Peptides trapping cocaine: docking simulation and experimental screening by solid phase extraction followed by liquid chromatography mass spectrometry in plasma samples

Microextraction approaches for bioanalytical applications: An overview

Biological samples are usually complex matrices due to the presence of proteins, salts and a variety of organic compounds with chemical properties similar to those of the target analytes. Therefore, sample preparation is often mandatory in order to isolate the analytes from troublesome matrices before instrumental analysis. Because the number of samples in drug development, doping analysis, forensic science, toxicological analysis, and preclinical and clinical assays is steadily increasing, novel high throughput sample preparation approaches are calling for. The key factors in this development are the miniaturization and the automation of the sample preparation approaches so as to cope with most of the twelve principles of green chemistry. In this review, recent trends in sample preparation and novel strategies will be discussed in detail with particular focus on sorptive and liquid-phase microextraction in bioanalysis. The actual applicability of selective sorbents is also considered. Additionally, the role of 3D printing in microextraction for bioanalytical methods will be pinpointed.

Investigations on the interface of nucleic acid aptamers and binding targets

Nucleic acid aptamers are single-stranded DNA or RNA of 20-100 nucleotides in length that have attracted substantial scientific interest due to their ability to specifically bind to target molecules via the formation of three-dimensional structures. Compared to traditional protein antibodies, aptamers have several advantages, such as their small size, high binding affinity, specificity, flexible structure, being chemical synthesizable and modifiable, good biocompatibility, high stability and low immunogenicity, which all contribute to their widely applications in the biomedical field. To date, much progress has been made in the study and applications of aptamers, however, detailed information on how aptamers bind to their targets is still scarce. Over the past few decades, many methods have been introduced to investigate the aptamer-target binding process, such as measuring the main kinetic or thermodynamic parameters, detecting the structural changes of the binding complexes, etc. Apart from traditional physicochemical methods, various types of molecular docking programs have been applied to simulate the aptamer-target interactions, while these simulations also have limitations. To facilitate the further research on the interactions, herein, we provide a brief review to illustrate the recent advances in the study of aptamer-target interactions. We summarize the binding targets of aptamers, such as small molecules, macromolecules, and even cells. Their binding constants (KD) are also summarized. Methods to probe the aptamer-target binding process, such as surface plasmon resonance (SPR), circular dichroism spectroscopy (CD), isothermal titration calorimetry (ITC), footprinting assay, truncation and mutation assay, nuclear magnetic resonance spectroscopy (NMR), X-ray crystallography and molecular docking simulation are indicated. The binding forces mediating the aptamer-target interactions, such as hydrogen bonding, electrostatic interaction, the hydrophobic effect, π-π stacking and van der Waals forces are summarized. The challenges and future perspectives are also discussed.

Hairpin DNA-AuNPs as molecular binding elements for the detection of volatile organic compounds

Hairpin DNA (hpDNA) loops were used for the first time as molecular binding elements in gas analysis. The hpDNA loops sequences of unpaired bases were studied in-silico to evaluate the binding versus four chemical classes (alcohols, aldehydes, esters and ketones) of volatile organic compounds (VOCs). The virtual binding score trend was correlated to the oligonucleotide size and increased of about 25% from tetramer to hexamer. Two tetramer and pentamer and three hexamer loops were selected to test the recognition ability of the DNA motif. The selection was carried out trying to maximize differences among chemical classes in order to evaluate the ability of the sensors to work as an array. All oligonucleotides showed similar trends with best binding scores for alcohols followed by esters, aldehydes and ketones. The seven ssDNA loops (CCAG, TTCT, CCCGA, TAAGT, ATAATC, CATGTC and CTGCAA) were then extended with the same double helix stem of four base pair DNA (GAAG to 5' end and CTTC to 3' end) and covalently bound to gold nanoparticles (AuNPs) using a thiol spacer attached to 5' end of the hpDNA. HpDNA-AuNPs were deposited onto 20 MHz quartz crystal microbalances (QCMs) to form the gas piezoelectric sensors. An estimation of relative binding affinities was obtained using different amounts of eight VOCs (ethanol, 3-methylbutan-1-ol, 1-pentanol, octanal, nonanal, ethyl acetate, ethyl octanoate, and butane-2,3-dione) representative of the four chemical classes. In agreement with the predicted simulation, hexamer DNA loops improved by two orders of magnitude the binding affinity highlighting the key role of the hpDNA loop size. Using the sensors as an array a clear discrimination of VOCs on the basis of molecular weight and functional groups was achieved, analyzing the experimental with principal components analysis (PCA) demonstrating that HpDNA is a promising molecular binding element for analysis of VOCs.

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.

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.

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.

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.

Porous membrane ultrafiltration-A novel method for enrichment of the active compounds from micro-plasma samples

To enrich the active compounds from plasma samples, a novel and simple method has been developed using a porous membrane envelope based on the ultrafiltration technique combining with high-performance liquid chromatography. The ultrafiltration device is a sealed porous membrane envelope prepared with a polypropylene sheet to effectively separate the active small molecules and large biomolecules, and a sample carrier is held inside the envelope to load plasma samples. The enrichment of hyperoside and isoquercitrin from rat plasma was used as an example. Significant factors of this method, such as membrane types, the desorption solvent, and the desorption time were optimized for the ultrafiltration method. Under the optimal conditions, correlation coefficients of 0.999 and 0.998 were obtained for hyperoside and isoquercitrin, respectively, with a linear range between 0.5 and 100μg/mL. The absolute extraction recoveries from 83.2% to 86.8% were achieved. The detection limits of the method for hyperoside and isoquercitrin were 0.22 and 0.20μg/mL, respectively. Compared with protein precipitation, solid-phase extraction and commercial ultrafiltration membrane methods, our proposed method demonstrates lower detection limits and lower cost for extraction. Also, it consumes less plasma samples and is found to be applicable to biological samples.

Selection of peptide ligands for piezoelectric peptide based gas sensors arrays using a virtual screening approach

Virtual and experimental affinity binding properties of 5 different peptides (cysteinylglycine, glutathione, Cys-Ile-His-Asn-Pro, Cys-Ile-Gln-Pro-Val, Cys-Arg-Gln-Val-Phe) vs. 14 volatile compounds belonging to relevant chemical classes were evaluated. The peptides were selected in order to have a large variability in physicochemical characteristics (including length). In virtual screening a rapid and cost-effective computational methodology for predicting binding scores of small peptide receptors vs. volatile compounds is proposed. Flexibility was considered for both ligands and peptides and each peptide conformer was treated as a possible receptor, generating a dedicated box and then running a docking process vs. all possible conformers of the 14 volatile compounds. The 5 peptides were covalently bound to gold nanoparticles and deposited onto 20 MHz quartz crystal microbalances to realize gas sensors. Gas sensing confirmed that each of the peptide conferred to the gold nanoparticles a particular selectivity pattern able to discriminate the 14 volatile compounds. The largest response was obtained for the pentapeptides Cys-Ile-His-Asn-Pro and Cys-Ile-Gln-Pro-Val while low response was achieved for the dipeptide. The comparative study, carried using a two-tailed T test, demonstrated that virtual screening was able to predict reliably the sensing ability of the pentapeptides. The dipeptide receptor exhibited 29% of virtual-experimental matching vs. 71% of glutathione and up to 93% for the pentapeptides. This virtual screening approach was proved to be a promising tool in predicting the behaviour of sensors array for gas detection.

Peptides Trapping Dioxins: A Docking-Based Inverse Screening Approach

A rapid and cost-effective computational methodology for designing and rationalizing the selection of small peptides as receptors for dioxin-like compounds was proposed. The backbone of the dioxin Ah receptor binding site was used to design a series of penta- and hexapeptide libraries, with 1400 elements in total. Peptide flexibility was considered and 10 conformers were found to be a good option to represent peptide conformational space with fair speed-accuracy ratio. Each peptide conformer was treated as a possible receptor, generating a dedicated box and then running a docking process using as ligands a family of 76 dibenzo-p-dioxins and 113 dibenzofurans mono- and polychlorinated. Significant predictions were confirmed by comparing primary structure of top and bottom ranked peptides binding dioxins confirming that scrambled positions of the same amino acids gave completely different predicted binding. The hexapeptide EWFQPW, with the best binding score, was chosen as selective sorbent material in solid-phase extraction. The retention performances were tested using the 2,3,7,8-tetrachlorodibenzo-p-dioxin and two polychlorinated biphenyls in order to verify the hexapeptide specificity. The solid-phase extraction experimental procedure was optimized, and analytical parameters of hexapeptide sorbent material were compared with the resin without hexapeptide and a commercial reversed phase cartridge.