Molecular aptamers for real-time protein-protein interaction study

Protein-protein interactions play critical roles in cellular functions, but current techniques for real-time study of these interactions are limited. We report the real-time monitoring of protein-protein interactions without labeling either of the two interacting proteins; this procedure poses minimum effects on the binding properties of the proteins. Our strategy uses a protein/aptamer complex to probe the interactions in a competitive assay where the binding of an aptamer to its target protein is altered by a second protein that interacts with the target protein. Two signal transduction strategies, fluorescence resonance energy transfer (FRET) and fluorescence anisotropy, have been designed to study the interactions of human alpha-thrombin with different proteins by using two aptamers specific for two binding sites on alpha-thrombin. Our method has been shown to be simple and effective, does not require labeling of proteins, makes use of easily obtainable aptamers, provides detailed protein-protein interaction information and has excellent sensitivity for protein detection and protein-protein interaction studies. The FRET and the fluorescent anisotropy approaches complement each other in providing insight into the kinetics, mechanisms, binding sites and binding dynamics of the interacting proteins.     

化学生物学新前沿——化学蛋白质组学

随着包括人类在内的主要模式生物的基因组计划的完成,生命科学的研究重心转向蛋白质组的研究--在对应基因组的整体蛋白质水平上系统研究调控细胞生命活动的蛋白质.化学蛋白质组学是化学生物学在后基因组时代的最新发展:化学蛋白质组学利用化学小分子为工具和手段,以基于靶蛋白质功能的新战略探测体内蛋白质组,是新一代的功能蛋白质组学.本文综述了化学蛋白质组学的最新进展、有关技术及其在生物医学和药物研发等方面的应用,并对化学蛋白质组学的发展趋势和前景进行了讨论.     

Targeting programmed cell death 4 (PDCD4) with biogenic compounds in ARDS by Gaussian process‐based QSAR virtual screening

The programmed cell death 4 (PDCD4) has recently been recognized as a new and attractive target of acute respiratory distress syndrome. Here, we attempted to discover new and potent PDCD4 mediator ligands from biogenic compounds using a synthetic strategy of statistical virtual screening and experimental affinity assay. In the procedure, a Gaussian process‐based quantitative structure‐activity relationship regression predictor was developed and validated statistically based on a curated panel of structure‐based protein‐ligand affinity data. The predictor was integrated with pharmacokinetics analysis, chemical redundancy reduction, and flexible molecular docking to perform high‐throughput virtual screening against a distinct library of chemically diverse, drug‐like biogenic compounds. Consequently, 6 hits with top scores were selected, and their binding affinities to the recumbent protein of human PDCD4 were identified, 3 out of which were determined to have high or moderate affinity with K_d at micromolar level. Structural analysis of protein‐ligand complexes revealed that hydrophobic interactions and van der Waals contacts are the primary chemical forces to stabilize the complex architecture of PDCD4 with these mediator ligands, while few hydrogen bonds, salt bridges, and/or π‐π stacking at the complex interfaces confer selectivity and specificity for the protein‐ligand recognition. It is suggested that the statistical Gaussian process‐based quantitative structure‐activity relationship screening strategy can be successfully applied to rational discovery of biologically active compounds. The newly identified molecular entities targeting PDCD4 are considered as promising lead scaffolds to develop novel chemical therapeutics for acute respiratory distress syndrome.     

Mapping a Noncovalent Protein–Peptide Interface by Top-Down FTICR Mass Spectrometry Using Electron Capture Dissociation

Noncovalent protein–ligand and protein–protein complexes are readily detected using electrospray ionization mass spectrometry (ESI MS). Furthermore, recent reports have demonstrated that careful use of electron capture dissociation (ECD) fragmentation allows covalent backbone bonds of protein complexes to be dissociated without disruption of noncovalent protein–ligand interactions. In this way the site of protein–ligand interfaces can be identified. To date, protein–ligand complexes, which have proven tractable to this technique, have been mediated by ionic electrostatic interactions, i.e., ion pair interactions or salt bridging. Here we extend this methodology by applying ECD to study a protein–peptide complex that contains no electrostatics interactions. We analyzed the complex between the 21 kDa p53-inhibitor protein anterior gradient-2 and its hexapeptide binding ligand (PTTIYY). ECD fragmentation of the 1:1 complex occurs with retention of protein–peptide binding and analysis of the resulting fragments allows the binding interface to be localized to a C-terminal region between residues 109 and 175. These finding are supported by a solution-phase competition assay, which implicates the region between residues 108 and 122 within AGR2 as the PTTIYY binding interface. Our study expands previous findings by demonstrating that top-down ECD mass spectrometry can be used to determine directly the sites of peptide–protein interfaces. This highlights the growing potential of using ECD and related top-down fragmentation techniques for interrogation of protein–protein interfaces.     

Bead-linked proteoliposomes: a reconstitution method for nmr analyses of membrane protein-ligand interactions

Structural information about the interactions between membrane proteins and their ligands provides insights into the membrane protein functions. A variety of surfactants have been used for structural analyses of membrane proteins, and in some cases, they yielded successful results. However, the use of surfactants frequently increases the conformational instability of membrane proteins and distorts their normal function. Here, we propose a new strategy of membrane protein reconstitution into lipid bilayers on affinity beads, which maintains the native conformation and function of the protein for NMR studies. The reconstituted membrane proteins are suitable for NMR analyses of interactions, by using the transferred cross-saturation method. The strategy was successfully applied to the interaction between a potassium ion channel, KcsA, and a pore-blocker, agitoxin2 (AgTx2). This strategy would be useful for analyzing the interactions between various membrane proteins and their ligands.     

Quantitative inhibitor fingerprinting of metalloproteases using small molecule microarrays

Current methods to identify interactions on small molecule microarrays (SMMs) introduce false positives that are difficult to dissect from the "real" binding events without tedious downstream re-evaluation. To specifically elucidate only activity-dependent ligand binding interactions, we have developed a technique that can be universally applied to present SMM systems. Our method makes use of a dual-color application strategy and is based on the simultaneous application of differentially treated samples. Overcoming the limitations of slide-to-slide variation, this method directly revealed activity-dependent interactions through a one-step application of protein samples on SMMs. Besides providing lead molecules for further development, the high-throughput screening results confer activity-dependent fingerprints for quantitative characterization and differentiation of proteins. The procedure was tested using a synthetic hydroxamate peptide library with 1400 discrete sequences permuted combinatorially across P1', P2', and P3' positions. Functional profiling across a panel of metalloproteases provided 44,800 datapoints within just eight SMM slides. These data were globally analyzed for activities, specificity, potency, and hierarchical clustering providing unique insights into inhibitor design and preference within this group of enzymes. Quantitative K(D) measurements performed on SMMs using one of the enzymes in the panel, Anthrax Lethal Factor, the toxic component of a notorious bioterror agent, unraveled several lead micromolar binders for further development. Overall, the effectiveness of the SMM platform is shown to be enhanced and extended using the strategy presented in this work.     

Analysis of beryllium to biomolecule binding using a metal specific fluorescent probe and competitive assay

Studying metal-biomolecule interactions is critical to the elucidation of the molecular basis of the biological functions and toxicity of metals. In the present study, a competitive fluorimetric approach has been developed to measure the apparent affinity of biomolecules for Be²⁺ by using a Be²⁺-specific fluorigenic probe (10-hydroxybenzo[h]quinoline-7-sulfonate, HBQS). Under physiological conditions, HBQS coordinates with Be²⁺ in a molar ratio of 1:1 and results in a fluorescence shift from 580 nm for HBQS to 480 nm for the Be-HBQS complex associated with significant fluorescence enhancement. When a beryllium ligand is present in the mixture of Be²⁺ and HBQS, the competition of ligand against HBQS for beryllium ion binding results in dissociation and thus a fluorescence decrease of the Be-HBQS complex. By titrating ligand and monitoring the dose-dependent decrease of Be-HBQS complex fluorescence at 480 nm, the apparent affinity between ligand and Be²⁺ can be derived. Applying this simple approach, the apparent affinities of various nucleotides and the iron-storage protein ferritin for beryllium ion have been determined. In particular, the apparent dissociation constant of Be²⁺ and adenosine 5′-triphosphate (ATP) was also validated by an electrospray ionization mass spectrometric (ESI-MS) method. The general applicability of the proposed competition assay was further demonstrated using FluoZin-1, a zinc fluorescent indicator, in a binding study for Zn²⁺ and bovine serum albumin. This newly developed competitive fluorimetric assay provides a sensitive, simple, and generic approach for affinity estimation of metal and biomolecule binding.     

Predicting in vivo protein peptide interactions with random phage display

Binding sites in protein complexes occasionally map to small peptides within one or more proteins. Random peptide display methods simulate binding interactions by providing all possible peptide combinations with an equal opportunity to bind a protein of interest. The natural substrates for the protein are typically known in advance. However, it is often the case that such substrates are identified as putative partner proteins by using in vivo methods such as yeast two hybrid screening. Unfortunately, such methods often produce lengthy datasets of protein sequences and offer little mechanistic insight into how such interactions might take place in vivo. Here, we review an approach that addresses this problem. First, sequence alignment tools identify and characterize blocks of conserved sequences among peptides recovered during random peptide display. Next, searching programs detect similar blocks of conserved sequences within naturally occurring proteins to predict partner proteins. Finally, the significance of an interaction is tested using site specific mutagenesis, binding competition or co-immunoprecipitation experiments. This strategy should become increasingly powerful with the growing popularity of interaction studies, sequencing projects and microarray analyses in modern biology.     

Structural analysis of bikunin glycosaminoglycan

The structure of an intact glycosaminoglycan (GAG) chain of the bikunin proteoglycan (PG) was analyzed using a combined top-down and bottom-up sequencing strategy. PGs are proteins with one or more linear, high-molecular weight, sulfated GAG polysaccharides O-linked to serine or threonine residues. GAGs are often responsible for the biological functions of PGs, and subtle variations in the GAG structure have pronounced physiological effects. Bikunin is a serine protease inhibitor found in human amniotic fluid, plasma, and urine. Bikunin is posttranslationally modified with a chondroitin sulfate (CS) chain, O-linked to a serine residue of the core protein. Recent studies have shown that the CS chain of bikunin plays an important role in the physiological and pathological functions of this PG. While no PG or GAG has yet been sequenced, bikunin, the least complex PG, offers a compelling target. Electrospray ionization Fourier transform-ion cyclotron resonance mass spectrometry (ESI FTICR-MS) permitted the identification of several major components in the GAG mixture having molecular masses in a range of 5505-7102 Da. This is the first report of a mass spectrum of an intact GAG component of a PG. FTICR-MS analysis of a size-uniform fraction of bikunin GAG mixture obtained by preparative polyacrylamide gel electrophoresis, allowed the determination of chain length and number of sulfo groups in the intact GAGs.     

A global metabolite profiling approach to identify protein-metabolite interactions

Understanding the biochemical functions of proteins is an important factor in elucidating their cellular and physiological functions. Due to the predominance of biopolymer interactions in biology, many methods have been designed to interrogate and identify biologically relevant interactions that proteins make to DNA, RNA, and other proteins. Complementary approaches that can elucidate binding interactions between proteins and small molecule metabolites will impact the understanding of protein-metabolite interactions and fill a need that is outside the scope of current methods. Here, we demonstrate the ability to identify natural protein-metabolite interactions from complex metabolite mixtures by combining a protein-mediated small molecule enrichment step with a global metabolite profiling platform.     

Analysis of transient membrane protein interactions by single-molecule diffusional mobility shift assay

Various repertoires of membrane protein interactions determine cellular responses to diverse environments around cells dynamically in space and time. Current assays, however, have limitations in unraveling these interactions in the physiological states in a living cell due to the lack of capability to probe the transient nature of these interactions on the crowded membrane. Here, we present a simple and robust assay that enables the investigation of transient protein interactions in living cells by using the single-molecule diffusional mobility shift assay (smDIMSA). Utilizing smDIMSA, we uncovered the interaction profile of EGFR with various membrane proteins and demonstrated the promiscuity of these interactions depending on the cancer cell line. The transient interaction profile obtained by smDIMSA will provide critical information to comprehend the crosstalk among various receptors on the plasma membrane.Subject terms: Fluorescence imaging, Super-resolution microscopy, Single-molecule biophysics     

Desmoplakin is important for proper cardiac cell-cell interactions

Normal cardiac function is maintained through dynamic interactions of cardiac cells with each other and with the extracellular matrix. These interactions are important for remodeling during cardiac growth and pathophysiological conditions. However, the precise mechanisms of these interactions remain unclear. In this study we examined the importance of desmoplakin (DSP) in cardiac cell-cell interactions. Cell-cell communication in the heart requires the formation and preservation of cell contacts by cell adhesion junctions called desmosome-like structures. A major protein component of this complex is DSP, which plays a role in linking the cytoskeletal network to the plasma membrane. Our laboratory previously generated a polyclonal antibody (1611) against the detergent soluble fraction of cardiac fibroblast plasma membrane. In attempting to define which proteins 1611 recognizes, we performed two-dimensional electrophoresis and identified DSP as one of the major proteins recognized by 1611. Immunoprecipitation studies demonstrated that 1611 was able to directly pulldown DSP. We also demonstrate that 1611 and anti-DSP antibodies co-localize in whole heart sections. Finally, using a three-dimensional in vitro cell-cell interaction assay, we demonstrate that 1611 can inhibit cell-cell interactions. These data indicate that DSP is an important protein for cell-cell interactions and affects a variety of cellular functions, including cytokine secretion.     

A Modular Synthesis of Teraryl‐Based α‐Helix Mimetics,Part 2: Synthesis of 5‐Pyridine Boronic Acid Pinacol Ester Building Blocks with Amino Acid Side Chains in 3‐Position

One of the most common protein–protein interactions (PPI) is the interaction of the α‐helix of one protein with the surface of the second one. Terphenylic scaffolds are bioinspired motifs in the inhibition of PPIs and have been identified as suitable α‐helix mimetics. One of the challenging aspects of this strategy is the poor solubility of terphenyls under physiological conditions. In the literature pyrrolopyrimidine‐, pyrimidine‐ or pyridazine‐based mimetics have been reported to show improved solubility. We present a new convergent strategy for the synthesis of linear pyridine‐type teraryls based on a phenylic core unit. A general approach for the synthesis of 3,5‐disubstituted pyridine‐based boronic acid pinacol esters with amino acid side chains in the 3‐position (representing Phe, Leu, Ile, Lys, Asp, Asn) is presented and exploits the functional group tolerance of the Knochel–Grignard reagents. The building blocks have been used in a convergent in situ two‐step synthesis of teraryl α‐helix mimetics.     

Template engineering through epitope recognition: a modular, biomimetic strategy for inorganic nanomaterial synthesis

Natural systems often utilize a single protein to perform multiple functions. Control over functional specificity is achieved through interactions with other proteins at well-defined epitope binding sites to form a variety of functional coassemblies. Inspired by the biological use of epitope recognition to perform diverse yet specific functions, we present a Template Engineering Through Epitope Recognition (TEThER) strategy that takes advantage of noncovalent, molecular recognition to achieve functional versatility from a single protein template. Engineered TEThER peptides span the biologic-inorganic interface and serve as molecular bridges between epitope binding sites on protein templates and selected inorganic materials in a localized, specific, and versatile manner. TEThER peptides are bifunctional sequences designed to noncovalently bind to the protein scaffold and to serve as nucleation sites for inorganic materials. Specifically, we functionalized identical clathrin protein cages through coassembly with designer TEThER peptides to achieve three diverse functions: the bioenabled synthesis of anatase titanium dioxide, cobalt oxide, and gold nanoparticles in aqueous solvents at room temperature and ambient pressure. Compared with previous demonstrations of site-specific inorganic biotemplating, the TEThER strategy relies solely on defined, noncovalent interactions without requiring any genetic or chemical modifications to the biomacromolecular template. Therefore, this general strategy represents a mix-and-match, biomimetic approach that can be broadly applied to other protein templates to achieve versatile and site-specific heteroassemblies of nanoscale biologic-inorganic complexes.     

Potential inhibitors of chemokine function: Analysis of noncovalent complexes of cc chemokine and small polyanionic molecules by ESI FT-ICR mass spectrometry

Chemokines play a critical role in inducing chemotaxis, extravasation, and activation of leukocytes both in routine immunosurveillance and autoimmune diseases. Traditionally, to disrupt chemokine function, strategies have focused on blockage of its interaction with the receptor. Recently, it has been demonstrated that binding to glycosaminoglycans (GAGs) is also required for the in vivo activity of many chemokines. Thus, interference with the GAG-binding of chemokines may offer an alternative, valid, anti-inflammatory strategy. However, the potential of using small polyanions to inhibit the interactions between chemokines and cell surface GAGs has not been fully explored. In this study, a mass spectrometry based filtration trapping assay was utilized to study the interactions between two CCR 2 ligands (MCP-1/CCL2 and MCP-3/CCL7) and a series of low molecular weight, polyanionic molecules. Findings were confirmed by using a hydrophobic trapping assay. The results indicated that Arixtra (fondaparinux sodium), sucrose octasulfate, and suramin were specific binders of the chemokines, while cyclodextrin sulfate, although the most highly sulfated molecule among the ones investigated, showed no binding. The binding stoichiometry of the small molecule ligand was determined from the measured molecular weight of the noncovalent complex. Furthermore, the dissociation constant between MCP-3 and Arixtra was determined by using electrospray ionization Fourier transform ion cyclotron resonance (ESI FT-ICR) mass spectrometry, which compared favorably with the result of the isothermal titration calorimetry (ITC) assay. The relative binding affinity of these ligands to MCP-3 was also determined using a competitive filtration trapping assay.     

基于镜像酶正交酶切的蛋白质复合物规模化精准分析新方法

蛋白质主要以复合物的形式参与各项生命活动.化学交联质谱(CXMS)技术作为近年来新兴的蛋白质复合物解析技术,不仅可实现蛋白质复合物规模化解析,而且普遍适用于任意相对分子质量和纯度的蛋白质复合物样品,因此已成为X-射线晶体衍射技术、冷冻电镜技术等蛋白质复合物解析经典技术的重要补充.目前,CXMS主要采用胰蛋白酶将交联后的...     

Sequence dependence in base flipping: experimental and computational studies

Base flipping is the movement of a DNA base from an intrahelical, base-stacked position to an extrahelical, solvent-exposed position. As there are favorable interactions for an intrahelical base, both hydrogen bonding and base stacking, base flipping is expected to be energetically prohibitive for an undamaged DNA duplex. For damaged DNA bases, however, the energetic cost of base flipping may be considerably lower. Using a selective, non-covalent assay for base flipping, the sequence dependence of base flipping in DNA sequences containing an abasic site has been studied. The dissociation constants of the zinc-cyclen complex to small molecules and single strands of DNA as well as the equilibrium constants for base flipping have been determined for these sequences. Molecular dynamics simulations of the zinc-cyclen complex bound to both single- and double-stranded DNA have been performed in an attempt to rationalize the differences in the dissociation constants obtained for the two systems. The results are compared to previous studies of base flipping in DNA containing an abasic site.     

Deep_CNN_LSTM_GO: Protein function prediction from amino-acid sequences

Protein amino acid sequences can be used to determine the functions of the protein. However, determining the function of a single protein requires many resources and a tremendous amount of time. Computational Intelligence methods such as Deep learning have been shown to predict the proteins' functions. This paper proposes a hybrid deep neural network model to predict an unknown protein's functions from sequences. The proposed model is named Deep_CNN_LSTM_GO. Deep_CNN_LSTM_GO is an Integration between Convolutional Neural network (CNN) and Long Short-Term Memory (LSTM) Neural Network to learn features from amino acid sequences and outputs the three different Gene Ontology (GO). The gene ontology represents the protein functions in the three sub-ontologies: Molecular Functions (MF), Biological Process (BP), and Cellular Component (CC). The proposed model has been trained and tested using UniProt-SwissProt's dataset. Another test has been done using Computational Assessment of Function Annotation (CAFA) on the three sub-ontologies. The proposed model outperforms different methods proposed in the field with better performance using three different evaluation metrics (Fmax, Smin, and AUPR) in the three sub-ontologies (MF, BP, CC).     

Computational analyses of high-throughput protein-protein interaction data

Protein-protein interactions play important roles in nearly all events that take place in a cell. High-throughput experimental techniques enable the study of protein-protein interactions at the proteome scale through systematic identification of physical interactions among all proteins in an organism. High-throughput protein-protein interaction data, with ever-increasing volume, are becoming the foundation for new biological discoveries. A great challenge to bioinformatics is to manage, analyze, and model these data. In this review, we describe several databases that store, query, and visualize protein-protein interaction data. Comparison between experimental techniques shows that each high-throughput technique such as yeast two-hybrid assay or protein complex identification through mass spectrometry has its limitations in detecting certain types of interactions and they are complementary to each other. In silico methods using protein/DNA sequences, domain and structure information to predict protein-protein interaction can expand the scope of experimental data and increase the confidence of certain protein-protein interaction pairs. Protein-protein interaction data correlate with other types of data, including protein function, subcellular location, and gene expression profile. Highly connected proteins are more likely to be essential based on the analyses of the global architecture of large-scale interaction network in yeast. Use of protein-protein interaction networks, preferably in conjunction with other types of data, allows assignment of cellular functions to novel proteins and derivation of new biological pathways. As demonstrated in our study on the yeast signal transduction pathway for amino acid transport, integration of high-throughput data with traditional biology resources can transform the protein-protein interaction data from noisy information into knowledge of cellular mechanisms.