Protein-peptide interactions

AAontology: An ontology of amino acid scales for interpretable machine learning

Amino acid scales are crucial for protein prediction tasks, many of them being curated in the AAindex database. Despite various clustering attempts to organize them and to better understand their relationships, these approaches lack the fine-grained classification necessary for satisfactory interpretability in many protein prediction problems. To address this issue, we developed AAontology-a two-level classification for 586 amino acid scales (mainly from AAindex) together with an in-depth analysis of their relations-using bag-of-word-based classification, clustering, and manual refinement over multiple iterations. AAontology organizes physicochemical scales into 8 categories and 67 subcategories, enhancing the interpretability of scale-based machine learning methods in protein bioinformatics. Thereby it enables researchers to gain a deeper biological insight. We anticipate that AAontology will be a building block to link amino acid properties with protein function and dysfunctions as well as aid informed decision-making in mutation analysis or protein drug design.

A deep attention model for wide-genome protein-peptide binding affinity prediction at a sequence level

Peptides are pivotal in numerous biological activities by engaging in up to 40 % of protein-protein interactions in many cellular processes. Due to their exceptional specificity and effectiveness, peptides have emerged as promising candidates for drug design. However, accurately predicting protein-peptide binding affinity remains a challenging. Aiming at the problem, we develop a prediction model PepPAP based on convolutional neural network and multi-head attention, which relies solely on sequence features. These features include physicochemical properties, intrinsic disorder, sequence encoding, and especially interface propensity which is extracted from 16,689 non-redundant protein-peptide complexes. Notably, the adopted regression stratification cross-validation scheme proposed in our previous work is beneficial to improve the prediction for the cases with extreme binding affinity values. On three benchmark test datasets: T100, a series of peptides targeting to PDZ domain and CXCR4, PepPAP shows excellent performance, outperforming the existing methods and demonstrating its good generalization ability. Furthermore, PepPAP has good results in binary interaction prediction, and the analysis of the feature space distribution visualization highlights PepPAP's effectiveness. To the best of our knowledge, PepPAP is the first sequence-based deep attention model for wide-genome protein-peptide binding affinity prediction, and holds the potential to offer valuable insights for the peptide-based drug design.

Insights into structural vaccinology harnessed for universal coronavirus vaccine development

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

Peptide-Based Flavivirus Biosensors: From Cell Structure to Virological and Serological Detection Methods

In tropical and developing countries, mosquito-borne diseases by flaviviruses pose a serious threat to public health. Early detection is critical for preventing their spread, but conventional methods are time-consuming and require skilled technicians. Biosensors have been developed to address this issue, but cross-reactivity with other flaviviruses remains a challenge. Peptides are essentially biomaterials used in diagnostics that allow virological and serological techniques to identify flavivirus selectively. This biomaterial originated as a small protein consisting of two to 50 amino acid chains. They offer flexibility in chemical modification and can be easily synthesized and applied to living cells in the engineering process. Peptides could potentially be developed as robust, low-cost, sensitive, and selective receptors for detecting flaviviruses. However, modification and selection of the receptor agents are crucial to determine the effectiveness of binding between the targets and the receptors. This paper addresses two potential peptide nucleic acids (PNAs) and affinity peptides that can detect flavivirus from another target-based biosensor as well as the potential peptide behaviors of flaviviruses. The PNAs detect flaviviruses based on the nucleotide base sequence of the target's virological profile via Watson-Crick base pairing, while the affinity peptides sense the epitope or immunological profile of the targets. Recent developments in the functionalization of peptides for flavivirus biosensors are explored in this Review by division into electrochemical, optical, and other detection methods.

Network analysis of the proteome and peptidome sheds light on human milk as a biological system

Proteins and peptides found in human milk have bioactive potential to benefit the newborn and support healthy development. Research has been carried out on the health benefits of proteins and peptides, but many questions still need to be answered about the nature of these components, how they are formed, and how they end up in the milk. This study explored and elucidated the complexity of the human milk proteome and peptidome. Proteins and peptides were analyzed with non-targeted nanoLC-Orbitrap-MS/MS in a selection of 297 milk samples from the CHILD Cohort Study. Protein and peptide abundances were determined, and a network was inferred using Gaussian graphical modeling (GGM), allowing an investigation of direct associations. This study showed that signatures of (1) specific mechanisms of transport of different groups of proteins, (2) proteolytic degradation by proteases and aminopeptidases, and (3) coagulation and complement activation are present in human milk. These results show the value of an integrated approach in evaluating large-scale omics data sets and provide valuable information for studies that aim to associate protein or peptide profiles from biofluids such as milk with specific physiological characteristics.

An In Silico Design of Peptides Targeting the S1/S2 Cleavage Site of the SARS-CoV-2 Spike Protein

SARS-CoV-2, responsible for the COVID-19 pandemic, invades host cells via its spike protein, which includes critical binding regions, such as the receptor-binding domain (RBD), the S1/S2 cleavage site, the S2 cleavage site, and heptad-repeat (HR) sections. Peptides targeting the RBD and HR1 inhibit binding to host ACE2 receptors and the formation of the fusion core. Other peptides target proteases, such as TMPRSS2 and cathepsin L, to prevent the cleavage of the S protein. However, research has largely ignored peptides targeting the S1/S2 cleavage site. In this study, bioinformatics was used to investigate the binding of the S1/S2 cleavage site to host proteases, including furin, trypsin, TMPRSS2, matriptase, cathepsin B, and cathepsin L. Peptides targeting the S1/S2 site were designed by identifying binding residues. Peptides were docked to the S1/S2 site using HADDOCK (High-Ambiguity-Driven protein-protein DOCKing). Nine peptides with the lowest HADDOCK scores and strong binding affinities were selected, which was followed by molecular dynamics simulations (MDSs) for further investigation. Among these peptides, BR582 and BR599 stand out. They exhibited relatively high interaction energies with the S protein at -1004.769 ± 21.2 kJ/mol and -1040.334 ± 24.1 kJ/mol, respectively. It is noteworthy that the binding of these peptides to the S protein remained stable during the MDSs. In conclusion, this research highlights the potential of peptides targeting the S1/S2 cleavage site as a means to prevent SARS-CoV-2 from entering cells, and contributes to the development of therapeutic interventions against COVID-19.

Modulating Secondary Structure Motifs Through Photo-Labile Peptide Staples

Peptide-protein interactions (PPIs) are facilitated by the well-defined three-dimensional structure of bioactive peptides, interesting compounds for the development of new therapeutic agents. Their secondary structure and thus their propensity to engage in PPIs can be influenced by the introduction of peptide staples on the side chains. In particular, light-controlled staples based on azobenzene photoswitches and their structural influence on helical peptides have been studied extensively. In contrast, photolabile staples bearing photocages as a structural key motif, have mainly been used to block supramolecular interactions. Their influence on the secondary structure of the target peptide is under-investigated. Thus, in this study we use a combination of spectroscopic techniques and in silico simulations to systematically study a series of helical peptides with varying length of the photo-labile staple to obtain a detailed insight into the structure-property relationship in such photoresponsive biomolecules.

Roles of Different β-Defensins in the Human Reproductive System: A Review Study

Human β-defensins (hBDs) are cationic peptides with an amphipathic spatial shape and a high cysteine content. The members of this peptide family have been found in the human body with various functions, including the human reproductive system. Of among β-defensins in the human body, β-defensin 1, β-defensin 2, and β-defensin 126 are known in the human reproductive system. Human β-defensin 1 interacts with chemokine receptor 6 (CCR6) in the male reproductive system to prevent bacterial infections. This peptide has a positive function in antitumor immunity by recruiting dendritic cells and memory T cells in prostate cancer. It is necessary for fertilization via facilitating capacitation and acrosome reaction in the female reproductive system. Human β-defensin 2 is another peptide with antibacterial action which can minimize infection in different parts of the female reproductive system such as the vagina by interacting with CCR6. Human β-defensin 2 could play a role in preventing cervical cancer via interactions with dendritic cells. Human β-defensin 126 is required for sperm motility and protecting the sperm against immune system factors. This study attempted to review the updated knowledge about the roles of β-defensin 1, β-defensin 2, and β-defensin 126 in both the male and female reproductive systems.

The Essentials on microRNA-Encoded Peptides from Plants to Animals

Primary transcripts of microRNAs (pri-miRNAs) were initially defined as long non-coding RNAs that host miRNAs further processed by the microRNA processor complex. A few years ago, however, it was discovered in plants that pri-miRNAs actually contain functional open reading frames (sORFs) that translate into small peptides called miPEPs, for microRNA-encoded peptides. Initially detected in Arabidopsis thaliana and Medicago truncatula, recent studies have revealed the presence of miPEPs in other pri-miRNAs as well as in other species ranging from various plant species to animals. This suggests that miPEP numbers remain largely underestimated and that they could be a common signature of pri-miRNAs. Here we present the most recent advances in miPEPs research and discuss how their discovery has broadened our vision of the regulation of gene expression by miRNAs, and how miPEPs could be interesting tools in sustainable agriculture or the treatment of certain human diseases.

Insights into protein-DNA interactions from hydrogen bond energy-based comparative protein-ligand analyses

Hydrogen bonds play important roles in protein folding and protein-ligand interactions, particularly in specific protein-DNA recognition. However, the distributions of hydrogen bonds, especially hydrogen bond energy (HBE) in different types of protein-ligand complexes, is unknown. Here we performed a comparative analysis of hydrogen bonds among three non-redundant datasets of protein-protein, protein-peptide, and protein-DNA complexes. Besides comparing the number of hydrogen bonds in terms of types and locations, we investigated the distributions of HBE. Our results indicate that while there is no significant difference of hydrogen bonds within protein chains among the three types of complexes, interfacial hydrogen bonds are significantly more prevalent in protein-DNA complexes. More importantly, the interfacial hydrogen bonds in protein-DNA complexes displayed a unique energy distribution of strong and weak hydrogen bonds whereas majority of the interfacial hydrogen bonds in protein-protein and protein-peptide complexes are of predominantly high strength with low energy. Moreover, there is a significant difference in the energy distributions of minor groove hydrogen bonds between protein-DNA complexes with different binding specificity. Highly specific protein-DNA complexes contain more strong hydrogen bonds in the minor groove than multi-specific complexes, suggesting important role of minor groove in specific protein-DNA recognition. These results can help better understand protein-DNA interactions and have important implications in improving quality assessments of protein-DNA complex models.

Peptide Platform as a Powerful Tool in the Fight against COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a global pandemic causing over 195 million infections and more than 4 million fatalities as of July 2021.To date, it has been demonstrated that a number of mutations in the spike glycoprotein (S protein) of SARS-CoV-2 variants of concern abrogate or reduce the neutralization potency of several therapeutic antibodies and vaccine-elicited antibodies. Therefore, the development of additional vaccine platforms with improved supply and logistic profile remains a pressing need. In this work, we have validated the applicability of a peptide-based strategy focused on a preventive as well as a therapeutic purpose. On the basis of the involvement of the dipeptidyl peptidase 4 (DPP4), in addition to the angiotensin converting enzyme 2 (ACE2) receptor in the mechanism of virus entry, we analyzed peptides bearing DPP4 sequences by protein-protein docking and assessed their ability to block pseudovirus infection in vitro. In parallel, we have selected and synthetized peptide sequences located within the highly conserved receptor-binding domain (RBD) of the S protein, and we found that RBD-based vaccines could better promote elicitation of high titers of neutralizing antibodies specific against the regions of interest, as confirmed by immunoinformatic methodologies and in vivo studies. These findings unveil a key antigenic site targeted by broadly neutralizing antibodies and pave the way to the design of pan-coronavirus vaccines.

Cryo-EM structure of PepT2 reveals structural basis for proton-coupled peptide and prodrug transport in mammals

The SLC15 family of proton-coupled solute carriers PepT1 and PepT2 play a central role in human physiology as the principal route for acquiring and retaining dietary nitrogen. A remarkable feature of the SLC15 family is their extreme substrate promiscuity, which has enabled the targeting of these transporters for the improvement of oral bioavailability for several prodrug molecules. Although recent structural and biochemical studies on bacterial homologs have identified conserved sites of proton and peptide binding, the mechanism of peptide capture and ligand promiscuity remains unclear for mammalian family members. Here, we present the cryo-electron microscopy structure of the outward open conformation of the rat peptide transporter PepT2 in complex with an inhibitory nanobody. Our structure, combined with molecular dynamics simulations and biochemical and cell-based assays, establishes a framework for understanding peptide and prodrug recognition within this pharmaceutically important transporter family.

Experimental and Computational Models for Side Chain Discrimination in Peptide-Protein Interactions

A bis(18‐crown‐6) Tröger's base receptor and 4‐substituted hepta‐1,7‐diyl bisammonium salt ligands have been used as a model system to study the interactions between non‐polar side chains of peptides and an aromatic cavity of a protein. NMR titrations and NOESY/ROESY NMR spectroscopy were used to analyze the discrimination of the ligands by the receptor based on the substituent of the ligand, both quantitatively (free binding energies) and qualitatively (conformations). The analysis showed that an all‐anti conformation of the heptane chain was preferred for most of the ligands, both free and when bound to the receptor, and that for all of the receptor‐ligand complexes, the substituent was located inside or partly inside of the aromatic cavity of the receptor. We estimated the free binding energy of a methyl‐ and a phenyl group to an aromatic cavity, via CH‐π, and combined aromatic CH‐π and π‐π interactions to be −1.7 and −3.3 kJ mol⁻¹, respectively. The experimental results were used to assess the accuracy of different computational methods, including molecular mechanics (MM) and density functional theory (DFT) methods, showing that MM was superior.

Protein-Peptide Binding Site Detection Using 3D Convolutional Neural Networks

Peptides and peptide-based molecules represent a promising therapeutic modality targeting intracellular protein-protein interactions, potentially combining the beneficial properties of biologics and small-molecule drugs. Protein-peptide complexes occupy a unique niche of interaction interfaces with respect to protein-protein and protein-small molecule complexes. Protein-peptide binding site identification resembles image object detection, a field that had been revolutionalized with computer vision techniques. We present a new protein-peptide binding site detection method called BiteNet_Pp by harnessing the power of 3D convolutional neural network. Our method employs a tensor-based representation of spatial protein structures, which is fed to 3D convolutional neural network, resulting in probability scores and coordinates of the binding "hot spots" in the input structures. We used the domain adaptation technique to fine-tune model trained on protein-small molecule complexes using a manually curated set of protein-peptide structures. BiteNet_Pp consistently outperforms existing state-of-the-art methods in the independent test benchmark. It takes less than a second to analyze a single-protein structure, making BiteNet_Pp suitable for the large-scale analysis of protein-peptide binding sites.

Strategies to Control or Mimic Growth Factor Activity for Bone, Cartilage, and Osteochondral Tissue Engineering

Growth factors play a critical role in tissue repair and regeneration. However, their clinical success is limited by their low stability, short half-life, and rapid diffusion from the delivery site. Supraphysiological growth factor concentrations are often required to demonstrate efficacy but can lead to adverse reactions, such as inflammatory complications and increased cancer risk. These issues have motivated the development of delivery systems that enable sustained release and controlled presentation of growth factors. This review specifically focuses on bioconjugation strategies to enhance growth factor activity for bone, cartilage, and osteochondral applications. We describe approaches to localize growth factors using noncovalent and covalent methods, bind growth factors via peptides, and mimic growth factor function with mimetic peptide sequences. We also discuss emerging and future directions to control spatiotemporal growth factor delivery to improve functional tissue repair and regeneration.

Structure- and sequence-based design of synthetic single-domain antibody libraries

Single-domain antibody fragments known as VHH have emerged in the pharmaceutical industry as useful biotherapeutics. These molecules, which are naturally produced by camelids, share the characteristics of high affinity and specificity with traditional human immunoglobulins, while consisting of only a single heavy chain. Currently, the most common method for generating VHH is via animal immunization, which can be costly and time-consuming. Here we describe the development of a synthetic VHH library for in vitro selection of single domain binders. We combine structure-based design and next-generation sequencing analysis to build a library with characteristics that closely mimic the natural repertoire. To validate the performance of our synthetic library, we isolated VHH against three model antigens (soluble mouse PD-1 ectodomain, amyloid-β peptide, and MrgX1 GPCR) of different sizes and characteristics. We were able to isolate diverse binders targeting different epitopes with high affinity (as high as 5 nM) against all three targets. We then show that anti-mPD-1 binders have functional activity in a receptor blocking assay.

Expression, purification and characterization of α-synuclein fibrillar specific scFv from inclusion bodies

Aggregation of α-synuclein (α-syn) has been implicated in multiple neurodegenerative disorders including Parkinson's disease (PD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA), collectively grouped as synucleinopathies. Recently, recombinant antibody fragments (Fab, scFvs and diabodies) against α-syn have emerged as an alternative to the traditional full-length antibody in immunotherapeutic approaches owing to their advantages including smaller size and higher stability, specificity and affinity. However, most of the recombinant antibody fragments tend to be expressed as inclusion bodies (IBs) making its purification extremely challenging. In the current study, a single-chain variable fragment (scFv-F) antibody, targeting the pathogenic α-syn fibrils, was engineered and expressed in E. coli. Majority of the expressed scFv-F accumulated in insoluble aggregates as IBs. A variety of mild and harsh solubilizing conditions were tested to solubilize IBs containing scFv-F to obtain the active protein. To preserve secondary structure and bioactivity, a mild solubilizing protocol involving 100 mM Tris, pH 12.5 with 2 M urea was chosen to dissolve IBs. Slow on-column refolding method was employed to subsequently remove urea and obtain active scFv-F. A three-dimensional (3D) model was built using homology modeling and subjected to molecular docking with the known α-syn structure. Structural alignment was performed to delineate the potential binding pocket. The scFv-F thus purified demonstrated high specificity towards α-syn fibrils compared to monomers. Molecular modeling studies suggest that scFv-F shares the same structural topology with other known scFvs. We present evidence through structural docking and alignment that scFv-F binds to α-syn C-terminal region. In conclusion, mild solubilization followed by slow on-column refolding can be utilized as a generalized and efficient method for hard to purify disease relevant insoluble proteins and/or antibody molecules from IBs.

Immobilization of Growth Factors for Cell Therapy Manufacturing

Cell therapy products exhibit great therapeutic potential but come with a deterring price tag partly caused by their costly manufacturing processes. The development of strategies that lead to cost-effective cell production is key to expand the reach of cell therapies. Growth factors are critical culture media components required for the maintenance and differentiation of cells in culture and are widely employed in cell therapy manufacturing. However, they are expensive, and their common use in soluble form is often associated with decreased stability and bioactivity. Immobilization has emerged as a possible strategy to optimize growth factor use in cell culture. To date, several immobilization techniques have been reported for attaching growth factors onto a variety of biomaterials, but these have been focused on tissue engineering. This review briefly summarizes the current landscape of cell therapy manufacturing, before describing the types of chemistry that can be used to immobilize growth factors for cell culture. Emphasis is placed to identify strategies that could reduce growth factor usage and enhance bioactivity. Finally, we describe a case study for stem cell factor.

Highly Flexible Ligand Docking: Benchmarking of the DockThor Program on the LEADS-PEP Protein-Peptide Data Set

Protein-peptide interactions play a crucial role in many cellular and biological functions, which justify the increasing interest in the development of peptide-based drugs. However, predicting experimental binding modes and affinities in protein-peptide docking remains a great challenge for most docking programs due to some particularities of this class of ligands, such as the high degree of flexibility. In this paper, we present the performance of the DockThor program on the LEADS-PEP data set, a benchmarking set composed of 53 diverse protein-peptide complexes with peptides ranging from 3 to 12 residues and with up to 51 rotatable bonds. The DockThor performance for pose prediction on redocking studies was compared with some state-of-the-art docking programs that were also evaluated on the LEADS-PEP data set, AutoDock, AutoDock Vina, Surflex, GOLD, Glide, rDock, and DINC, as well as with the task-specific docking protocol HPepDock. Our results indicate that DockThor could dock 40% of the cases with an overall backbone RMSD below 2.5 Å when the top-scored docking pose was considered, exhibiting similar results to Glide and outperforming other protein-ligand docking programs, whereas rDock and HPepDock achieved superior results. Assessing the docking poses closest to the crystal structure (i.e., best-RMSD pose), DockThor achieved a success rate of 60% in pose prediction. Due to the great overall performance of handling peptidic compounds, the DockThor program can be considered as suitable for docking highly flexible and challenging ligands, with up to 40 rotatable bonds. DockThor is freely available as a virtual screening Web server at https://www.dockthor.lncc.br/ .

A review on peptide functionalized graphene derivatives as nanotools for biosensing

Peptides exhibit unique binding behavior with graphene and its derivatives by forming bonds on its edges and planes. This makes them useful for sensing and imaging applications. This review with (155 refs.) summarizes the advances made in the last decade in the field of peptide-GO bioconjugation, and the use of these conjugates in analytical sciences and imaging. The introduction emphasizes the need for understanding the biotic-abiotic interactions in order to construct controllable peptide-functionalized graphitic material-based nanotools. The next section covers covalent and non-covalent interactions between peptide and oxidized graphene derivatives along with a discussion of the adsorption events during interfacing. We then describe applications of peptide-graphene conjugates in bioassays, with subsections on (a) detection of cancer cells, (b) monitoring protease activity, (c) determination of environmental pollutants and (d) determination of pathogenic microorganisms. The concluding section describes the current status of peptide functionalized graphitic bioconjugates and addresses future perspectives. Graphical abstractSchematic representation depicting biosensing applications of peptide functionalized graphene oxide.

PepBDB: a comprehensive structural database of biological peptide-protein interactions

Summary

A structural database of peptide-protein interactions is important for drug discovery targeting peptide-mediated interactions. Although some peptide databases, especially for special types of peptides, have been developed, a comprehensive database of cleaned peptide-protein complex structures is still not available. Such cleaned structures are valuable for docking and scoring studies in structure-based drug design. Here, we have developed PepBDB-a curated Peptide Binding DataBase of biological complex structures from the Protein Data Bank (PDB). PepBDB presents not only cleaned structures but also extensive information about biological peptide-protein interactions, and allows users to search the database with a variety of options and interactively visualize the search results.

Availability and implementation

PepBDB is available at http://huanglab.phys.hust.edu.cn/pepbdb/.

Computational Opportunities and Challenges in Finding Cyclic Peptide Modulators of Protein-Protein Interactions

Peptide cyclization can improve stability, conformational constraint, and compactness. However, apart from beta-turn structures, which are well incorporated into cyclic peptides (CPs), many primary peptide structures and functions are markedly altered by cyclization. Accordingly, to mimic linear peptide interfaces with cyclic peptides, it can be beneficial to screen combinatorial cyclic peptide libraries. Computational methods have been developed to screen CPs, but face a number of challenges. Here, we review methods to develop in silico computational libraries, and the potential for screening naturally occurring libraries of CPs. The simplest and most rapid computational pharmacophore methods that estimate peptide three-dimensional structures to be screened versus targets are relatively easy to implement, and while the constraint on structure imposed by cyclization makes them more effective than the same approaches with linear peptides, there are a large number of limiting assumptions. In contrast, full molecular dynamics simulations of cyclic peptide structures not only are costly to implement, but also require careful attention to interpretation, so that not only is the computation time rate limiting, but the interpretation time is also rate limiting due to the analysis of the typically complex underlying conformational space of CPs. A challenge for the field of computational cyclic peptide screening is to bridge this gap effectively. Natural compound libraries of short cyclic peptides, and short cyclized regions of proteins, encoded in the genomes of many organisms present a potential treasure trove of novel functionality which may be screened via combined computational and experimental screening approaches.

Alanine rich peptide from Populus trichocarpa inhibit growth of Staphylococcus aureus via targetting its extracellular domain of Sensor Histidine Kinase YycGex protein

BACKGROUND

Due to growing concern towards microbial resistance, ongoing search for developing novel bioactive compounds such as peptides is on rise. The aim of this study was to evaluate antimicrobial effect of Populus trichocarpa extract, chemically identify the active peptide fraction and finds its target in Staphylococcus aureus.

METHODS

In this study the active fraction of P. trichocarpa crude extract was purified and characterized using MS/MS. This peptide PT13 antimicrobial activity was confirmed by in-vitro agar based disk diffusion and in-vivo infection model of G. mellonella. The proteomic expression analysis of S. aureus under influence of PT13 was studied using LTQ-Orbitrap-MS in-solution digestion and identity of target protein was acquired with their quantified expression using label-free approach of Progenesis QI software. Docking study was performed with peptide PT13 and its target YycG protein using CABS-dock.

RESULTS

The active fraction PT13 sequence was identified as KVPVAAAAAAAAAVVASSMVVAAAK, with 25 amino acid including 13 alanine having M/Z 2194.2469. PT13 was uniformly inhibited growth S. aureus SA91 and MIC was determined 16 μg/mL for SA91 S. aureus strain. Sensor histidine kinase (YycG) was most significant target found differentially expressed under influence of PT13. G. mellonella larvae were killed rapidly due to S aureus infection, whereas death in protected group was insignificant in compare to control. The docking models showed ten docking models with RMSD value 1.89 for cluster 1 and RMSD value 3.95 for cluster 2 which is predicted to be high quality model.

CONCLUSION

Alanine rich peptide could be useful in constructing as antimicrobial peptide for targeting extracellular Domain of Sensor Histidine Kinase YycG from S. aureus used in the study.

Hydrogels Constructed from Engineered Proteins

Due to their various potential biomedical applications, hydrogels based on engineered proteins have attracted considerable interest. Benefitting from significant progress in recombinant DNA technology and protein engineering/design techniques, the field of protein hydrogels has made amazing progress. The latest progress of hydrogels constructed from engineered recombinant proteins are presented, mainly focused on biorecognition-driven physical hydrogels as well as chemically crosslinked hydrogels. The various bio-recognition based physical crosslinking strategies are discussed, as well as chemical crosslinking chemistries used to engineer protein hydrogels, and protein hydrogels' various biomedical applications. The future perspectives of this fast evolving field of biomaterials are also discussed.

Peptides and Peptide Analogs to Inhibit Protein-Protein Interactions

Protein-protein interactions are governed by relatively few amino acid residues at the binding interface. Peptides derived from these protein regions may serve as mimics of one of the interaction partners in structural studies or as inhibitors to disrupt the respective interaction and investigate its biological consequences. Inhibitory peptides may also be lead structures for drug development if the respective protein-protein interaction is essential for a pathogen or disease mechanism. Binding peptides may be systematically derived from one of the binding partners or found in the screen of combinatorial peptide libraries. Molecular modelling based on structural data helps to refine existing peptides or even design novel binding peptides. This chapter gives an outline of the binding peptide discovery process and subsequent chemical modifications to further enhance affinity and specificity and to increase stability against degradation in vivo. Examples from the past three decades illustrate the great diversity of applications for protein binding peptides and peptide analogs.

Human Non-neutralizing HIV-1 Envelope Monoclonal Antibodies Limit the Number of Founder Viruses during SHIV Mucosal Infection in Rhesus Macaques

HIV-1 mucosal transmission begins with virus or virus-infected cells moving through mucus across mucosal epithelium to infect CD4+ T cells. Although broadly neutralizing antibodies (bnAbs) are the type of HIV-1 antibodies that are most likely protective, they are not induced with current vaccine candidates. In contrast, antibodies that do not neutralize primary HIV-1 strains in the TZM-bl infection assay are readily induced by current vaccine candidates and have also been implicated as secondary correlates of decreased HIV-1 risk in the RV144 vaccine efficacy trial. Here, we have studied the capacity of anti-Env monoclonal antibodies (mAbs) against either the immunodominant region of gp41 (7B2 IgG1), the first constant region of gp120 (A32 IgG1), or the third variable loop (V3) of gp120 (CH22 IgG1) to modulate in vivo rectal mucosal transmission of a high-dose simian-human immunodeficiency virus (SHIV-BaL) in rhesus macaques. 7B2 IgG1 or A32 IgG1, each containing mutations to enhance Fc function, was administered passively to rhesus macaques but afforded no protection against productive clinical infection while the positive control antibody CH22 IgG1 prevented infection in 4 of 6 animals. Enumeration of transmitted/founder (T/F) viruses revealed that passive infusion of each of the three antibodies significantly reduced the number of T/F genomes. Thus, some antibodies that bind HIV-1 Env but fail to neutralize virus in traditional neutralization assays may limit the number of T/F viruses involved in transmission without leading to enhancement of viral infection. For one of these mAbs, gp41 mAb 7B2, we provide the first co-crystal structure in complex with a common cyclical loop motif demonstrated to be critical for infection by other retroviruses.

Computational approaches to developing short cyclic peptide modulators of protein-protein interactions

Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating "difficult" targets, such as protein-protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non"druglike" by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance-the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.

Synthesis of bioactive protein hydrogels by genetically encoded SpyTag-SpyCatcher chemistry

Protein-based hydrogels have emerged as promising alternatives to synthetic hydrogels for biomedical applications, owing to the precise control of structure and function enabled by protein engineering. Nevertheless, strategies for assembling 3D molecular networks that carry the biological information encoded in full-length proteins remain underdeveloped. Here we present a robust protein gelation strategy based on a pair of genetically encoded reactive partners, SpyTag and SpyCatcher, that spontaneously form covalent isopeptide linkages under physiological conditions. The resulting "network of Spies" may be designed to include cell-adhesion ligands, matrix metalloproteinase-1 cleavage sites, and full-length globular proteins [mCherry and leukemia inhibitory factor (LIF)]. The LIF network was used to encapsulate mouse embryonic stem cells; the encapsulated cells remained pluripotent in the absence of added LIF. These results illustrate a versatile strategy for the creation of information-rich biomaterials.

Identification and fine mapping of a linear B cell epitope of human vimentin

Knowledge about antibody-antigen interactions is important for the understanding of the immune system mechanisms and for supporting development of drugs and biomarkers. A tool for identification of these antigenic epitopes of specific antibodies is epitope mapping. In this study, a modified enzyme-linked immunosorbent assay was applied for epitope mapping of a mouse monoclonal vimentin antibody using overlapping resin-bound peptides covering the entire vimentin protein. The minimal epitope required for binding was identified as the LDSLPLVD sequence using N- and C-terminally truncated peptides. The peptide sequence LDSLPLVDTH was identified as the complete epitope, corresponding to amino acids 428-437 in the C-terminal end of the human vimentin protein. Alanine scanning and functionality scanning applying substituted peptides were used to identify amino acids essential for antibody reactivity. In particular, the two aspartate residues were found to be essential for antibody reactivity since these amino acids could not be substituted without a reduction in antibody reactivity. The majority of the remaining amino acids could be substituted without reducing antibody reactivity notably. These results confirm that charged amino acids are essential for antibody reactivity and that the vimentin antibody is dependent on side-chain interactions in combination with backbone interactions.

SpyLigase peptide-peptide ligation polymerizes affibodies to enhance magnetic cancer cell capture

Individual proteins can now often be modified with atomic precision, but there are still major obstacles to connecting proteins into larger assemblies. To direct protein assembly, ideally, peptide tags would be used, providing the minimal perturbation to protein function. However, binding to peptides is generally weak, so assemblies are unstable over time and disassemble with force or harsh conditions. We have recently developed an irreversible protein-peptide interaction (SpyTag/SpyCatcher), based on a protein domain from Streptococcus pyogenes, that locks itself together via spontaneous isopeptide bond formation. Here we develop irreversible peptide-peptide interaction, through redesign of this domain and genetic dissection into three parts: a protein domain termed SpyLigase, which now ligates two peptide tags to each other. All components expressed efficiently in Escherichia coli and peptide tags were reactive at the N terminus, at the C terminus, or at internal sites. Peptide-peptide ligation enabled covalent and site-specific polymerization of affibodies or antibodies against the tumor markers epidermal growth factor receptor (EGFR) and HER2. Magnetic capture of circulating tumor cells (CTCs) is one of the most promising approaches to improve cancer prognosis and management, but CTC capture is limited by inefficient recovery of cells expressing low levels of tumor antigen. SpyLigase-assembled protein polymers made possible the isolation of cancerous cells expressing lower levels of tumor antigen and should have general application in enhancing molecular capture.

Biomarkers in Japanese encephalitis: a review

JE is a flavivirus generated dreadful CNS disease which causes high mortality in various pediatric groups. JE disease is currently diagnosed by measuring the level of viral antigens and virus neutralization IgM antibodies in blood serum and CSF by ELISA. However, it is not possible to measure various disease-identifying molecules, structural and molecular changes occurred in tissues, and cells by using such routine methods. However, few important biomarkers such as cerebrospinal fluid, plasma, neuro-imaging, brain mapping, immunotyping, expression of nonstructural viral proteins, systematic mRNA profiling, DNA and protein microarrays, active caspase-3 activity, reactive oxygen species and reactive nitrogen species, levels of stress-associated signaling molecules, and proinflammatory cytokines could be used to confirm the disease at an earlier stage. These biomarkers may also help to diagnose mutant based environment specific alterations in JEV genotypes causing high pathogenesis and have immense future applications in diagnostics. There is an utmost need for the development of new more authentic, appropriate, and reliable physiological, immunological, biochemical, biophysical, molecular, and therapeutic biomarkers to confirm the disease well in time to start the clinical aid to the patients. Hence, the present review aims to discuss new emerging biomarkers that could facilitate more authentic and fast diagnosis of JE disease and its related disorders in the future.

Chimeric rhinoviruses displaying MPER epitopes elicit anti-HIV neutralizing responses

Background

The development of an effective AIDS vaccine has been a formidable task, but remains a critical necessity. The well conserved membrane-proximal external region (MPER) of the HIV-1 gp41 glycoprotein is one of the crucial targets for AIDS vaccine development, as it has the necessary attribute of being able to elicit antibodies capable of neutralizing diverse isolates of HIV.

Methodology/Principle Findings

Guided by X-ray crystallography, molecular modeling, combinatorial chemistry, and powerful selection techniques, we designed and produced six combinatorial libraries of chimeric human rhinoviruses (HRV) displaying the MPER epitopes corresponding to mAbs 2F5, 4E10, and/or Z13e1, connected to an immunogenic surface loop of HRV via linkers of varying lengths and sequences. Not all libraries led to viable chimeric viruses with the desired sequences, but the combinatorial approach allowed us to examine large numbers of MPER-displaying chimeras. Among the chimeras were five that elicited antibodies capable of significantly neutralizing HIV-1 pseudoviruses from at least three subtypes, in one case leading to neutralization of 10 pseudoviruses from all six subtypes tested.

Conclusions

Optimization of these chimeras or closely related chimeras could conceivably lead to useful components of an effective AIDS vaccine. While the MPER of HIV may not be immunodominant in natural infection by HIV-1, its presence in a vaccine cocktail could provide critical breadth of protection.

PepBind: a comprehensive database and computational tool for analysis of protein-peptide interactions

Protein-peptide interactions, where one partner is a globular protein (domain) and the other is a flexible linear peptide, are key components of cellular processes predominantly in signaling and regulatory networks, hence are prime targets for drug design. To derive the details of the protein-peptide interaction mechanism is often a cumbersome task, though it can be made easier with the availability of specific databases and tools. The Peptide Binding Protein Database (PepBind) is a curated and searchable repository of the structures, sequences and experimental observations of 3100 protein-peptide complexes. The web interface contains a computational tool, protein inter-chain interaction (PICI), for computing several types of weak or strong interactions at the protein-peptide interaction interface and visualizing the identified interactions between residues in Jmol viewer. This initial database release focuses on providing protein-peptide interface information along with structure and sequence information for protein-peptide complexes deposited in the Protein Data Bank (PDB). Structures in PepBind are classified based on their cellular activity. More than 40% of the structures in the database are found to be involved in different regulatory pathways and nearly 20% in the immune system. These data indicate the importance of protein-peptide complexes in the regulation of cellular processes.

Secondary structure, a missing component of sequence-based minimotif definitions

Minimotifs are short contiguous segments of proteins that have a known biological function. The hundreds of thousands of minimotifs discovered thus far are an important part of the theoretical understanding of the specificity of protein-protein interactions, posttranslational modifications, and signal transduction that occur in cells. However, a longstanding problem is that the different abstractions of the sequence definitions do not accurately capture the specificity, despite decades of effort by many labs. We present evidence that structure is an essential component of minimotif specificity, yet is not used in minimotif definitions. Our analysis of several known minimotifs as case studies, analysis of occurrences of minimotifs in structured and disordered regions of proteins, and review of the literature support a new model for minimotif definitions that includes sequence, structure, and function.

Epitope-specificity of recombinant antibodies reveals promiscuous peptide-binding properties

Protein-peptide interactions are a common occurrence and essential for numerous cellular processes, and frequently explored in broad applications within biology, medicine, and proteomics. Therefore, understanding the molecular mechanism(s) of protein-peptide recognition, specificity, and binding interactions will be essential. In this study, we report the first detailed analysis of antibody-peptide interaction characteristics, by combining large-scale experimental peptide binding data with the structural analysis of eight human recombinant antibodies and numerous peptides, targeting tryptic mammalian and eukaryote proteomes. The results consistently revealed that promiscuous peptide-binding interactions, that is, both specific and degenerate binding, were exhibited by all antibodies, and the discovery was corroborated by orthogonal data, indicating that this might be a general phenomenon for low-affinity antibody-peptide interactions. The molecular mechanism for the degenerate peptide-binding specificity appeared to be executed through the use of 2-3 semi-conserved anchor residues in the C-terminal part of the peptides, in analogue to the mechanism utilized by the major histocompatibility complex-peptide complexes. In the long-term, this knowledge will be instrumental for advancing our fundamental understanding of protein-peptide interactions, as well as for designing, generating, and applying peptide specific antibodies, or peptide-binding proteins in general, in various biotechnical and medical applications.

Peptide tag forming a rapid covalent bond to a protein, through engineering a bacterial adhesin

Protein interactions with peptides generally have low thermodynamic and mechanical stability. Streptococcus pyogenes fibronectin-binding protein FbaB contains a domain with a spontaneous isopeptide bond between Lys and Asp. By splitting this domain and rational engineering of the fragments, we obtained a peptide (SpyTag) which formed an amide bond to its protein partner (SpyCatcher) in minutes. Reaction occurred in high yield simply upon mixing and amidst diverse conditions of pH, temperature, and buffer. SpyTag could be fused at either terminus or internally and reacted specifically at the mammalian cell surface. Peptide binding was not reversed by boiling or competing peptide. Single-molecule dynamic force spectroscopy showed that SpyTag did not separate from SpyCatcher until the force exceeded 1 nN, where covalent bonds snap. The robust reaction conditions and irreversible linkage of SpyTag shed light on spontaneous isopeptide bond formation and should provide a targetable lock in cells and a stable module for new protein architectures.