Evolving a Peptide: Library Platforms and Diversification Strategies

Optimization of the antifungal properties of the bacterial peptide EntV by variant analysis

Fungal resistance to commonly used medicines is a growing public health threat, and there is a dire need to develop new classes of antifungals. We previously described a peptide produced by Enterococcus faecalis, EntV, that restricts Candida albicans to a benign form rather than having direct fungicidal activity. Moreover, we showed that one 12-amino acid (aa) alpha helix of this peptide retained full activity, with partial activity down to the 10aa alpha helix. Using these peptides as a starting point, the current investigation sought to identify the critical features necessary for antifungal activity and to screen for new variants with enhanced activity using both biofilm and C. elegans infection assays. First, the short peptides were screened for residues with critical activity by generating alanine substitutions. Based on this information, we used synthetic molecular evolution (SME) to rationally vary the specific residues of the 10aa variant in combination to generate a library that was screened to identify variants with more potent antifungal activity than the parent template. Five gain-of-function peptides were identified. Additionally, chemical modifications to the peptides to increase stability, including substitutions of D-amino acids and hydrocarbon stapling, were investigated. The most promising peptides were additionally tested in mouse models of oropharyngeal and systemic candidiasis where their efficacy in preventing infection was demonstrated. The expectation is that these discoveries will contribute to the development of new therapeutics in the fight against antimicrobial resistant fungi.

IMPORTANCE

Since the early 1980s, the incidence of disseminated life-threatening fungal infections has been on the rise. Worldwide, Candida and Cryptococcus species are among the most common agents causing these infections. Simultaneously, with this rise of clinical incidence, there has also been an increased prevalence of antifungal resistance, making treatment of these infections very difficult. For example, there are now strains of Candida auris that are resistant to all three classes of currently used antifungal drugs. In this study, we report on a strategy that allows for the development of novel antifungal agents by using synthetic molecular evolution. These discoveries demonstrate that the enhancement of antifungal activity from naturally occurring peptides is possible and can result in clinically relevant agents that have efficacy in multiple in vivo models as well as the potential for broad-spectrum activity.

Surface expression of carbonic anhydrase on E. coli as a sustainable approach for enzymatic CO2 capture

The utilisation of carbonic anhydrase (CA) in CO2 sequestration is becoming prominent as an efficient, environment friendly and rapid catalyst for capturing CO2 from industrial emissions. However, the application of CA enzyme in soluble form is constrained due to its poor stability in operational conditions of CO2 capture and also production cost of the enzyme. Addressing these limitations, the present study focuses on the surface display of CA from Bacillus halodurans (BhCA) on E coli aiming to contribute to the cost-effectiveness of carbon capture through CA technology. This involved the fusion of the BhCA-encoding gene with the adhesion molecule involved in diffuse adherence (AIDA-I) autotransporter, resulting in the efficient display of BhCA (595 ± 60 U/gram dry cell weight). Verification of the surface display of BhCA was accomplished by conjugating with FITC labelled anti-his antibody followed by fluorescence-activated cell sorting (FACS) and cellular fractionation in conjunction with zymography. Biochemical characterisation of whole-cell biocatalyst revealed a noteworthy enhancement in thermostability, improvement in the thermostability with T1/2 of 90 ± 1.52 minutes at 50 ˚C, 36 ± 2.51 minutes at 60 ˚C and18 ± 1.52 minutes at 80˚C. Surface displayed BhCA displayed remarkable reusability retaining 100% activity even after 15 cycles. Surface displayed BhCA displayed highly alkali stable nature like free counterpart in solution. The alkali stability of the surface-displayed BhCA was comparable to its free counterpart in solution. Furthermore, the study investigated the impact of different metal ions, modulators, and detergents on the whole-cell biocatalysts. The present work represents the first report on surface display of CA utilising the AIDA-1 autotransporter.

Review of phage display: A jack-of-all-trades and master of most biomolecule display

Phage display was first described by George P. Smith when it was shown that virus particles were capable of presenting foreign proteins on their surface. The technology has paved the way for the evolution of various biomolecules presentation and diverse selection strategies. This unique feature has been applied as a versatile platform for numerous applications in drug discovery, protein engineering, diagnostics, and vaccine development. Over the decades, the limits of biomolecules displayed on phage particles have expanded from peptides to proteomes and even alternative scaffolds. This has allowed phage display to be viewed as a versatile display platform to accommodate various biomolecules ranging from small peptides to larger proteomes which has significantly impacted advancements in the biomedical industry. This review will explore the vast array of biomolecules that have been successfully employed in phage display technology in biomedical research.

iAVPs-ResBi: Identifying antiviral peptides by using deep residual network and bidirectional gated recurrent unit

Human history is also the history of the fight against viral diseases. From the eradication of viruses to coexistence, advances in biomedicine have led to a more objective understanding of viruses and a corresponding increase in the tools and methods to combat them. More recently, antiviral peptides (AVPs) have been discovered, which due to their superior advantages, have achieved great impact as antiviral drugs. Therefore, it is very necessary to develop a prediction model to accurately identify AVPs. In this paper, we develop the iAVPs-ResBi model using k-spaced amino acid pairs (KSAAP), encoding based on grouped weight (EBGW), enhanced grouped amino acid composition (EGAAC) based on the N5C5 sequence, composition, transition and distribution (CTD) based on physicochemical properties for multi-feature extraction. Then we adopt bidirectional long short-term memory (BiLSTM) to fuse features for obtaining the most differentiated information from multiple original feature sets. Finally, the deep model is built by combining improved residual network and bidirectional gated recurrent unit (BiGRU) to perform classification. The results obtained are better than those of the existing methods, and the accuracies are 95.07, 98.07, 94.29 and 97.50% on the four datasets, which show that iAVPs-ResBi can be used as an effective tool for the identification of antiviral peptides. The datasets and codes are freely available at https://github.com/yunyunliang88/iAVPs-ResBi.

Exploring shark VNAR antibody against infectious diseases using phage display technology

Antibody with high affinity and specificity to antigen has widely used as a tool to combat various diseases. The variable domain of immunoglobulin new antigen receptor (VNAR) naturally found in shark contains autonomous function as single-domain antibody. Due to its excellent characteristics, the small, non-complex, and highly stable have made shark VNAR can acquires the antigen-binding capability that might not be reached by conventional antibody. Phage display technology enables shark VNAR to be presented on the surface of phage, allowing the exploration of shark VNAR as an alternative antibody format to target antigens from various infectious diseases. The application of phage-displayed shark VNAR in antibody library and biopanning eventually leads to the discovery and isolation of antigen-specific VNARs with diagnostic and therapeutic potential towards infectious diseases. This review provides an overview of the shark VNAR antibody, the types of phage display technology with comparison to the other types of display system, as well as the application and case studies of phage-displayed shark VNAR antibodies against infectious diseases.

Construction and Applications of Mammalian Cell-Based DNA-Encoded Peptide/Protein Libraries

DNA-encoded peptide/protein libraries are the starting point for protein evolutionary modification and functional peptide/antibody selection. Different display technologies, protein directed evolution, and deep mutational scanning (DMS) experiments employ DNA-encoded libraries to provide sequence variations for downstream affinity- or function-based selections. Mammalian cells promise the inherent post-translational modification and near-to-natural conformation of exogenously expressed mammalian proteins and thus are the best platform for studying transmembrane proteins or human disease-related proteins. However, due to the current technical bottlenecks of constructing mammalian cell-based large size DNA-encoded libraries, the advantages of mammalian cells as screening platforms have not been fully exploited. In this review, we summarize the current efforts in constructing DNA-encoded libraries in mammalian cells and the existing applications of these libraries in different fields.

Targeting Peptides: The New Generation of Targeted Drug Delivery Systems

Peptides can act as targeting molecules, analogously to oligonucleotide aptamers and antibodies. They are particularly efficient in terms of production and stability in physiological environments; in recent years, they have been increasingly studied as targeting agents for several diseases, from tumors to central nervous system disorders, also thanks to the ability of some of them to cross the blood-brain barrier. In this review, we will describe the techniques employed for their experimental and in silico design, as well as their possible applications. We will also discuss advancements in their formulation and chemical modifications that make them even more stable and effective. Finally, we will discuss how their use could effectively help to overcome various physiological problems and improve existing treatments.

Strategies and opportunities for engineering antifungal peptides for therapeutic applications

Antifungal peptides (AFPs) are widely described as promising prospects to treat and prevent fungal infections, though they are far less studied than their antibacterial counterparts. Although promising, AFPs have practical limitations that have hindered their use as therapeutics. Rational design and combinatorial engineering are powerful protein engineering strategies with much potential to address the limitations of AFPs by designing peptides with improved physiochemical and biological characteristics. We examine how rational design and combinatorial engineering approaches have already been used to improve the properties of AFPs and propose key opportunities for applying these strategies to push the design and application of AFPs forward.

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

In Silico Analysis of Neutralizing Antibody Epitopes on The Hepatitis C Virus Surface Glycoproteins

OBJECTIVE

Despite of antiviral drugs and successful treatment, an effective vaccine against hepatitis C virus (HCV) infection is still required. Recently, bioinformatic methods same as prediction algorithms, have greatly contributed to the use of peptides in the design of immunogenic vaccines. Therefore, finding more conserved sites on the surface glycoproteins (E1 and E2) of HCV, as major targets to design an effective vaccine against genetically different viruses in each genotype was the goal of the study.

MATERIALS AND METHODS

In this experimental study, 100 entire sequences of E1 and E2 were retrieved from the NCBI website and analyzed in terms of mutations and critical sites by Bioedit 7.7.9, MEGA X software. Furthermore, HCV-1a samples were obtained from some infected people in Iran, and reverse transcriptase-polymerase chain reaction (RTPCR) assay was optimized to amplify their E1 and E2 genes. Moreover, all three-dimensional structures of E1 and E2 downloaded from the PDB database were analyzed by YASARA. In the next step, three interest areas of humoral immunity in the E2 glycoprotein were evaluated. OSPREY3.0 protein design software was performed to increase the affinity to neutralizing antibodies in these areas.

RESULTS

We found the effective in silico binding affinity of residues in three broadly neutralizing epitopes of E2 glycoprotein. First, positions that have substitution capacity were detected in these epitopes. Furthermore, residues that have high stability for substitution in these situations were indicated. Then, the mutants with the strongest affinity to neutralize antibodies were predicted. I414M, T416S, I422V, I414M-T416S, and Q412N-I414M-T416S substitutions theoretically were exhibited as mutants with the best affinity binding.

CONCLUSION

Using an innovative filtration strategy, the residues of E2 epitopes which have the best in silico binding affinity to neutralizing antibodies were exhibited and a distinct peptide library platform was designed.

Biofunctionalization of Multiplexed Silicon Photonic Biosensors

Silicon photonic (SiP) sensors offer a promising platform for robust and low-cost decentralized diagnostics due to their high scalability, low limit of detection, and ability to integrate multiple sensors for multiplexed analyte detection. Their CMOS-compatible fabrication enables chip-scale miniaturization, high scalability, and low-cost mass production. Sensitive, specific detection with silicon photonic sensors is afforded through biofunctionalization of the sensor surface; consequently, this functionalization chemistry is inextricably linked to sensor performance. In this review, we first highlight the biofunctionalization needs for SiP biosensors, including sensitivity, specificity, cost, shelf-stability, and replicability and establish a set of performance criteria. We then benchmark biofunctionalization strategies for SiP biosensors against these criteria, organizing the review around three key aspects: bioreceptor selection, immobilization strategies, and patterning techniques. First, we evaluate bioreceptors, including antibodies, aptamers, nucleic acid probes, molecularly imprinted polymers, peptides, glycans, and lectins. We then compare adsorption, bioaffinity, and covalent chemistries for immobilizing bioreceptors on SiP surfaces. Finally, we compare biopatterning techniques for spatially controlling and multiplexing the biofunctionalization of SiP sensors, including microcontact printing, pin- and pipette-based spotting, microfluidic patterning in channels, inkjet printing, and microfluidic probes.

Rationally Designed Minimal Bioactive Domains of AS-48 Bacteriocin Homologs Possess Potent Antileishmanial Properties

Leishmaniasis, a category I neglected tropical disease, is a group of diseases caused by the protozoan parasite Leishmania species with a wide range of clinical manifestations. Current treatment options can be highly toxic and expensive, with drug relapse and the emergence of resistance. Bacteriocins, antimicrobial peptides ribosomally produced by bacteria, are a relatively new avenue for potential antiprotozoal drugs. Particular interest has been focused on enterocin AS-48, with previously proven efficacy against protozoan species, including Leishmania spp. Sequential characterization of enterocin AS-48 has illustrated that antibacterial bioactivity is preserved in linearized, truncated forms; however, minimal domains of AS-48 bacteriocins have not yet been explored against protozoans. Using rational design techniques to improve membrane penetration activity, we designed peptide libraries using the minimal bioactive domain of AS-48 homologs. Stepwise changes to the charge (z), hydrophobicity (H), and hydrophobic dipole moment (μH) were achieved through lysine and tryptophan substitutions and the inversion of residues within the helical wheel, respectively. A total of 480 synthetic peptide variants were assessed for antileishmanial activity against Leishmania donovani. One hundred seventy-two peptide variants exhibited 50% inhibitory concentration (IC50) values below 20 μM against axenic amastigotes, with 60 peptide variants in the nanomolar range. Nine peptide variants exhibited potent activity against intracellular amastigotes with observed IC50 values of <4 μM and limited in vitro host cell toxicity, making them worthy of further drug development. Our work demonstrates that minimal bioactive domains of naturally existing bacteriocins can be synthetically engineered to increase membrane penetration against Leishmania spp. with minimal host cytotoxicity, holding the promise of novel, potent antileishmanial therapies. IMPORTANCE Leishmaniasis is a neglected tropical disease caused by protozoan parasites of the genus Leishmania. There are three primary clinical forms, cutaneous, mucocutaneous, and visceral, with visceral leishmaniasis being fatal if left untreated. Current drug treatments are less than ideal, especially in resource-limited areas, due to the difficult administration and treatment regimens as well as the high cost and the emergence of drug resistance. Identifying potent antileishmanial agents is of the utmost importance. We utilized rational design techniques to synthesize enterocin AS-48 and AS-48-like bacteriocin-based peptides and screened these peptides against L. donovani using a fluorescence-based phenotypic assay. Our results suggest that bacteriocins, specifically these rationally designed AS-48-like peptides, are promising leads for further development as antileishmanial drugs.

PPARβ/δ-Interfering Peptide Enhanced Mesenchymal Stromal Cell Immunoregulatory Properties

Background

Mesenchymal stem/stromal cells (MSCs) have been widely used for their therapeutic properties in many clinical applications including osteoarthritis. Despite promising preclinical results showing the ability of MSC to reduce the clinical severity of osteoarthritis (OA) in experimental animal models, the benefits of intra-articular injection of MSC in OA patients are limited to the short term. In this regard, it is anticipated that improving the properties of MSC may collectively enhance their long-term beneficial effects on OA.

Methods and Results

Recently, we have shown that PPARβ/δ inhibition using a commercially available antagonist in murine MSC increases their immunoregulatory potential in vitro as well as their therapeutic potential in an experimental murine arthritis model. Here, we relied on an innovative strategy to inhibit PPARβ/δ:NF-κB TF65 subunit interaction in human MSC by designing and synthesizing an interfering peptide, referred to PP11. Through RT-qPCR experiments, we evidenced that the newly synthesized PP11 peptide reduced the expression level of PDK4, a PPARβ/δ target gene, but did not modify the expression levels of ACOX1 and CPT1A, PPARα target genes, and FABP4, a PPARγ target gene compared with untreated human MSC. Moreover, we showed that human MSCs pretreated with PP11 exhibit a significantly higher capacity to inhibit the proliferation of activated PBMC and to decrease the frequency of M1-like macrophages.

Conclusions

We designed and synthesized an interfering peptide that potently and specifically blocks PPARβ/δ activity with concomitant enhancement of MSC immunoregulatory properties.

Small Peptides in the Detection of Mycotoxins and Their Potential Applications in Mycotoxin Removal

Mycotoxins pose significant risks to humans and livestock. In addition, contaminated food- and feedstuffs can only be discarded, leading to increased economic losses and potential ecological pollution. Mycotoxin removal and real-time toxin level monitoring are effective approaches to solve this problem. As a hot research hotspot, small peptides derived from phage display peptide libraries, combinatorial peptide libraries, and rational design approaches can act as coating antigens, competitive antigens, and anti-immune complexes in immunoassays for the detection of mycotoxins. Furthermore, as a potential approach to mycotoxin degradation, small peptides can mimic the natural enzyme catalytic site to construct artificial enzymes containing oxidoreductases, hydrolase, and lyase activities. In summary, with the advantages of mature synthesis protocols, diverse structures, and excellent biocompatibility, also sharing their chemical structure with natural proteins, small peptides are widely used for mycotoxin detection and artificial enzyme construction, which have promising applications in mycotoxin degradation. This paper mainly reviews the advances of small peptides in the detection of mycotoxins, the construction of peptide-based artificial enzymes, and their potential applications in mycotoxin control.

Characterization of the Binding Behavior of Specific Cobalt and Nickel Ion-Binding Peptides Identified by Phage Surface Display

In recent years, the application focus of phage surface display (PSD) technology has been extended to the identification of metal ion-selective peptides. In previous studies, two phage clones—a nickel-binding one with the peptide motif CNAKHHPRCGGG and a cobalt-binding one with the peptide motif CTQMLGQLCGGG—were isolated, and their binding ability to metal-loaded NTA agarose beads was investigated. Here, the free cyclic peptides are characterized by UV/VIS spectroscopy with respect to their binding capacity for the respective target ion and in crossover experiments for the other ion by isothermal titration calorimetry (ITC) in different buffer systems. This revealed differences in selectivity and affinity. The cobalt-specific peptide is very sensitive to different buffers; it has a 20-fold higher affinity for cobalt and nickel under suitable conditions. The nickel-specific peptide binds more moderately and robustly in different buffers but only selectively to nickel.

AmyP53, a Therapeutic Peptide Candidate for the Treatment of Alzheimer’s and Parkinson’s Disease: Safety, Stability, Pharmacokinetics Parameters and Nose-to Brain Delivery

Neurodegenerative disorders are a major public health issue. Despite decades of research efforts, we are still seeking an efficient cure for these pathologies. The initial paradigm of large aggregates of amyloid proteins (amyloid plaques, Lewis bodies) as the root cause of Alzheimer’s and Parkinson’s diseases has been mostly dismissed. Instead, membrane-bound oligomers forming Ca²⁺-permeable amyloid pores are now considered appropriate targets for these diseases. Over the last 20 years, our group deciphered the molecular mechanisms of amyloid pore formation, which appeared to involve a common pathway for all amyloid proteins, including Aβ (Alzheimer) and α-synuclein (Parkinson). We then designed a short peptide (AmyP53), which prevents amyloid pore formation by targeting gangliosides, the plasma membrane receptors of amyloid proteins. Herein, we show that aqueous solutions of AmyP53 are remarkably stable upon storage at temperatures up to 45 °C for several months. AmyP53 appeared to be more stable in whole blood than in plasma. Pharmacokinetics studies in rats demonstrated that the peptide can rapidly and safely reach the brain after intranasal administration. The data suggest both the direct transport of AmyP53 via the olfactory bulb (and/or the trigeminal nerve) and an indirect transport via the circulation and the blood–brain barrier. In vitro experiments confirmed that AmyP53 is as active as cargo peptides in crossing the blood–brain barrier, consistent with its amino acid sequence specificities and physicochemical properties. Overall, these data open a route for the use of a nasal spray formulation of AmyP53 for the prevention and/or treatment of Alzheimer’s and Parkinson’s diseases in future clinical trials in humans.

High-Throughput Synthesis of Thin Films for the Discovery of Energy Materials: A Perspective

Thin films are an integral part of many electronic and optoelectronic devices. They also provide an excellent platform for material characterization. Therefore, strategies for the fabrication of thin films are constantly developed and have significantly benefited from the advent of high-throughput synthesis (HTS) platforms. This perspective summarizes recent advances in HTS of thin films from experimentalists’ point of view. The work analyzes general strategies of HTS and then discusses their use in developing new energy materials for applications that rely on thin films, such as solar cells, light-emitting diodes, batteries, superconductors, and thermoelectrics. The perspective also summarizes some key challenges and opportunities in the HTS of thin films.

Design and selection of peptides to block the SARS-CoV-2 receptor binding domain by molecular docking

The novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is currently one of the most contagious viruses in existence and the cause of the worst pandemic in this century, COVID-19. SARS-CoV-2 infection begins with the recognition of the cellular receptor angiotensin converting enzyme-2 by its spike glycoprotein receptor-binding domain (RBD). Thus, the use of small peptides to neutralize the infective mechanism of SARS-CoV-2 through the RBD is an interesting strategy. The binding ability of 104 peptides (University of Nebraska Medical Center's Antimicrobial Peptide Database) to the RBD was assessed using molecular docking. Based on the molecular docking results, peptides with great affinity to the RBD were selected. The most common amino acids involved in the recognition of the RBD were identified to design novel peptides based on the number of hydrogen bonds that were formed. At physiological pH, these peptides are almost neutral and soluble in aqueous media. Interestingly, several peptides showed the capability to bind to the active surface area of the RBD of the Wuhan strain, as well as to the RBD of the Delta variant and other SARS-Cov-2 variants. Therefore, these peptides have promising potential in the treatment of the COVID-19 disease caused by different variants of SARS-CoV-2. This research work will be focused on the molecular docking of peptides by molecular dynamics, in addition to an analysis of the possible interaction of these peptides with physiological proteins. This methodology could be extended to design peptides that are active against other viruses.

Emerging Computational Approaches for Antimicrobial Peptide Discovery

In the last two decades many reports have addressed the application of artificial intelligence (AI) in the search and design of antimicrobial peptides (AMPs). AI has been represented by machine learning (ML) algorithms that use sequence-based features for the discovery of new peptidic scaffolds with promising biological activity. From AI perspective, evolutionary algorithms have been also applied to the rational generation of peptide libraries aimed at the optimization/design of AMPs. However, the literature has scarcely dedicated to other emerging non-conventional in silico approaches for the search/design of such bioactive peptides. Thus, the first motivation here is to bring up some non-standard peptide features that have been used to build classical ML predictive models. Secondly, it is valuable to highlight emerging ML algorithms and alternative computational tools to predict/design AMPs as well as to explore their chemical space. Another point worthy of mention is the recent application of evolutionary algorithms that actually simulate sequence evolution to both the generation of diversity-oriented peptide libraries and the optimization of hit peptides. Last but not least, included here some new considerations in proteogenomic analyses currently incorporated into the computational workflow for unravelling AMPs in natural sources.

iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model

The COVID-19 pandemic caused several million deaths worldwide. Development of anti-coronavirus drugs is thus urgent. Unlike conventional non-peptide drugs, antiviral peptide drugs are highly specific, easy to synthesize and modify, and not highly susceptible to drug resistance. To reduce the time and expense involved in screening thousands of peptides and assaying their antiviral activity, computational predictors for identifying anti-coronavirus peptides (ACVPs) are needed. However, few experimentally verified ACVP samples are available, even though a relatively large number of antiviral peptides (AVPs) have been discovered. In this study, we attempted to predict ACVPs using an AVP dataset and a small collection of ACVPs. Using conventional features, a binary profile and a word-embedding word2vec (W2V), we systematically explored five different machine learning methods: Transformer, Convolutional Neural Network, bidirectional Long Short-Term Memory, Random Forest (RF) and Support Vector Machine. Via exhaustive searches, we found that the RF classifier with W2V consistently achieved better performance on different datasets. The two main controlling factors were: (i) the dataset-specific W2V dictionary was generated from the training and independent test datasets instead of the widely used general UniProt proteome and (ii) a systematic search was conducted and determined the optimal k-mer value in W2V, which provides greater discrimination between positive and negative samples. Therefore, our proposed method, named iACVP, consistently provides better prediction performance compared with existing state-of-the-art methods. To assist experimentalists in identifying putative ACVPs, we implemented our model as a web server accessible via the following link: http://kurata35.bio.kyutech.ac.jp/iACVP.

Sequencing the Origins of Life

One goal of origins of life research is to understand how primitive informational and catalytic biopolymers emerged and evolved. Recently, a number of sequencing techniques have been applied to analysis of replicating and evolving primitive biopolymer systems, providing a sequence-specific and high-resolution view of primitive chemical processes. Here, we review application of sequencing techniques to analysis of synthetic and primitive nucleic acids and polypeptides. This includes next-generation sequencing of primitive polymerization and evolution processes, followed by discussion of other novel biochemical techniques that could contribute to sequence analysis of primitive biopolymer driven chemical systems. Further application of sequencing to origins of life research, perhaps as a life detection technology, could provide insight into the origin and evolution of informational and catalytic biopolymers on early Earth or elsewhere.

Basic Principles and Recent Advances in Magnetic Cell Separation

Magnetic cell separation has become a key methodology for the isolation of target cell populations from biological suspensions, covering a wide spectrum of applications from diagnosis and therapy in biomedicine to environmental applications or fundamental research in biology. There now exists a great variety of commercially available separation instruments and reagents, which has permitted rapid dissemination of the technology. However, there is still an increasing demand for new tools and protocols which provide improved selectivity, yield and sensitivity of the separation process while reducing cost and providing a faster response. This review aims to introduce basic principles of magnetic cell separation for the neophyte, while giving an overview of recent research in the field, from the development of new cell labeling strategies to the design of integrated microfluidic cell sorters and of point-of-care platforms combining cell selection, capture, and downstream detection. Finally, we focus on clinical, industrial and environmental applications where magnetic cell separation strategies are amongst the most promising techniques to address the challenges of isolating rare cells.

Ligand Selection for Affinity Chromatography Using Phage Display

Phage display coupled with in vitro affinity selection to mimic evolutionary principles has propelled the discovery of specific binding peptides and proteins for diverse applications, including affinity chromatography. By tailoring screening conditions, ligands with desired predefined properties, such as pH- or ion strength-responsive binding, can be identified from phage-displayed combinatorial peptide libraries. Initial hit peptides can be further optimized through directed evolution by focused mutagenesis and rescreening. Quantitative analysis of eluted binders with next-generation sequencing (NGS) assists in reducing enrichment bias and simplifies picking the most promising ligand candidate(s) through enrichment ranking. We describe, in detail, procedures of ligand selection for affinity chromatography using peptide phage display library screening, focused mutagenesis, and NGS. Furthermore, we outline the subsequent workflow for ligand characterization and affinity column construction.

Plant Antimicrobial Peptides as Potential Tool for Topic Treatment of Hidradenitis Suppurativa

Among chronic skin autoinflammatory diseases, Hidradenitis Suppurativa (HS) stands out for its chronicity, highly variable condition, and profound impact on the patients' quality of life. HS is characterized by suppurative skin lesions in diverse body areas, including deep-seated painful nodules, abscesses, draining sinus, and bridged scars, among others, with typical topography. To date, HS is considered a refractory disease and medical treatments aim to reduce the incidence, the infection, and the pain of the lesions. For this purpose, different classes of drugs, including anti-inflammatory molecules, antibiotics and biological drugs are being used. Antimicrobial peptides (AMPs), also called defense peptides, emerge as a new class of therapeutic compounds, with broad-spectrum antimicrobial action, in addition to reports on their anti-inflammatory, healing, and immunomodulating activity. Such peptides are present in prokaryotes and eukaryotes, as part of the innate eukaryotic immune system. It has been proposed that a deregulation in the expression of AMPs in human epithelial tissues of HS patients may be associated with the etiology of this skin disease. In this scenario, plant AMPs stand out for their richness, diversity of types, and broad antimicrobial effects, with potential application for topical systemic use in patients affected by HS.

Peptibody Based on FGFR1-Binding Peptides From the FGF4 Sequence as a Cancer-Targeting Agent

Targeted therapies are a promising alternative to conventional chemotherapy, with an increasing number of therapeutics targeting specific molecular aberrancies in cancer cells. One of the emerging targets for directed cancer treatments is fibroblast growth factor receptors (FGFRs), which are known to be involved in the pathogenesis and progression of multiple cancer types, specially in lung, bladder, and breast cancers. Here, we are demonstrating the development of the FGFR1-targeting agent based on the interactome screening approach, based on the isolation of binding regions from ligands interacting with the receptor. The parallel analysis by FGFR1 pull-down of chymotryptic peptides coupled with MS analysis, and PepSpot analysis yielded equivalent peptide sequences from FGF4, one of the FGFR1 ligands. Three sequences served as a basis for peptibody (Fc-fusion) generation, to overcome clinical limitations of peptidic agents, and two of them showed favorable FGFR1-binding in vitro and FGFR1-dependent internalization into cells. To validate if developed FGFR1-targeting peptibodies can be used for drug delivery, similar to the well-established concept of antibody-drug conjugates (ADCs), peptibodyF4_1 was successfully conjugated with monomethylauristatin E (MMAE), and has shown significant and specific toxicity toward FGFR1-expressing lung cancer cell lines, with nanomolar EC50 values. Essentially, the development of new effective FGFR1 binders that comprise the naturally occurring FGFR-recognition peptides and Fc region ensuring high plasma stability, and long bloodstream circulation is an interesting strategy expanding targeted anticancer agents' portfolio. Furthermore, identifying peptides effectively binding the receptor from sequences of its ligands is not limited to FGFRs and is an approach versatile enough to be a basis for a new peptide/peptibodies development strategy.

APPTEST is a novel protocol for the automatic prediction of peptide tertiary structures

Good knowledge of a peptide's tertiary structure is important for understanding its function and its interactions with its biological targets. APPTEST is a novel computational protocol that employs a neural network architecture and simulated annealing methods for the prediction of peptide tertiary structure from the primary sequence. APPTEST works for both linear and cyclic peptides of 5-40 natural amino acids. APPTEST is computationally efficient, returning predicted structures within a number of minutes. APPTEST performance was evaluated on a set of 356 test peptides; the best structure predicted for each peptide deviated by an average of 1.9Å from its experimentally determined backbone conformation, and a native or near-native structure was predicted for 97% of the target sequences. A comparison of APPTEST performance with PEP-FOLD, PEPstrMOD and PepLook across benchmark datasets of short, long and cyclic peptides shows that on average APPTEST produces structures more native than the existing methods in all three categories. This innovative, cutting-edge peptide structure prediction method is available as an online web server at https://research.timmons.eu/apptest, facilitating in silico study and design of peptides by the wider research community.

Peptide Affinity Chromatography Applied to Therapeutic Antibodies Purification

The interest in therapeutic monoclonal antibodies (mAbs) has significantly grown in the pharmaceutical industry, exceeding 100 FDA mAbs approved. Although the upstream processing of their industrial production has been significantly improved in the last years, the downstream processing still depends on immobilized protein A affinity chromatography. The high cost, low capacity and short half-life of immobilized protein A chromatography matrices, encouraged the design of alternative short-peptide ligands for mAb purification. Most of these peptides have been obtained by screening combinatorial peptide libraries. These low-cost ligands can be easily produced by solid-phase peptide synthesis and can be immobilized on chromatographic supports, thus obtaining matrices with high capacity and selectivity. Furthermore, matrices with immobilized peptide ligands have longer half-life than those with protein A due to the higher stability of the peptides. In this review the design and synthesis of peptide ligands, their immobilization on chromatographic supports and the evaluation of the affinity supports for their application in mAb purification is described.

Allosteric Modulator Leads Hiding in Plain Site: Developing Peptide and Peptidomimetics as GPCR Allosteric Modulators

Allosteric modulators (AMs) of G-protein coupled receptors (GPCRs) are desirable drug targets because they can produce fewer on-target side effects, improved selectivity, and better biological specificity (e.g., biased signaling or probe dependence) than orthosteric drugs. An underappreciated source for identifying AM leads are peptides and proteins-many of which were evolutionarily selected as AMs-derived from endogenous protein-protein interactions (e.g., transducer/accessory proteins), intramolecular receptor contacts (e.g., pepducins or extracellular domains), endogenous peptides, and exogenous libraries (e.g., nanobodies or conotoxins). Peptides offer distinct advantages over small molecules, including high affinity, good tolerability, and good bioactivity, and specific disadvantages, including relatively poor metabolic stability and bioavailability. Peptidomimetics are molecules that combine the advantages of both peptides and small molecules by mimicking the peptide's chemical features responsible for bioactivity while improving its druggability. This review 1) discusses sources and strategies to identify peptide/peptidomimetic AMs, 2) overviews strategies to convert a peptide lead into more drug-like "peptidomimetic," and 3) critically analyzes the advantages, disadvantages, and future directions of peptidomimetic AMs. While small molecules will and should play a vital role in AM drug discovery, peptidomimetics can complement and even exceed the advantages of small molecules, depending on the target, site, lead, and associated factors.

Improved Microbial Fuel Cell Performance by Engineering E. coli for Enhanced Affinity to Gold

Microorganism affinity for surfaces can be controlled by introducing material binding motifs into proteins such as fimbrial tip and outer membrane proteins. Here, controlled surface affinity is used to manipulate and enhance electrical power production in a typical bioelectrochemical system, a microbial fuel cell (MFC). Specifically, gold-binding motifs of various affinity were introduced into two scaffolds in Escherichia coli: eCPX, a modified version of outer membrane protein X (OmpX), and FimH, the tip protein of the fimbriae. The behavior of these strains on gold electrodes was examined in small-scale (240 µL) MFCs and 40 mL U-tube MFCs. A clear correlation between the affinity of a strain for a gold surface and the peak voltage produced during MFC operation is shown in the small-scale MFCs; strains displaying peptides with high affinity for gold generate potentials greater than 80 mV while strains displaying peptides with minimal affinity to gold produce potentials around 30 mV. In the larger MFCs, E. coli strains with high affinity to gold exhibit power densities up to 0.27 mW/m2, approximately a 10-fold increase over unengineered strains lacking displayed peptides. Moreover, in the case of the modified FimH strains, this increased power production is sustained for five days.

Role of Peptides in Diagnostics

The specificity of a diagnostic assay depends upon the purity of the biomolecules used as a probe. To get specific and accurate information of a disease, the use of synthetic peptides in diagnostics have increased in the last few decades, because of their high purity profile and ability to get modified chemically. The discovered peptide probes are used either in imaging diagnostics or in non-imaging diagnostics. In non-imaging diagnostics, techniques such as Enzyme-Linked Immunosorbent Assay (ELISA), lateral flow devices (i.e., point-of-care testing), or microarray or LC-MS/MS are used for direct analysis of biofluids. Among all, peptide-based ELISA is considered to be the most preferred technology platform. Similarly, peptides can also be used as probes for imaging techniques, such as single-photon emission computed tomography (SPECT) and positron emission tomography (PET). The role of radiolabeled peptides, such as somatostatin receptors, interleukin 2 receptor, prostate specific membrane antigen, αβ3 integrin receptor, gastrin-releasing peptide, chemokine receptor 4, and urokinase-type plasminogen receptor, are well established tools for targeted molecular imaging ortumor receptor imaging. Low molecular weight peptides allow a rapid clearance from the blood and result in favorable target-to-non-target ratios. It also displays a good tissue penetration and non-immunogenicity. The only drawback of using peptides is their potential low metabolic stability. In this review article, we have discussed and evaluated the role of peptides in imaging and non-imaging diagnostics. The most popular non-imaging and imaging diagnostic platforms are discussed, categorized, and ranked, as per their scientific contribution on PUBMED. Moreover, the applicability of peptide-based diagnostics in deadly diseases, mainly COVID-19 and cancer, is also discussed in detail.

Focused peptide library screening as a route to a superior affinity ligand for antibody purification

Affinity chromatography is the linchpin of antibody downstream processing and typically relies on bacterial immunoglobulin (Ig)-binding proteins, epitomized by staphylococcal protein A-based ligands. However, such affinity ligands are fairly costly and suffer from chemical instability, leading to ligand denaturation and leaching from chromatographic support. Innovations in this area are aimed at developing robust and highly selective antibody ligands capable of withstanding harsh column sanitization conditions. We report the development and first-stage characterization of a selective short linear peptide ligand of the IgG Fc region capable of capturing all four IgG subclasses. The ligand was discovered through in vitro directed evolution. A focused phage-display library based on a previously identified peptide lead was subjected to a single-round screen against a pool of human IgG. The hits were identified with next-generation sequencing and ranked according to the enrichment ratio relative to their frequency in the pre-screened library. The top enriched peptide GSYWYNVWF displaying highest affinity for IgG was coupled to bromohydrin-activated agarose beads via a branched linker. The resulting affinity matrix was characterized with a dynamic binding capacity of approx. 43 mg/mL, on par with commercially employed protein A-based resin.

Design of Thioether Cyclic Peptide Scaffolds with Passive Permeability and Oral Exposure

Advances in the design of permeable peptides and in the synthesis of large arrays of macrocyclic peptides with diverse amino acids have evolved on parallel but independent tracks. Less precedent combines their respective attributes, thereby limiting the potential to identify permeable peptide ligands for key targets. Herein, we present novel 6-, 7-, and 8-mer cyclic peptides (MW 774-1076 g·mol-1) with passive permeability and oral exposure that feature the amino acids and thioether ring-closing common to large array formats, including DNA- and RNA-templated synthesis. Each oral peptide herein, selected from virtual libraries of partially N-methylated peptides using in silico methods, reflects the subset consistent with low energy conformations, low desolvation penalties, and passive permeability. We envision that, by retaining the backbone N-methylation pattern and consequent bias toward permeability, one can generate large peptide arrays with sufficient side chain diversity to identify permeability-biased ligands to a variety of protein targets.

A Simplified Amino Acidic Alphabet to Unveil the T-Cells Receptors Antigens: A Computational Perspective

The exposure to pathogens triggers the activation of adaptive immune responses through antigens bound to surface receptors of antigen presenting cells (APCs). T cell receptors (TCR) are responsible for initiating the immune response through their physical direct interaction with antigen-bound receptors on the APCs surface. The study of T cell interactions with antigens is considered of crucial importance for the comprehension of the role of immune responses in cancer growth and for the subsequent design of immunomodulating anticancer drugs. RNA sequencing experiments performed on T cells represented a major breakthrough for this branch of experimental molecular biology. Apart from the gene expression levels, the hypervariable CDR3α/β sequences of the TCR loops can now be easily determined and modelled in the three dimensions, being the portions of TCR mainly responsible for the interaction with APC receptors. The most direct experimental method for the investigation of antigens would be based on peptide libraries, but their huge combinatorial nature, size, cost, and the difficulty of experimental fine tuning makes this approach complicated time consuming, and costly. We have implemented in silico methodology with the aim of moving from CDR3α/β sequences to a library of potentially antigenic peptides that can be used in immunologically oriented experiments to study T cells’ reactivity. To reduce the size of the library, we have verified the reproducibility of experimental benchmarks using the permutation of only six residues that can be considered representative of all ensembles of 20 natural amino acids. Such a simplified alphabet is able to correctly find the poses and chemical nature of original antigens within a small subset of ligands of potential interest. The newly generated library would have the advantage of leading to potentially antigenic ligands that would contribute to a better understanding of the chemical nature of TCR-antigen interactions. This step is crucial in the design of immunomodulators targeted towards T-cells response as well as in understanding the first principles of an immune response in several diseases, from cancer to autoimmune disorders.

Extended yeast surface display linkers enhance the enrichment of ligands in direct mammalian cell selections

Selections of yeast-displayed ligands on mammalian cell monolayers benefit from high target expression and nanomolar affinity, which are not always available. Prior work extending the yeast-protein linker from 40 to 80 amino acids improved yield and enrichment but is hypothesized to be below the optimal length, prompting evaluation of an extended amino acid linker. A 641-residue linker provided enhanced enrichment with a 2-nM affinity fibronectin ligand and 105 epidermal growth factor receptors (EGFR) per cell (14 ± 2 vs. 8 ± 1, P = 0.008) and a >600-nM affinity ligand, 106 EGFR per cell system (23 ± 7 vs. 0.8 ± 0.2, P = 0.004). Enhanced enrichment was also observed with a 310-nM affinity affibody ligand and 104 CD276 per cell, suggesting a generalizable benefit to other scaffolds and targets. Spatial modeling of the linker suggests that improved extracellular accessibility of ligand enables the observed enrichment under conditions not previously possible.

Small and Simple, yet Sturdy: Conformationally Constrained Peptides with Remarkable Properties

The sheer size and vast chemical space (i.e., diverse repertoire and spatial distribution of functional groups) underlie peptides’ ability to engage in specific interactions with targets of various structures. However, the inherent flexibility of the peptide chain negatively affects binding affinity and metabolic stability, thereby severely limiting the use of peptides as medicines. Imposing conformational constraints to the peptide chain offers to solve these problems but typically requires laborious structure optimization. Alternatively, libraries of constrained peptides with randomized modules can be screened for specific functions. Here, we present the properties of conformationally constrained peptides and review rigidification chemistries/strategies, as well as synthetic and enzymatic methods of producing macrocyclic peptides. Furthermore, we discuss the in vitro molecular evolution methods for the development of constrained peptides with pre-defined functions. Finally, we briefly present applications of selected constrained peptides to illustrate their exceptional properties as drug candidates, molecular recognition probes, and minimalist catalysts.

Ultra-high-throughput SPE-MALDI workflow: Blueprint for efficient purification and screening of peptide libraries

At the forefront of synthetic endeavors in the pharmaceutical industry, including drug discovery and high-throughput screening, timelines are tight and large quantities of pure chemical targets are rarely available. In this regard, the development of novel and increasingly challenging chemistries requires a commensurate level of innovation to develop reliable analytical assays and purification workflows with rapid turnaround that enables accelerated pharmacological evaluation. A small-scale automation platform enabling high-throughput analysis and purification to streamline the selection of candidate leads would be a transformative advance. Herein, we introduce an automation-friendly solid-phase extraction-matrix-assisted laser desorption/ionization (SPE-MALDI) platform applied to the high-throughput purification and analysis of peptide libraries. This advance enabled us to purify peptides from microgram levels in less than a day with results comparable to traditional high-performance liquid chromatography-diode array detection-mass spectrometry (HPLC-DAD-MS).

Mutational Analysis of Ocriplasmin to Reduce Proteolytic and Autolytic Activity in Pichia pastoris

BACKGROUND

Ocriplasmin (Jetrea) is using for the treatment of symptomatic vitreomacular adhesion. This enzyme undergoes rapid inactivation and limited activity duration as a result of its autolytic nature after injection within the eye. Moreover, the proteolytic activity can cause photoreceptor damage, which may result in visual impairment in more serious cases.

RESULTS

The present research aimed to reduce the disadvantages of ocriplasmin using site-directed mutagenesis. To reduce the autolytic activity of ocriplasmin in the first variant, lysine 156 changed to glutamic acid and, in the second variant for the proteolytic activity reduction, alanine 59 mutated to threonine. The third variant contained both mutations. Expression of wild type and three mutant variants of ocriplasmin constructs were done in the Pichia pastoris expression system. The mutant variants were analyzed in silico and in vitro and compared to the wild type. The kinetic parameters of ocriplasmin variants showed both variants with K156E substitution were more resistant to autolytic degradation than wild-type. These variants also exhibited reduced Kcat and Vmax values. An increase in their Km values, leading to a decreased catalytic efficiency (the Kcat/Km ratio) of autolytic and mixed variants. Moreover, in the variant with A59T mutation, Kcat and Vmax values have reduced compared to wild type. The mix variants showed the most increase in Km value (almost 2-fold) as well as reduced enzymatic affinity to the substrate. Thus, the results indicated that combined mutations at the ocriplasmin sequence were more effective compared with single mutations.

CONCLUSIONS

The results indicated such variants represent valuable tools for the investigation of therapeutic strategies aiming at the non-surgical resolution of vitreomacular adhesion.

Design, Screening, and Testing of Non-Rational Peptide Libraries with Antimicrobial Activity: In Silico and Experimental Approaches

One of the challenges of modern biotechnology is to find new routes to mitigate the resistance to conventional antibiotics. Antimicrobial peptides (AMPs) are an alternative type of biomolecules, naturally present in a wide variety of organisms, with the capacity to overcome the current microorganism resistance threat. Here, we reviewed our recent efforts to develop a new library of non-rationally produced AMPs that relies on bacterial genome inherent diversity and compared it with rationally designed libraries. Our approach is based on a four-stage workflow process that incorporates the interplay of recent developments in four major emerging technologies: artificial intelligence, molecular dynamics, surface-display in microorganisms, and microfluidics. Implementing this framework is challenging because to obtain reliable results, the in silico algorithms to search for candidate AMPs need to overcome issues of the state-of-the-art approaches that limit the possibilities for multi-space data distribution analyses in extremely large databases. We expect to tackle this challenge by using a recently developed classification algorithm based on deep learning models that rely on convolutional layers and gated recurrent units. This will be complemented by carefully tailored molecular dynamics simulations to elucidate specific interactions with lipid bilayers. Candidate AMPs will be recombinantly-expressed on the surface of microorganisms for further screening via different droplet-based microfluidic-based strategies to identify AMPs with the desired lytic abilities. We believe that the proposed approach opens opportunities for searching and screening bioactive peptides for other applications.

Engineering protein fragments via evolutionary and protein-protein interaction algorithms: de novo design of peptide inhibitors for FO F1 -ATP synthase

Enzyme subunit interfaces have remarkable potential in drug design as both target and scaffold for their own inhibitors. We show an evolution-driven strategy for the de novo design of peptide inhibitors targeting interfaces of the Escherichia coli FoF1-ATP synthase as a case study. The evolutionary algorithm ROSE was applied to generate diversity-oriented peptide libraries by engineering peptide fragments from ATP synthase interfaces. The resulting peptides were scored with PPI-Detect, a sequence-based predictor of protein-protein interactions. Two selected peptides were confirmed by in vitro inhibition and binding tests. The proposed methodology can be widely applied to design peptides targeting relevant interfaces of enzymatic complexes.

Cyanine Conjugate-Based Biomedical Imaging Probes

Cyanine is a class of fluorescent dye with meritorious fluorescence properties and has motivated numerous researchers to explore its imaging capabilities by miscellaneous structural modification and functionalization strategies. The covalent conjugation with other functional molecules represents a distinctive design strategy and has shown immense potential in both basic and clinical research. This review article summarizes recent achievements in cyanine conjugate-based probes for biomedical imaging. Particular attention is paid to the conjugation with targeting warheads and other contrast agents for targeted fluorescence imaging and multimodal imaging, respectively. Additionally, their clinical potential in cancer diagnostics is highlighted and some concurrent impediments for clinical translation are discussed.

HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks

The growing prevalence of resistance to antibiotics motivates the search for new antibacterial agents. Antimicrobial peptides are a diverse class of well-studied membrane-active peptides which function as part of the innate host defence system, and form a promising avenue in antibiotic drug research. Some antimicrobial peptides exhibit toxicity against eukaryotic membranes, typically characterised by hemolytic activity assays, but currently, the understanding of what differentiates hemolytic and non-hemolytic peptides is limited. This study leverages advances in machine learning research to produce a novel artificial neural network classifier for the prediction of hemolytic activity from a peptide's primary sequence. The classifier achieves best-in-class performance, with cross-validated accuracy of [Formula: see text] and Matthews correlation coefficient of 0.71. This innovative classifier is available as a web server at https://research.timmons.eu/happenn , allowing the research community to utilise it for in silico screening of peptide drug candidates for high therapeutic efficacies.

Surface Display Technology for Biosensor Applications: A Review

Surface display is a recombinant technology that expresses target proteins on cell membranes and can be applied to almost all types of biological entities from viruses to mammalian cells. This technique has been used for various biotechnical and biomedical applications such as drug screening, biocatalysts, library screening, quantitative assays, and biosensors. In this review, the use of surface display technology in biosensor applications is discussed. In detail, phage display, bacterial surface display of Gram-negative and Gram-positive bacteria, and eukaryotic yeast cell surface display systems are presented. The review describes the advantages of surface display systems for biosensor applications and summarizes the applications of surface displays to biosensors.

Peptides for Health Benefits 2019

In recent years, peptides have received increased interest in pharmaceutical, food, cosmetics and various other fields [...].