standard detergent, DDM (n-dodecyl-β-d-maltoside), but were also more effective than the original GDN at preserving protein integrity long term. These agents represent valuable alternatives to GDN, and are likely to facilitate structural determination of challenging membrane proteins.

Saponins Form Nonionic Lipid Nanodiscs for Protein Structural Studies by Nuclear Magnetic Resonance Spectroscopy.

Structural studies of membrane proteins in native-like environments require the development of diverse membrane mimetics. Currently there is a need for nanodiscs formed with nonionic belt molecules to avoid nonphysiological electrostatic interactions between the membrane system and protein of interest. Here, we describe the formation of lipid nanodiscs from the phospholipid DMPC and a class of nonionic glycoside natural products called saponins. The morphology, surface characteristics, and magnetic alignment properties of the saponin nanodiscs were characterized by light scattering and solid-state NMR experiments. We determined that preparing nanodiscs with high saponin/lipid ratios reduced their size, diminished their ability to spontaneously align in a magnetic field, and favored insertion of individual saponin molecules in the lipid bilayer surface. Further, purification of saponin nanodiscs allowed flipping of the orientation of aligned nanodiscs by 90°. Finally, we found that aligned saponin nanodiscs provide a sufficient alignment medium to allow the measurement of residual dipolar couplings (RDCs) in aqueous cytochrome c.

Multiplexed Isobaric Quantitative Cross-Linking Reveals Drug-Induced Interactome Changes in Breast Cancer Cells.

The study of protein structures and interactions is critical to understand their function. Chemical cross-linking of proteins with mass spectrometry (XL-MS) is a rapidly developing structural biology technique able to provide valuable insight into protein conformations and interactions, even as they exist within their native cellular environment. Quantitative analysis of cross-links can reveal protein conformational and interaction changes that occur as a result of altered biological states, environmental conditions, or pharmacological perturbations. Our laboratory recently developed an isobaric quantitative protein interaction reporter (iqPIR) cross-linking strategy for comparative interactome studies. This strategy relies on isotope encoded chemical cross-linkers that have the same molecular mass yet produce unique and specific isotope signatures upon fragmentation in the mass spectrometer which can be used for quantitative analysis of cross-linked peptides. The initial set of iqPIR molecules allowed for binary comparisons. Here, we describe the in vivo application of an extended set of six iqPIR reagents (6-plex iqPIR), allowing multiplexed quantitative interactome analysis of up to six biological samples in a single LC-MS acquisition. Multiplexed iqPIR is demonstrated on MCF-7 breast cancer cells treated with five different Hsp90 inhibitors revealing large scale protein conformational and interaction changes specific to the molecular class of the inhibitors.

Delivery of target proteins through microfluidics supports increased cell viability for in-cell NMR spectroscopy

Physiological relevance as it pertains to in vitro v. in vivo research has been a topic of critical discussion in the field chemical biology, particularly as it applies to high-resolution, structural studies of proteins and the cellular environment. In-cell NMR presents a modern approach that helps bridge this gap, but it requires delivery of labeled protein into the living cell. The current array of common protein transfection methods involve damage to cell physiology and limited scalability. We tested a microfulidics method, Volume Exchange for Convective Transfer, VECT, demonstrating its feasibility for delivery of target protein into large numbers of eukaryotic cells with limited impact on viability.

Predicting spectroscopic properties of fluorescent proteins with a variational autoencoder

Fluorescent proteins are ubiquitous as a visualization tool in biological research and efforts to improve their experimentally useful properties are of practical interest. Owing to a diversity of existing methods, such as photophysical characterization and protein structural studies, there is substantial literature about residues and secondary structures that can be altered to modulate spectroscopic properties. Yet, an efficient strategy for identifying such sites and predicting the impact of mutagenesis remains elusive.

Protein structural ensembles by integrative computational-experimental approaches

Understanding the molecular mechanisms used by biological systems to perform their functions is often essential to rationally target associated diseases. In many cases, the knowledge of the 3D structure of these systems provides precious insights. However, it is often the interplay between structural and dynamical properties that determines the behavior of complex systems. While both experimental and computational methods are invaluable tools to study protein structure and dynamics, limitations in each individual technique can hamper their capabilities.

Combing force manipulation and Raman spectroscopy characterization to study protein structures

Single-molecule force spectroscopy delineates the individual behavior of molecules from the molecular extensions associated with conformational changes versus force manipulations. Vibrational spectroscopy depicts the molecular structures from the endogenous oscillations of all chemical bonds inside the molecules upon irradiation. Leveraging both tools, we are able to precisely control a single molecule, directly monitor the force-associated structural changes, and efficiently characterize the designated intermediates in dynamic processes.

Improving membrane protein structural study in electron cryo-microscopy: impact of surfactant excess

Over the past decade, the number of membrane protein (MP) structures solved at the atomic resolution level by electron cryo-microscopy (cryo-EM) has increased dramatically [1]. Despite the impact of cryo-EM in MP structural biology, further technological developments are still required. A major limitation lies in the preparation of high-quality grids: general advices might be shared [2], but grid properties remain poorly reproducible and system-dependent.

Comparative evaluation of spin label modeling methods for protein structural studies

Site-directed spin labeling (SDSL) in conjunctions with electron paramagnetic resonance (EPR) is a powerful tool for investigating protein structure and dynamics. Several EPR experiments can be utilized to evaluate motion, membrane interactions and measure distance distributions between spin labels attached to proteins. Our ability to investigate protein structure and dynamics from SDSL EPR experiments depends on accurate and efficient spin label modeling methods. While several spin label modeling methods exist, a robust comparative evaluation of these methods over a large data set has not been performed.

Studying protein structure and function by native separation-mass spectrometry.

Alterations in protein structure may have profound effects on biological function. Analytical techniques that permit characterization of proteins while maintaining their conformational and functional state are crucial for studying changes in the higher order structure of proteins and for establishing structure-function relationships. Coupling of native protein separations with mass spectrometry is emerging rapidly as a powerful approach to study these aspects in a reliable, fast and straightforward way. This Review presents the available native separation modes for proteins, covers practical considerations on the hyphenation of these separations with mass spectrometry and highlights the involvement of affinity-based separations to simultaneously obtain structural and functional information of proteins. The impact of these approaches is emphasized by selected applications addressing biomedical and biopharmaceutical research questions.

Designing Overlap Extension PCR Primers for Protein Mutagenesis: A Programmatic Approach.

Overlap extension PCR is one of the routinely used methods to generate mutagenic genes for the functional and structural study of proteins. However, it is time-consuming to design the overlapping mutagenic primers and gene primers by manual operation. In this chapter, we present a Python script that is able to search all the possible primer combinations according to the preset definitions and calculate the necessary parameters of each primer for the users, which could facilitate the primer design process. Up to 256 pairs of primers can be provided for selection using this script.

A radical approach to radicals.

Nitroxide radicals are characterized by a long-lived spin-unpaired electronic ground state and are strongly sensitive to their chemical surroundings. Combined with electron paramagnetic resonance spectroscopy, these electronic features have led to the widespread application of nitroxide derivatives as spin labels for use in studying protein structure and dynamics. Site-directed spin labelling requires the incorporation of nitroxides into the protein structure, leading to a new protein-ligand molecular model. However, in protein crystallographic refinement nitroxides are highly unusual molecules with an atypical chemical composition. Because macromolecular crystallography is almost entirely agnostic to chemical radicals, their structural information is generally less accurate or even erroneous. In this work, proteins that contain an example of a radical compound (Chemical Component Dictionary ID MTN) from the nitroxide family were re-refined by defining its ideal structural parameters based on quantum-chemical calculations. The refinement results show that this procedure improves the MTN ligand geometries, while at the same time retaining higher agreement with experimental data.

Molecular insight into sulfa antibiotic drug binding with human proteins

Biomaterial protein, perform the most effectual and distinct functions in cells. They execute numerous functions that include control of biochemical reaction, transport of molecules, building the immune system etc. Considering the fact that proteins are the preferred druggable targets for most of small molecules/ligands; in this manuscript we have deciphered the thermodynamic profile of two antibiotic drugs sulfamethazine (SMZ) and sulfadiazine (SDZ) upon interaction with myoglobin. Temperature dependent fluorescence spectroscopy and molecular dynamic simulation have been employed to monitor the said complexation reaction(s). The experimental data denoted spontaneous, electrostatic and hydrophobic interaction involved between the protein and the drugs. The results further suggested enthalpy driven exothermic binding process for both the cases. The interaction affinity is slightly more for SMZ as compared to that SDZ. Molecular dynamics (MD) simulation complimented the complex bindings with stability and compactness of the protein upon ligation. This work can help and shape the study of biomaterial protein structure and function upon binding with the drug which will provide useful information in designing and modifying the target as well as the ligand in the field of biomedical research.

DLBLS_SS: protein secondary structure prediction using deep learning and broad learning system.

Protein secondary structure prediction (PSSP) is not only beneficial to the study of protein structure and function but also to the development of drugs. As a challenging task in computational biology, experimental methods for PSSP are time-consuming and expensive. In this paper, we propose a novel PSSP model DLBLS_SS based on deep learning and broad learning system (BLS) to predict 3-state and 8-state secondary structure. We first use a bidirectional long short-term memory (BLSTM) network to extract global features in residue sequences. Then, our proposed SEBTCN based on temporal convolutional networks (TCN) and channel attention can capture bidirectional key long-range dependencies in sequences. We also use BLS to rapidly optimize fused features while further capturing local interactions between residues. We conduct extensive experiments on public test sets including CASP10, CASP11, CASP12, CASP13, CASP14 and CB513 to evaluate the performance of the model. Experimental results show that our model exhibits better 3-state and 8-state PSSP performance compared to five state-of-the-art models.

Protein Subcellular Localization Based on Evolutionary Information and Segmented Distribution

The prediction of protein subcellular localization not only is important for the study of protein structure and function but also can facilitate the design and development of new drugs. In recent years, feature extraction methods based on protein evolution information have attracted much attention and made good progress. Based on the protein position-specific score matrix (PSSM) obtained by PSI-BLAST, PSSM-GSD method is proposed according to the data distribution characteristics. In order to reflect the protein sequence information as much as possible, AAO method, PSSM-AAO method, and PSSM-GSD method are fused together. Then, conditional entropy-based classifier chain algorithm and support vector machine are used to locate multilabel proteins. Finally, we test Gpos-mPLoc and Gneg-mPLoc datasets, considering the severe imbalance of data, and select SMOTE algorithm to expand a few sample; the experiment shows that the AAO + PSSM ∗ method in the paper achieved 83.1% and 86.8% overall accuracy, respectively. After experimental comparison of different methods, AAO + PSSM ∗ has good performance and can effectively predict protein subcellular location.

TfNN15N: A γ-15N-Labeled Diazo-Transfer Reagent for the Synthesis of β-15N-Labeled Azides.

Azides are infrared (IR) probes that are important for structure and dynamics studies of proteins. However, they often display complex IR spectra owing to Fermi resonances and multiple conformers. Isotopic substitution of azides weakens the Fermi resonance, allowing more accurate IR spectral analysis. Site-specifically 15N-labeled aromatic azides, but not aliphatic azides, are synthesized through nitrosation. Both 15N-labeled aromatic and aliphatic azides are synthesized through nucleophilic substitution or diazo-transfer reaction but as an isotopomeric mixture. We present the synthesis of TfNN15N, a γ-15N-labeled diazo-transfer reagent, and its use to prepare β-15N-labeled aliphatic as well as aromatic azides.