Computational design of peptide ligands for ochratoxin A

Prediction of promiscuous multiepitope-based peptide vaccine against RdRp of rotavirus using immunoinformatics studies

Rotavirus, a dsRNA virus in the Reoviridae family, shows a segmented genome. The VP1 gene encodes the RNA-dependent RNA polymerase (RdRp). This study aims to develop a multiepitope-based vaccine targeting RdRp using immunoinformatic approaches. In this study, 100 available nucleotide sequences of VP1-Rotavirus belonging to different strains across the world were retrieved from NCBI database. The selected sequences were aligned, and a global consensus sequence was developed by using CLC work bench. The study involved immunoinformatic approaches and molecular docking studies to reveal the promiscuous epitopes that can be eventually used as active vaccine candidates for Rotavirus. In total, 27 highly immunogenic, antigenic, and non-allergenic T-cell and B-cell epitopes were predicted for the Multiepitope vaccine (MEV) against rotavirus. It was also observed that MEV can prove to be effective worldwide due to its high population coverage, demonstrating the consistency of this vaccine. Moreover, there is a high docking interaction and immunological response with a binding score of -50.2 kcal/mol, suggesting the vaccine's efficacy. Toll-like receptors (TLRs) also suggest that the vaccine is physiologically and immunologically effective. Collectively, our data point to an effective MEV against rotavirus that can effectively reduce viral infections and improve the health status worldwide.

Advances in screening, synthesis, modification, and biomedical applications of peptides and peptide aptamers

Peptides and peptide aptamers have emerged as promising molecules for a wide range of biomedical applications due to their unique properties and versatile functionalities. The screening strategies for identifying peptides and peptide aptamers with desired properties are discussed, including high-throughput screening, display screening technology, and in silico design approaches. The synthesis methods for the efficient production of peptides and peptide aptamers, such as solid-phase peptide synthesis and biosynthesis technology, are described, along with their advantages and limitations. Moreover, various modification techniques are explored to enhance the stability, specificity, and pharmacokinetic properties of peptides and peptide aptamers. This includes chemical modifications, enzymatic modifications, biomodifications, genetic engineering modifications, and physical modifications. Furthermore, the review highlights the diverse biomedical applications of peptides and peptide aptamers, including targeted drug delivery, diagnostics, and therapeutic. This review provides valuable insights into the advancements in screening, synthesis, modification, and biomedical applications of peptides and peptide aptamers. A comprehensive understanding of these aspects will aid researchers in the development of novel peptide-based therapeutics and diagnostic tools for various biomedical challenges.

Degradation of ochratoxins A and B by lipases: A kinetic study unraveled by molecular modeling

Mycotoxins are toxic substances produced by fungi and, frequently, different mycotoxins cooccur in food commodities. Ochratoxin A (OTA) and Ochratoxin B (OTB) may co-occur in a variety of foods, like red wines and wheat, presenting a significant risk of population exposure. In this study, we investigated the potential of five lipases (Candida rugosa Lipase, Candida antarctica B Lipase, Thermomyces lanuginosus Lipase, Amano Lipase A from Aspergillus niger (ANL) and Porcine Pancreas Lipase (PPL)) to hydrolyze OTA and OTB into non-hazardous products. Only ANL and PPL degraded both substrates, however, with varying degrees of efficiency. PPL completely degraded OTB (9 h), but only 43% of OTA (25 h). Molecular simulations indicated a high binding energy of OTA to PPL, that can be explained by the impact of the chlorine group, impairing hydrolysis. ANL was able to completely degrade both mycotoxins, OTA in 3 h and OTB in 10 h. The ANL enzyme showed also high specificity to OTA, however, the activity of this enzyme is not affected by chlorine and hydrolyzes OTA faster than OTB. These two enzymes were found to be able to detoxify co-occurring ochratoxins A and B, making isolated enzymes an alternative to the direct use of microorganisms for mycotoxin mitigation in food.

Rationally designed peptide conjugated to gold nanoparticles for detection of aflatoxin B1 in point-of-care dot-blot assay

Aflatoxin B1 (AFB1) is a hepatotoxic and carcinogenic food contaminant. Although on-site paper-based detection is sensitive it depends on expensive antibodies which are difficult to raise against mycotoxins. Here, we rationally designed a high binding octapeptide, N-KSGKSKPR-C peptide for AFB1 detection, by molecular docking, as confirmed by indirect ELISA (K_d 323 nM). Further, conjugation of octapeptide with gold nanoparticles (26 nm) permitted its use as a visual detection agent in rapid, sensitive dot-blot assay (LOD 0.39 μg/kg). The assay displayed negligible cross-reactivity with co-contaminating mycotoxins. AFB1 recovery from spiked wheat sample was comparable by dot-blot (78-91 %) and HPLC (65-87 %). Evaluation of dot-blot using certified reference material and 146 food and feed samples showed high correlation R² = 0.87 with HPLC. The assay displayed high accuracy (91 %), sensitivity (71 %) and specificity (96.5 %). Therefore, the developed dot-blot assay holds promise for monitoring AFB1 contamination in food and feed.

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.

Recent Progress in Rapid Determination of Mycotoxins Based on Emerging Biorecognition Molecules: A Review

Mycotoxins are secondary metabolites produced by fungal species, which pose significant risk to humans and livestock. The mycotoxins which are produced from Aspergillus, Penicillium, and Fusarium are considered most important and therefore regulated in food- and feedstuffs. Analyses are predominantly performed by official laboratory methods in centralized labs by expert technicians. There is an urgent demand for new low-cost, easy-to-use, and portable analytical devices for rapid on-site determination. Most significant advances were realized in the field bioanalytical techniques based on molecular recognition. This review aims to discuss recent progress in the generation of native biomolecules and new bioinspired materials towards mycotoxins for the development of reliable bioreceptor-based analytical methods. After brief presentation of basic knowledge regarding characteristics of most important mycotoxins, the generation, benefits, and limitations of present and emerging biorecognition molecules, such as polyclonal (pAb), monoclonal (mAb), recombinant antibodies (rAb), aptamers, short peptides, and molecularly imprinted polymers (MIPs), are discussed. Hereinafter, the use of binders in different areas of application, including sample preparation, microplate- and tube-based assays, lateral flow devices, and biosensors, is highlighted. Special focus, on a global scale, is placed on commercial availability of single receptor molecules, test-kits, and biosensor platforms using multiplexed bead-based suspension assays and planar biochip arrays. Future outlook is given with special emphasis on new challenges, such as increasing use of rAb based on synthetic and naïve antibody libraries to renounce animal immunization, multiple-analyte test-kits and high-throughput multiplexing, and determination of masked mycotoxins, including stereoisomeric degradation products.

A new class of sensing elements for sensors: Clamp peptides for Zika virus

The design of a new class of selective and high affinity antibody mimetics termed clamp peptide (CP) that incorporate three short peptides structurally and mechanically mimicking a clamp is proposed as sensing elements for a reliable detection sensor platform. The CPs consist of two short peptides functioning as arms that recognize two different epitopes in the target protein and are connected by a third short peptide that acts as a hinge between the peptide arms. For the construction of CPs, we employed a rational design combined with computational methods. To illustrate our approach, we designed a CP that binds selectively to the envelope protein of the Zika virus (ZIKV). The virtual docking cycles were run maximizing the discrimination between ZIKV and Dengue virus (DENV) envelope proteins. DENV was chosen among the flavivirus family because it has high structural similarity with ZIKV. When employed in a colorimetric binding assay or in label-free electrochemical impedance sensor format, the CP was selective for ZIKV vs DENV particles showing detection limit under 10⁴ copies/mL, comparable to anti-ZIKV antibodies. Apparent dissociation binding constants (Kd) confirmed a better performance of CPs than mono-arm peptides (Kd of best CP = 162 nM ± 23 nM; Kd of best mono-arm peptide = 11.15 ± 2.76 μM). The performance of the assays based on CPs was also verified in serum and urine (diluted 1:10 and 1:1 respectively). The detection limits of CPs decreased about one order of magnitude for ZIKV detection in serum or urine, with a distinct analytical signal starting from 10⁵ copies/mL of ZIKV.

Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening

BACKGROUND

Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2.

METHODS

In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis.

RESULTS

The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant.

CONCLUSION

Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2.

Determine the Potential Epitope Based Peptide Vaccine Against Novel SARS-CoV-2 Targeting Structural Proteins Using Immunoinformatics Approaches

Coronaviruses (CoVs) belong to the Coronaviridae-family. The genus Beta-coronaviruses, are enveloped positive strand RNA viruses with club-like spikes at the surface with a unique replication process and a large RNA genome (∼25 kb). CoVs are known as one of the major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Recently, a new strain of coronavirus has been identified and named as SARS-CoV-2. A large number of COVID-19 (disease caused by SARS-CoV-2) cases are being diagnosed all over the World especially in China (Wuhan). COVID-19 showed high mortality rate exponentially, however, not even a single effective cure is being introduced yet against COVID-19. In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against COVID-19 for the development of a coronavirus peptide vaccine. Cytotoxic T-lymphocyte (CTL) and B-cell epitopes were predicted for SARS-CoV-2 coronavirus structural proteins (Spikes, Membrane, Envelope, and Nucleocapsid). The docking complexes of the top 10 epitopes having antigenic sites were analyzed led by binding affinity and binding interactional analyses of top ranked predicted peptides with the MHC-I HLA molecule. The predicted peptides may have potential to be used as peptide vaccine against COVID-19.

Molecular Design of Peptide-Fc Fusion Drugs

Background:

Peptide-Fc fusion drugs, also known as peptibodies, are a category of biological therapeutics in which the Fc region of an antibody is genetically fused to a peptide of interest. However, to develop such kind of drugs is laborious and expensive. Rational design is urgently needed.

Methods:

We summarized the key steps in peptide-Fc fusion technology and stressed the main computational resources, tools, and methods that had been used in the rational design of peptide-Fc fusion drugs. We also raised open questions about the computer-aided molecular design of peptide-Fc.

Results:

The design of peptibody consists of four steps. First, identify peptide leads from native ligands, biopanning, and computational design or prediction. Second, select the proper Fc region from different classes or subclasses of immunoglobulin. Third, fuse the peptide leads and Fc together properly. At last, evaluate the immunogenicity of the constructs. At each step, there are quite a few useful resources and computational tools.

Conclusion:

Reviewing the molecular design of peptibody will certainly help make the transition from peptide leads to drugs on the market quicker and cheaper.

Removal of ochratoxin A by a carboxypeptidase and peptides present in liquid cultures of Bacillus subtilis CW14

Ochratoxin A (OTA) is an important mycotoxin that contaminates a variety of agricultural products. The cell-free supernatant of Bacillus subtilis CW14 liquid cultures were reported previously to be capable of removing OTA efficiently. In this work, we examined several substances that are probably involved in this removal of OTA using in vitro experiments. The strain CW14 culture supernatant that was separated by ultrafiltration showed that the fractions collected at >10 kDa and <3 kDa had a significant ability to reduce OTA (84.9 and 74.8%, respectively) when incubated with 6 μg/ml OTA at 37 °C for 24 h. A putative metalloenzyme was responsible for the activity of the >10-kDa fraction, which was confirmed by the detrimental effects of heat treatments or addition of SDS, proteinase K, or EDTA. Subsequently, a carboxypeptidase (CP) gene that was likely related to the enzymatic conversion of OTA by the >10-kDa fraction was cloned from the B. subtilis CW14 genome, and over-expressed in Escherichia coli. The recombinant CP degraded 71.3% of OTA at 37 °C for 24 h, and ochratoxin α (OTα) was confirmed as a degradation product. From the <3-kDa fraction, some small peptides (1.7 kDa >Mw >0.7 kDa) were purified and decreased OTA by 45.0% under the same conditions, but no product was detected. These peptides were presumed to be capable of binding OTA due to their affinity with the OTA molecule, and the OTA-peptide complexes escaped from the extraction procedures for OTA quantification. These results indicated there was a probable synergistic effect that was involved in removal of OTA by the strain CW14 culture supernatant, which included enzymatic degradation by a CP and physical adsorption by some small peptides.

Computational Competitive and Negative Design To Derive a Specific cJun Antagonist

Basic leucine zipper (bZIP) proteins reside at the end of cell-signaling cascades and function to modulate transcription of specific gene targets. bZIPs are recognized as important regulators of cellular processes such as cell growth, apoptosis, and cell differentiation. One such validated transcriptional regulator, activator protein-1, is typically comprised of heterodimers of Jun and Fos family members and is key in the progression and development of a number of different diseases. The best described component, cJun, is upregulated in a variety of diseases such as cancer, osteoporosis, and psoriasis. Toward our goal of inhibiting bZIP proteins implicated in disease pathways, we here describe the first use of a novel in silico peptide library screening platform that facilitates the derivation of sequences exhibiting a high affinity for cJun while disfavoring homodimer formation or formation of heterodimers with other closely related Fos sequences. In particular, using Fos as a template, we have computationally screened a peptide library of more than 60 million members and ranked hypothetical on/off target complexes according to predicted stability. This resulted in the identification of a sequence that bound cJun but displayed little homomeric stability or preference for cFos. The computationally selected sequence maintains an interaction stability similar to that of a previous experimentally derived cJun antagonist while providing much improved specificity. Our study provides new insight into the use of tandem in silico screening/ in vitro validation and the ability to create a peptide that is capable of satisfying conflicting design requirements.

Peptide Modified ZnO Nanoparticles as Gas Sensors Array for Volatile Organic Compounds (VOCs)

In this work a peptide based gas sensor array based of ZnO nanoparticles (ZnONPs) has been realized. Four different pentapeptides molecularly modeled for alcohols and esters having cysteine as a common spacer have been immobilized onto ZnONPs. ZnONPs have been morphologically and spectroscopically characterized. Modified nanoparticles have been then deposited onto quartz crystal microbalances (QCMs) and used as gas sensors with nitrogen as carrier gas. Analysis of the pure compounds modeled demonstrated a nice fitting of modeling with real data. The peptide based ZnONPs had very low sensitivity to water, compared to previously studied AuNPs peptide based gas sensors allowing the use of the array on samples with high water content. Real samples of fruit juices have been assayed; stability of the signal, good repeatability, and discrimination ability of the array was achieved.

Synthesis of Molecularly Imprinted Polymer Nanoparticles for α-Casein Detection Using Surface Plasmon Resonance as a Milk Allergen Sensor

Food recalls due to undeclared allergens or contamination are costly to the food manufacturing industry worldwide. As the industry strives for better manufacturing efficiencies over a diverse range of food products, there is a need for the development of new analytical techniques to improve monitoring of the presence of unintended food allergens during the food manufacturing process. In particular, the monitoring of wash samples from cleaning in place systems (CIP), used in the cleaning of food processing equipment, would allow for the effective removal of allergen containing ingredients in between food batches. Casein proteins constitute the biggest group of proteins in milk and hence are the most common milk protein allergen in food ingredients. As such, these proteins could present an ideal analyte for cleaning validation. In this work, molecularly imprinted polymer nanoparticles (nanoMIPs) with high affinity toward bovine α-casein were synthesized using a solid-phase imprinting method. The nanoMIPs were then characterized and incorporated into label free surface plasmon resonance (SPR) based sensor. The nanoMIPs demonstrated good binding affinity and selectivity toward α-casein (K_D ∼ 10 × 10^-9 M). This simple affinity sensor demonstrated the quantitative detection of α-casein achieving a detection limit of 127 ± 97.6 ng mL^-1 (0.127 ppm) which is far superior to existing commercially available ELISA kits. Recoveries from spiked CIP wastewater samples were within the acceptable range (87-120%). The reported sensor could allow food manufacturers to adequately monitor and manage food allergen risk in food processing environments while ensuring that the food produced is safe for the consumer.

Molecular Modeling and Simulation Tools in the Development of Peptide-Based Biosensors for Mycotoxin Detection: Example of Ochratoxin

Mycotoxin contamination of food and feed is now ubiquitous. Exposures to mycotoxin via contact or ingestion can potentially induce adverse health outcomes. Affordable mycotoxin-monitoring systems are highly desired but are limited by (a) the reliance on technically challenging and costly molecular recognition by immuno-capture technologies; and (b) the lack of predictive tools for directing the optimization of alternative molecular recognition modalities. Our group has been exploring the development of ochratoxin detection and monitoring systems using the peptide NFO4 as the molecular recognition receptor in fluorescence, electrochemical and multimodal biosensors. Using ochratoxin as the model mycotoxin, we share our perspective on addressing the technical challenges involved in biosensor fabrication, namely: (a) peptide receptor design; and (b) performance evaluation. Subsequently, the scope and utility of molecular modeling and simulation (MMS) approaches to address the above challenges are described. Informed and enabled by phage display, the subsequent application of MMS approaches can rationally guide subsequent biomolecular engineering of peptide receptors, including bioconjugation and bioimmobilization approaches to be used in the fabrication of peptide biosensors. MMS approaches thus have the potential to reduce biosensor development cost, extend product life cycle, and facilitate multi-analyte detection of mycotoxins, each of which positively contributes to the overall affordability of mycotoxin biosensor monitoring systems.

Bioinspired recognition elements for mycotoxin sensors

Mycotoxins are low molecular weight molecules produced as secondary metabolites by filamentous fungi that can be found as natural contaminants in many foods and feeds. These toxins have been shown to have adverse effects on both human and animal health, and are the cause of significant economic losses worldwide. Sensors for mycotoxin analysis have traditionally applied elements of biological origin for the selective recognition purposes. However, since the 1970s there has been an exponential growth in the use of genetically engineered or synthetic biomimetic recognition elements that allow some of the limitations associated with the use of natural receptors for the analyses of these toxins to be circumvented. This review provides an overview of recent advances in the application of bioinspired recognition elements, including recombinant antibodies, peptides, aptamers, and molecularly imprinted polymers, to the development of sensors for mycotoxins based on different transduction elements. Graphical abstract Novel analytical methods based on bioinspired recognition elements, such as recombinant antibodies, peptides, aptamers, and molecularly imprinted polymers, can improve the detection of mycotoxins and provide better tools than their natural counterparts to ensure food safety.

Evaluation of Ochratoxin Recognition by Peptides Using Explicit Solvent Molecular Dynamics

Biosensing platforms based on peptide recognition provide a cost-effective and stable alternative to antibody-based capture and discrimination of ochratoxin-A (OTA) vs. ochratoxin-B (OTB) in monitoring bioassays. Attempts to engineer peptides with improved recognition efficacy require thorough structural and thermodynamic characterization of the binding-competent conformations. Classical molecular dynamics (MD) approaches alone do not provide a thorough assessment of a peptide's recognition efficacy. In this study, in-solution binding properties of four different peptides, a hexamer (SNLHPK), an octamer (CSIVEDGK), NFO4 (VYMNRKYYKCCK), and a 13-mer (GPAGIDGPAGIRC), which were previously generated for OTA-specific recognition, were evaluated using an advanced MD simulation approach involving accelerated configurational search and predictive modeling. Peptide configurations relevant to ochratoxin binding were initially generated using biased exchange metadynamics and the dynamic properties associated with the in-solution peptide-ochratoxin binding were derived from Markov State Models. Among the various peptides, NFO4 shows superior in-solution OTA sensing and also shows superior selectivity for OTA vs. OTB due to the lower penalty associated with solvating its bound complex. Advanced MD approaches provide structural and energetic insights critical to the hapten-specific recognition to aid the engineering of peptides with better sensing efficacies.

Selective solid phase extraction of JWH synthetic cannabinoids by using computationally designed peptides

The objective of the present work is to demonstrate a rational way to prepare selective sorbents able to extract simultaneously several structural analogs. For this purpose the binding specificity of two hexapeptides computationally designed (VYWLVW and YYIGGF) versus four synthetic cannabinoids Naphthalen-1-yl-(1-pentylindol-3-yl)methanone (JWH 018), naphthalen-1-yl-(1-butylindol-3-yl)methanone (JWH 073), (R)-(1-((1-methylpiperidin-2-yl)methyl)-1H-indol-3-yl)(naphthalen-1-yl)methanone (AM 1220) and (R)-(+)-[2,3-Dihydro-5-methyl-3-(4-morpholinylmethyl)pyrrolo[1,2,3-de]-1,4-benzoxazin-6-yl]-1-napthalenylmethanone (WIN 55) was computationally studied and then experimentally tested by solid-phase extraction (SPE) clean-up and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis. The two peptides were chosen using a semi combinatorial virtual technique by generating 4 cycles of peptide libraries (around 2.3×10⁴ elements). To select the two peptides, the simulated binding scores between synthetic cannabinoids and peptides was used by maximizing the recognition properties of amino acid motif between the two JWH and the other synthetic cannabinoids. In particular, the peptide YYIGGF, having also affinity for AM 120, was selected as control because it was the only one without tryptophan residues within the best peptides obtained from simulation. Experimentally, the two hexapeptides were tested as SPE sorbent using nanomolar solutions of the four drugs. After optimization of best retentions the binding constants were calculated by loading synthetic cannabinoids solutions at different concentrations. The results indicated a strong interaction between hexapeptide VYWLVW and JWH 018 (15.58±2.03×10⁶M^-1), 3-fold and 40-fold larger compared to the analog JWH 073 and both AM 1220 and the WIN 55. Similar trend was observed for the hexapeptide YYIGGF but the binding constants were at least three times lower highlighting the key role of the tryptophan. To demonstrate the hexapeptides specific interaction with only synthetic cannabinoids, a cross-reactivity study was carried out using other drugs (cocaine, morphine, phencyclidine and methamphetamine) in the same SPE condition. Finally the practical utility of these peptide modified sorbent materials was further demonstrated by detecting the synthetic cannabinoids in real samples using hair matrix.

Selective tools for the solid-phase extraction of Ochratoxin A from various complex samples: immunosorbents, oligosorbents, and molecularly imprinted polymers

The evolution of instrumentation in terms of separation and detection has allowed a real improvement of the sensitivity and the analysis time. However, the analysis of ultra-traces of toxins such as ochratoxin A (OTA) from complex samples (foodstuffs, biological fluids…) still requires a step of purification and of preconcentration before chromatographic determination. In this context, extraction sorbents leading to a molecular recognition mechanism appear as powerful tools for the selective extraction of OTA and of its structural analogs in order to obtain more reliable and sensitive quantitative analyses of these compounds in complex media. Indeed, immunosorbents and oligosorbents that are based on the use of immobilized antibodies and of aptamers, respectively, and that are specific to OTA allow its selective clean-up from complex samples with high enrichment factors. Similar molecular recognition mechanisms can also be obtained by developing molecularly imprinted polymers, the synthesis of which leads to the formation of cavities that are specific to OTA, thus mimicking the recognition site of the biomolecules. Therefore, the principle, the advantages, the limits of these different types of extraction tools, and their complementary behaviors will be presented. The introduction of these selective tools in miniaturized devices will also be discussed.

New biorecognition molecules in biosensors for the detection of toxins

Biological and synthetic recognition elements are at the heart of the majority of modern bioreceptor assays. Traditionally, enzymes and antibodies have been integrated in the biosensor designs as a popular choice for the detection of toxin molecules. But since 1970s, alternative biological and synthetic binders have been emerged as a promising alternative to conventional biorecognition elements in detection systems for laboratory and field-based applications. Recent research has witnessed immense interest in the use of recombinant enzymatic methodologies and nanozymes to circumvent the drawbacks associated with natural enzymes. In the area of antibody production, technologies based on the modification of in vivo synthesized materials and in vitro approaches with development of "display "systems have been introduced in the recent years. Subsequently, molecularly-imprinted polymers and Peptide nucleic acid (PNAs) were developed as an attractive receptor with applications in the area of sample preparation and detection systems. In this article, we discuss all alternatives to conventional biomolecules employed in the detection of various toxin molecules We review recent developments in modified enzymes, nanozymes, nanobodies, aptamers, peptides, protein scaffolds and DNazymes. With the advent of nanostructures and new interface materials, these recognition elements will be major players in future biosensor development.

Comparison of Electrochemical Immunosensors and Aptasensors for Detection of Small Organic Molecules in Environment, Food Safety, Clinical and Public Security

We review here the most frequently reported targets among the electrochemical immunosensors and aptasensors: antibiotics, bisphenol A, cocaine, ochratoxin A and estradiol. In each case, the immobilization procedures are described as well as the transduction schemes and the limits of detection. It is shown that limits of detections are generally two to three orders of magnitude lower for immunosensors than for aptasensors, due to the highest affinities of antibodies. No significant progresses have been made to improve these affinities, but transduction schemes were improved instead, which lead to a regular improvement of the limit of detections corresponding to ca. five orders of magnitude over these last 10 years. These progresses depend on the target, however.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands

Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders.

Solid-Phase Extraction of Pesticides by Using Bioinspired Peptide Receptors

A virtual development of hexapeptide receptors bioinspired by the acetylcholinesterase enzyme active site is proposed. A semicombinatorial approach was applied to generate a virtual hexapeptides library with different affinity properties towards organophosphate and carbamate pesticides. The virtual screening process was addressed to obtain peptides able to separate pesticide subclasses in the experimental work. Three hexapeptides, two generated by molecular modeling and one having a scrambled sequence, were used as selective sorbent materials for pesticides in preanalytical solid-phase extraction (SPE) method. Selective adsorption and cross-reactivity were tested directly on a mix of four pesticides (carbaryl, chlorpyrifos-ethyl, malathion, and thiabendazole) having different structures and physico-chemical properties, at a total concentration of 120 ppb (each pesticide at concentration of 30 ppb). The results were compared to traditional sorbent material such as C-18 and strata-X. Data showed that only one of the hexapeptides virtually designed had significant differences in competitive absorption between aliphatic pesticide malathion, fungicide thiabendazole chosen as negative control, and aromatic pesticides. These results partially supported the simulated strategy.