Protein Recognition Research Articles

Recognition of polymorphic Csd proteins determines sex in the honeybee.

Sex in honeybees, Apis mellifera, is genetically determined by heterozygous versus homo/hemizygous genotypes involving numerous alleles at the single complementary sex determination locus. The molecular mechanism of sex determination is however unknown because there are more than 4950 known possible allele combinations, but only two sexes in the species. We show how protein variants expressed from complementary sex determiner (csd) gene determine sex. In females, the amino acid differences between Csd variants at the potential-specifying domain (PSD) direct the selection of a conserved coiled-coil domain for binding and protein complexation. This recognition mechanism activates Csd proteins and, thus, the female pathway. In males, the absence of polymorphisms establishes other binding elements at PSD for binding and complexation of identical Csd proteins. This second recognition mechanism inactivates Csd proteins and commits male development via default pathway. Our results demonstrate that the recognition of different versus identical variants of a single protein is a mechanism to determine sex.

Distinct ADP-ribosylation factor-GTP exchange factors govern the opposite polarity of 2 receptor kinases.

Polarity of plasma membrane proteins is essential for cell morphogenesis and control of cell division and, thus, influences organ and whole plant development. In Arabidopsis (Arabidopsis thaliana) root endodermal cells, 2 transmembrane kinases, INFLORESCENCE AND ROOT APICES RECEPTOR KINASE (IRK) and KINASE ON THE INSIDE (KOIN), accumulate at opposite lateral domains. Their polarization is tightly linked to their activities regulating cell division and ground tissue patterning. The polarization of IRK and KOIN relies solely on the secretion of newly synthesized protein. However, the secretion machinery by which their opposite, lateral polarity is achieved remains largely unknown. Here, we show that different sets of ADP-ribosylation factor (ARF)-guanine-nucleotide exchange factors (ARF-GEFs) mediate their secretion. ARF-GEF GNOM-like-1 (GNL1) regulates KOIN secretion to the inner polar domain, thereby directing KOIN sorting early in the secretion pathway. For IRK, combined chemical and genetic analyses showed that the ARG-GEF GNL1, GNOM, and the BREFELDIN A-INHIBITED-GUANINE NUCLEOTIDE-EXCHANGE FACTORs 1 to 4 (BIG1-BIG4) collectively regulate its polar secretion. The ARF-GEF-dependent mechanisms guiding IRK or KOIN lateral polarity were active across different root cell types and functioned regardless of the protein's inner/outer polarity in those cells. Therefore, we propose that specific polar trafficking of IRK and KOIN occurs via distinct mechanisms that are not constrained by cell identity or polar axis and likely rely on individual protein recognition.

Unnatural Amino Acid Engineering for Intracellular Delivery of Protein Therapeutics.

Protein drugs are a critically important therapeutic modality due to the sophisticated binding recognition, catalytic properties, and disease relevance of proteins. There is a clear need for new strategies able to improve pharmacokinetics, bioavailability, and/or intracellular delivery of therapeutic proteins, as stability limitations have significantly hindered clinical advancement, and most proteins are membrane impermeable. Bioconjugation strategies able to site-specifically modify proteins with cell binding, and other ligands offer a particularly valuable approach to facilitate protein delivery due to the importance of ligand presentation on protein bioactivity and cellular uptake. We explored unnatural amino acid (UAA) incorporation as a novel strategy to tunably incorporate clustered cell-binding ligands in fluorescent proteins and suicide enzymes, resulting in substantial increases in cell-specific uptake and targeted cell-killing activity. These approaches offer a valuable and versatile method to modify a variety of proteins and enable improved clinical potential.

Dynamic Evolution of Bacterial Ligand Recognition by Formyl Peptide Receptors.

The detection of invasive pathogens is critical for host immune defense. Cell surface receptors play a key role in the recognition of diverse microbe-associated molecules, triggering leukocyte recruitment, phagocytosis, release of antimicrobial compounds, and cytokine production. The intense evolutionary forces acting on innate immune receptor genes have contributed to their rapid diversification across plants and animals. However, the functional consequences of immune receptor divergence are often unclear. Formyl peptide receptors (FPRs) comprise a family of animal G protein-coupled receptors which are activated in response to a variety of ligands including formylated bacterial peptides, pathogen virulence factors, and host-derived antimicrobial peptides. FPR activation in turn promotes inflammatory signaling and leukocyte migration to sites of infection. Here we investigate patterns of gene loss, diversification, and ligand recognition among FPRs in primates and carnivores. We find that FPR1, which plays a critical role in innate immune defense in humans, has been lost in New World primates. Amino acid variation in FPR1 and FPR2 among primates and carnivores is consistent with a history of repeated positive selection acting on extracellular domains involved in ligand recognition. To assess the consequences of FPR divergence on bacterial ligand interactions, we measured binding between primate FPRs and the FPR agonist Staphylococcus aureus enterotoxin B, as well as S. aureus FLIPr-like, an FPR inhibitor. We found that few rapidly evolving sites in primate FPRs are sufficient to modulate recognition of bacterial proteins, demonstrating how natural selection may serve to tune FPR activation in response to diverse microbial ligands.

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems.

Molecular differentiation by supramolecular sensors is typically achieved through sensor arrays, relying on the pattern recognition responses of large panels of isolated sensing elements. Here we report a new one-pot systems chemistry approach to differential sensing in biological solutions. We constructed an adaptive network of three cross-assembling sensor elements with diverse analyte-binding and photophysical properties. This robust sensing approach exploits complex interconnected sensor-sensor and sensor-analyte equilibria, producing emergent supramolecular and photophysical responses unique to each analyte. We characterize the basic mechanisms by which an adaptive network responds to analytes. The inherently data-rich responses of an adaptive network discriminate among very closely related proteins and protein mixtures without relying on designed protein recognition elements. We show that a single adaptive sensing solution provides better analyte discrimination using fewer response observations than a sensor array built from the same components. We also show the network's ability to adapt and respond to changing biological solutions over time.

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

AbstractMolecular differentiation by supramolecular sensors is typically achieved through sensor arrays, relying on the pattern recognition responses of large panels of isolated sensing elements. Here we report a new one‐pot systems chemistry approach to differential sensing in biological solutions. We constructed an adaptive network of three cross‐assembling sensor elements with diverse analyte‐binding and photophysical properties. This robust sensing approach exploits complex interconnected sensor‐sensor and sensor‐analyte equilibria, producing emergent supramolecular and photophysical responses unique to each analyte. We characterize the basic mechanisms by which an adaptive network responds to analytes. The inherently data‐rich responses of an adaptive network discriminate among very closely related proteins and protein mixtures without relying on designed protein recognition elements. We show that a single adaptive sensing solution provides better analyte discrimination using fewer response observations than a sensor array built from the same components. We also show the network's ability to adapt and respond to changing biological solutions over time.

Wavelength multiplexing infrared metasurfaces for protein recognition and trace detection

Abstract Infrared metasurfaces have exhibited exceptional optical properties that differ from naturally occurring metallic and dielectric nanostructure, enabling non-destructive and label-free sensing in a broadband region. However, implementing wavelength multiplexing sensors in broadband infrared has faced significant challenges. These challenges arise from the difficulty in efficiently exciting high Q resonances at specific wavelengths and the inability to individually tune each resonance. Herein, we present a dual resonant metasurface that utilizes a metal–dielectric–metal plasmonic grating and a dielectric–metal channel. By adjusting the vertical and horizontal structures of metasurface, we can independently modify the spectrum of the metasurface in the near-infrared and mid-infrared regions. This broadband infrared metasurface exhibits robust spectral regulation, enabling a polarization-dependent strategy for the dual-resonance. It offers a competitive advantage over traditional metallic nanostructure in refractive index sensing at the second near-infrared window and ultrasensitive vibrational spectroscopy in mid-infrared. Specifically, our proposed metasurface achieves protein concentration sensing and dynamic monitoring of protein concentration in the infrared two-zone. Additionally, it enhances the mid-infrared absorption of amide II with a high Q resonance. The metasurface which combines wavelength multiplexing and polarization dependent switch for protein recognition and trace detection, presents a novel approach for developing high-performance sensors and Integrated photonics sensors in the broadband infrared region.

Analysing potent biomarkers along phytochemicals for breast cancer therapy: an in silico approach

PurposeThis research focused on the identification of herbal compounds as potential anti-cancer drugs, especially for breast cancer, that involved the recognition of Notch downstream targets NOTCH proteins (1–4) specifically expressed in breast tumours as biomarkers for prognosis, along with P53 tumour antigens, that were used as comparisons to check the sensitivity of the herbal bio-compounds.MethodsAfter investigating phytochemical candidates, we employed an approach for computer-aided drug design and analysis to find strong breast cancer inhibitors. The present study utilized in silico analyses and protein docking techniques to characterize and rank selected bio-compounds for their efficiency in oncogenic inhibition for use in precise carcinomic cell growth control.ResultsSeveral of the identified phytocompounds found in herbs followed Lipinski’s Rule of Five and could be further investigated as potential medicinal molecules. Based on the Vina score obtained after the docking process, the active compound Epigallocatechin gallate in green tea with NOTCH (1–4) and P53 proteins showed promising results for future drug repurposing. The stiffness and binding stability of green tea pharmacological complexes were further elucidated by the molecular dynamic simulations carried out for the highest scoring phytochemical ligand complex.ConclusionThe target-ligand complex of green tea active compound Epigallocatechin gallate with NOTCH (1–4) had the potential to become potent anti-breast cancer therapeutic candidates following further research involving wet-lab experiments.

Site-specific incorporation of reduction-controlled guest amino acids into proteins for cucurbituril recognition

Protein recognition using host-guest recognition approach is of great interest but has been limited mainly to the protein N-terminal residues. Here, we site-specific incorporated two novel non-canonical amino acids containing supramolecular guest motifs into protein via an expanded genetic code. Through Staudinger reduction reactions, the encoded unnatural residues on protein becoming activated and can be specifically recognized by cucurbit[7]uril (CB[7]) and cucurbit[8]uril (CB[8]). We demonstrated that enzyme containing guest amino acid incorporated near the active site can be reversibly regulated by CB[7] recognition, and CB[8] recognition induces protein dimerization. These amino acids will make useful addition to the supramolecular toolbox for protein targeting using molecular recognition approaches.

Investigation of differences in the protein transport capability of homochiral nanochannels

Chiral recognition plays a crucial role in the normal functioning of biological systems. The recognition of proteins in chiral environments underpins many fundamental life processes. Taking advantage of the distinct interactions between different proteins and chiral environments, this study presents the design of homochiral metal–organic framework (MOF)/nanochannels based membrane separator, enabling highly selective and high-throughput protein separation. The chiral separation membrane was fabricated by employing TiO2 nanochannel membrane (TM) as the supporting membrane and Ti ion source. Using terephthalic acid (BDC) and d/l-phenylalanine (DP/LP) as ligands, a layered TiMOF (MIL-125(Ti) used in this study) incorporating chiral selector molecules (named as DP/M and LP/M) were synthesized in situ within the TiO2 nanochannels. The bovine serum albumin (BSA) adsorption capacity of DP/M decorated TM was demonstrated to be 2.8 times higher than that of LP/M decorated TM, and was found to be related to the content of the chiral selector DP in the separation membrane. Furthermore, different recognition abilities by the chiral channels were observed for proteins with different isoelectric points. Based on a comprehensive exploration of the variations in the interaction forces between protein and chiral selector molecules, a nanoscale chromatography column-like separation model was proposed. The chiral separation membranes designed in this study provide a new platform for understanding the interactions between chiral compounds and proteins, and open up new avenues for fabricating chiral bio-interface materials, elucidating the role of chiral recognition in biological systems, and developing novel biomaterials and devices.

Recognition of immune reactive proteins as a potential multiepitope vaccine candidate of Taenia solium cysticerci through proteomic approach.

Metacestode, the larva of Taenia solium, is the causative agent for neurocysticercosis (NCC), which causes epilepsy. The unavailability of a vaccine against human NCC is a major cause for its widespread prevalence across the globe. Therefore, the development of a reliable vaccine against NCC is the need of the hour. Employing a combination of proteomics and immunoinformatics, we endeavored to formulate a vaccine candidate. The immune reactive cyst fluid antigensof T. solium were identified by immune-blotting two-dimensional gels with NCC patient's sera, followed by Matrix-assisted laser desorption-ionizationanalysis. We performed a detailed proteomic study of these immune reactive proteins by utilizing immune-informatics tools, identified the nontoxic, nonallergic, B-cell epitopes, and collected epitopes with the least sequence homology with human and other Taenia species. These epitopes were joined through linkers to construct a multiepitope vaccine. Different physiochemical parameters such as molecular weight (23.82 kDa), instability (39.91), and aliphatic index (49.61) were calculated to ensure the stability of the linked peptides vaccine. The vaccine demonstrated stable interactions with different immune receptors like Toll-like receptor 4and IgG confirming that it will effectively stimulate the host immune response. We anticipate that our designed B-cell linear epitope-based vaccine will show promising results in in vitro and in vivo assays. This study provides a platform that would be useful to develop other suitable vaccine candidates to prevent helminthic neglected tropical diseases in near future.

Protein-DNA recognition mechanisms and specificity.

The accumulated knowledge about the structure of protein-DNA complexes allowed us to understand the mechanisms of protein-DNA recognition and searching for a specific site on DNA. Obviously, the mechanism of specific DNA recognition by a protein must satisfy two requirements. First, the probability of incorrect binding should be very small. Second, the time to find the "correct" binding site should not be too long. If we assume that protein recognition of a precise site on DNA occurs at some distance from DNA and calculate global minima, we can avoid local minima at short distances. The only long-range interaction is the interaction of charges. The location of charges on DNA in three-dimensional space depends on the local conformation of DNA and thus reflects the DNA sequence and sets the spatial pattern for recognition. Various factors such as counter ion concentration, ionic strength, and pH can affect protein recognition of DNA. Nowadays, the theory of long-range interactions makes it possible to calculate the best mutual spatial arrangement of protein and DNA molecules by charged groups and avoid misplaced binding.

Facile synthesis of flower-like sandwich-structured molecularly imprinted polymers for efficient recognition of target protein from egg white.

In this work, a facile method for synthesis of flower-like sandwich-structured molecularly imprinted polymers (NiO@PDA/MIPs) was proposed for protein recognition. Polydopamine modified flower-like NiO was used as substrate to immobilize the target protein (ovalbumin, OVA), and dopamine was utilized as functional monomer to form the imprinted layer. The whole preparation process was conducted in aqueous solution at room temperature. The key preparation conditions were studied systematically. Owing to the large surface-to-volume of the flower-like structure and the multifunctional groups on the polydopamine layer, the NiO@PDA/MIPs showed large binding capacity (143.2mg/g), efficient adsorption kinetics (60min) and excellent selectivity toward OVA. Meanwhile, the NiO@PDA/MIPs possessed satisfactory stability and reusability. Finally, successful capture of OVA from egg white suggested its potential value in practical applications.

Scutellarin Mediates Cytochrome P450 3A4 and 2C19 Expression via Pregnane X Receptor and Constitutive Androstane Receptor.

Breviscapine is a flavonoid extracted from Erigeron breviscapus (Vant.) Hand.-Mazz., and mainly contains scutellarin. Nuclear receptors play important roles in regulating transporter and drug metabolic enzymes. To investigate the regulatory effects of scutellarin on CYP3A4 and 2C19 in HepG2 and Caco-2 cells based on nuclear receptors PXR and CAR. The proteins and mRNA levels of CYP3A4 and CYP2C19 treated with scutellarin were detected by Western Blot and RT-qPCR. Using assays of the dual-luciferase reporter, promoter sequences containing hPXR and hCAR protein recognition and binding regulatory elements CYP3A4 and CYP2C19 were inserted upstream of the reporter gene, and the expression vector and the reporter vector were cotransfected into HepG2 and Caco-2 cells. Scutellarin inhibited mRNA of CYP3A4 and PXR, and promoted mRNA expression of CYP2C19 and CAR in RT-qPCR results. Western-blot results showed scutellarin inhibited the expression of CYP3A4 and promoted the expression of CYP2C19. The dual-luciferase reporter genes showed that scutellarin enhanced the expression level of CYP2C19, and when its concentration was 40 and 80μmol/L, CYP3A4 was significantly increased. Scutellarin down-regulates CYP3A4 through PXR, and its mechanism may work by up-regulating CAR, binding to PXR to inhibit PXR-mediated expression of CYP3A4. Scutellarin up-regulates CYP2C19 through CAR.

DBPMod: a supervised learning model for computational recognition of DNA-binding proteins in model organisms.

DNA-binding proteins (DBPs) play critical roles in many biological processes, including gene expression, DNA replication, recombination and repair. Understanding the molecular mechanisms underlying these processes depends on the precise identification of DBPs. In recent times, several computational methods have been developed to identify DBPs. However, because of the generic nature of the models, these models are unable to identify species-specific DBPs with higher accuracy. Therefore, a species-specific computational model is needed to predict species-specific DBPs. In this paper, we introduce the computational DBPMod method, which makes use of a machine learning approach to identify species-specific DBPs. For prediction, both shallow learning algorithms and deep learning models were used, with shallow learning models achieving higher accuracy. Additionally, the evolutionary features outperformed sequence-derived features in terms of accuracy. Five model organisms, including Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli, Homo sapiens and Mus musculus, were used to assess the performance of DBPMod. Five-fold cross-validation and independent test set analyses were used to evaluate the prediction accuracy in terms of area under receiver operating characteristic curve (auROC) and area under precision-recall curve (auPRC), which was found to be ~89-92% and ~89-95%, respectively. The comparative results demonstrate that the DBPMod outperforms 12 current state-of-the-art computational approaches in identifying the DBPs for all five model organisms. We further developed the web server of DBPMod to make it easier for researchers to detect DBPs and is publicly available at https://iasri-sg.icar.gov.in/dbpmod/. DBPMod is expected to be an invaluable tool for discovering DBPs, supplementing the current experimental and computational methods.

Analyzing Fcγ-Receptor Interactions on Monocytes with the Proximity Ligation Assay (PLA).

Proximity ligation assays (PLA) enable the detection and characterization of protein interactions independent of protein abundance or genetic modifications. This technique exploits both antibody and DNA-binding features, providing high selectivity and sensitivity for protein recognition and visualization of single-protein molecules with high spatial accuracy. Here, we describe the general procedure for a direct PLA on splenic monocytes to analyze FcγRIIb homodimerization. However, this method can be applied to other cells and receptors of interest.

Efficient Selective Adsorption of SARS-CoV-2 via the Recognition of Spike Proteins Using an Affinity Spongy Monolith.

Since the outbreak of COVID-19, SARS-CoV-2, the infection has been spreading to date. The rate of false-negative result on a polymerase chain reaction (PCR) test considered the gold standard is roughly 20%. Therefore, its accuracy poses a question as well as needs improvement in the test. This study reports fabrication of a substrate of an anti-spike protein (AS)-immobilized porous material having selective adsorption toward a spike protein protruding from the surface of SARS-CoV-2. We have employed an organic polymer substrate called spongy monolith (SPM). The SPM has through-pores of about 10 μm and is adequate for flowing liquid containing virus particles. It also involves an epoxy group on the surface, enabling arbitrary proteins such as antibodies to immobilize. When antibodies of the spike protein toward receptor binding domain were immobilized, selective adsorption of the spike protein was observed. At the same time, when mixed analytes of spike proteins, lysozymes and amylases, were flowed into an AS-SPM, selective adsorption toward the spike proteins was observed. Then, SARS-CoV-2 was flowed into the BSA-SPM or AS-SPM, amounts of SARS-CoV-2 adsorption toward the AS-SPM were much larger compared to the ones toward the BSA-SPM. Furthermore, rotavirus was not adsorbed to the AS-SPM at all. These results show that the AS-SPM recognizes selectively the spike proteins of SARS-CoV-2 and may be possible applications for the purification and concentration of SARS-CoV-2.

New stochastic devices for simultaneous analysis of mismatch repair proteins and KRAS in biological samples

Two stochastic microsensors based on the immobilization of inulins: inutec and frutafit in a paste obtained from a graphene decorated with nitrogen (10.8 %), and boron (2.6 %), and paraffin oil (IR purity) were designed, characterized and validated for the molecular recognition and analysis of mismatch repair proteins like MLH1, MSH2, MSH6, PMS2, and of KRAS in biological samples such as: whole blood, urine, saliva, and tumoral tissues. The sensor based on inutec exhibited the largest working concentration range (10 decades of concentration) and the lowest limit of determination (0.32fg mL−1) when used for the assay of MLH1, and the wider working concentration range (8 decades of concentration), and the lowest limit of determination (2.30fg mL−1) when used for the assay of MSH6. The sensor based on frutafit exhibited the largest working concentration range (10 decades of concentration) when used for the determination of KRAS, and the wider working concentration range (5 decades of concentration), and the lowest limit of determination (1.00fg mL−1) when used for the assay of PMS2. No influence of the modifier (inutec and frutafit) was recorded on the linear concentration range (10 decades of concentration), and on the limit of determination (1.00 fg mL−1) for the assay of MSH2. The recoveries of MLH1, MSH2, MSH6, PMS2, and of KRAS in whole blood, urine, saliva, and tumoral tissues were higher than 98.00 with RSD (%) values lower than 0.10 %.

C-terminal sequence stability profiling in Saccharomyces cerevisiae reveals protective protein quality control pathways

Protein quality control (PQC) mechanisms are essential for degradation of misfolded or dysfunctional proteins. An essential part of protein homeostasis is recognition of defective proteins by PQC components and their elimination by the ubiquitin-proteasome system, often concentrating on protein termini as indicators of protein integrity. Changes in amino acid composition of C-terminal ends arise through protein disintegration, alternative splicing, or during the translation step of protein synthesis from premature termination or translational stop-codon read-through. We characterized reporter protein stability using light-controlled exposure of the random C-terminal peptide collection (CtPC) in budding yeast revealing stabilizing and destabilizing features of amino acids at positions-5 to-1 of the C terminus. The (de)stabilization properties of CtPC-degrons depend on amino acid identity, position, as well as composition of the C-terminal sequence and are transferable. Evolutionary pressure toward stable proteins in yeast is evidenced by amino acid residues under-represented in cytosolic and nuclear proteins at corresponding C-terminal positions, but over-represented in unstable CtPC-degrons, and vice versa. Furthermore, analysis of translational stop-codon read-through peptides suggested that such extended proteins have destabilizing C termini. PQC pathways targeting CtPC-degrons involved the ubiquitin-protein ligase Doa10 and the cullin-RING E3 ligase SCFDas1 (Skp1-Cullin-F-box protein). Overall, our data suggest a proteome protection mechanism that targets proteins with unnatural C termini by recognizing a surprisingly large number of C-terminal sequence variants.

Mechanisms of substrate processing during ER-associated protein degradation.

Maintaining proteome integrity is essential for long-term viability of all organisms and is overseen by intrinsic quality control mechanisms. The secretory pathway of eukaryotes poses a challenge for such quality assurance as proteins destined for secretion enter the endoplasmic reticulum (ER) and become spatially segregated from the cytosolic machinery responsible for disposal of aberrant (misfolded or otherwise damaged) or superfluous polypeptides. The elegant solution provided by evolution is ER-membrane-bound ubiquitylation machinery that recognizes misfolded or surplus proteins or by-products of protein biosynthesis in the ER and delivers them to 26S proteasomes for degradation. ER-associated protein degradation (ERAD) collectively describes this specialized arm of protein quality control via the ubiquitin-proteasome system. But, instead of providing a single strategy to remove defective or unwanted proteins, ERAD represents a collection of independent processes that exhibit distinct yet overlapping selectivity for a wide range of substrates. Not surprisingly, ER-membrane-embedded ubiquitin ligases (ER-E3s) act as central hubs for each of these separate ERAD disposal routes. In these processes, ER-E3s cooperate with a plethora of specialized factors, coordinating recognition, transport and ubiquitylation of undesirable secretory, membrane and cytoplasmic proteins. In this Review, we focus on substrate processing during ERAD, highlighting common threads as well as differences between the many routes via ERAD.