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The cyclic depsipeptide mycotoxins beauvericin and enniatins are capable of reaching the systemic circulation through various routes of exposure and are hence capable of exerting central nervous system (CNS) effects, if they are able to pass the blood-brain barrier (BBB), which was the main objective of this study. Quantification of the mycotoxins was performed using an in-house developed and validated bio-analytical UHPLC-MS/MS method. Prior to the BBB experiments, the metabolic stability of the mycotoxins was evaluated in vitro in mouse serum and brain homogenate. The BBB permeation kinetics of beauvericin and enniatins were studied using an in vivo mice model, applying multiple time regression for studying the blood-to-brain influx. Additionally, capillary depletion was applied to obtain the fraction of the peptides really entering the brain parenchyma and the fraction loosely adhered to the brain capillary wall. Finally, also the brain-to-blood efflux transport kinetics was studied. Metabolic stability data indicated that the investigated mycotoxins were stable during the duration of the in vivo study. The brain influx study showed that beauvericin and enniatins are able to cross the blood-brain barrier in mice: using the Gjedde-Patlak biphasic model, it was shown that all investigated mycotoxins exert a high initial influx rate into the brain (K1 ranging from 11 to 53μL/(g×min)), rapidly reaching a plateau. After penetration, the mycotoxins reached the brain parenchyma (95%) with only a limited amount residing in the capillaries (5%). Negligible efflux (

During fundamental research, it is recommended to evaluate the test compound identity and purity in order to obtain reliable study outcomes. For peptides, quality control (QC) analyses are routinely performed using reversed-phase liquid chromatography coupled to an ultraviolet (UV) detector system. These traditional QC methods, using a C18 column and a linear gradient with formic acid (FA) as acidic modifier in the mobile phase, might not result in optimal chromatographic performance for basic peptides due to their cationic nature and hence may lead to erroneous results. Therefore, the influence of the used chromatographic system on the final QC results of basic peptides was evaluated using five cationic cell-penetrating peptides and five C18-chromatographic systems, differing in the column particle size (high performance liquid chromatography (HPLC) versus ultra-high performance liquid chromatography (UHPLC)), the acidic modifier (FA versus trifluoroacetic acid (TFA)), and the column temperature (30 °C versus 60 °C). Our results indicate that a UHPLC system with the C18 column thermostated at 30 °C and a mobile phase containing TFA, provides the most suitable routine QC analysis method for cationic peptides, outperforming in sensitivity and resolution compared to the other systems. We also demonstrate the use of a single quad mass spectrometry (MS) detector system during QC analysis of (cationic) peptides, allowing identification of the peptide and its impurities, as well as the evaluation of the peak purity.

Quorum sensing peptides are signalling molecules that are produced by mainly gram-positive bacteria. These peptides can exert different effects, ranging from intra- and interspecies bacterial virulence to bacterial–host interactions. To better comprehend these functional differences, we explored their chemical space, bacterial species distribution and receptor-binding properties using multivariate data analyses, with information obtained from the Quorumpeps database. The quorum sensing peptides can be categorized into three main clusters, which, in turn, can be divided into several subclusters: the classification is based on characteristic chemical properties, including peptide size/compactness, hydrophilicity/lipophilicity, cyclization and the presence of (unnatural) S-containing and aromatic amino acids. Most of the bacterial species synthesize peptides located into one cluster. However, some Streptococcus, Stapylococcus, Clostridium, Bacillus and Lactobacillus species produce peptides that are distributed over more than one cluster, with the quorum sensing peptides of Bacillus subtilis even occupying the total peptide space. The AgrC, FsrC and LamC receptors are only activated by cyclic (thio)lacton or lactam quorum sensing peptides, while the lipophilic isoprenyl-modified peptides solely bind the ComP receptor in Bacillus species. © 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 104: 544–551, 2015.

Peptides are an increasingly important group of pharmaceuticals, positioned between classic small organic molecules and larger bio-molecules such as proteins. Currently, the peptide drug market is growing twice as fast as other drug markets, illustrating the increasing clinical as well as economical impact of this medicine group. Most peptides today are manufactured by solid-phase peptide synthesis (SPPS). This review will provide a structured overview of the most commonly observed peptide-related impurities in peptide medicines, encompassing the active pharmaceutical ingredients (API or drug substance) as well as the finished drug products. Not only is control of these peptide-related impurities and degradants critical for the already approved and clinically used peptide-drugs, these impurities also possess the capability of greatly influencing initial functionality studies during early drug discovery phases, possibly resulting in erroneous conclusions. The first group of peptide-related impurities is SPPS-related: deletion and insertion of amino acids are related to inefficient Fmoc-deprotection and excess use of amino acid reagents, respectively. Fmoc-deprotection can cause racemization of amino acid residues and thus diastereomeric impurities. Inefficient deprotection of amino acid side chains results into peptide-protection adducts. Furthermore, unprotected side chains can react with a variety of reagents used in the synthesis. Oxidation of amino acid side chains and dimeric-to-oligomeric impurities were also observed. Unwanted peptide counter ions such as trifluoroacetate, originating from the SPPS itself or from additional purification treatments, may also be present in the final peptide product. Contamination of the desired peptide product by other unrelated peptides was also seen, pointing out the lack of appropriate GMP. The second impurity group results from typical peptide degradation mechanisms such as β-elimination, diketopiperazine, pyroglutamate and succinimide formation. These SPPS- and degradation-related impurity types can also found in the finished peptide drug products, which can additionally contain a third group of related impurities, i.e. the API-excipient degradation products.

Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antitumor, immune-modulating and cell-penetrating compounds. However, due to their specific structure, chromatographic analysis often requires special buffer systems or the use of trifluoroacetic acid, limiting mass spectrometry detection. Therefore, we used a traditional aqueous/acetonitrile based gradient system, containing 0.1% (m/v) formic acid, to separate four pharmaceutically relevant lipopeptides (polymyxin B1, caspofungin, daptomycin and gramicidin A1), which were selected based upon hierarchical cluster analysis (HCA) and principal component analysis (PCA).In total, the performance of four different C18 columns, including one UPLC column, were evaluated using two parallel approaches. First, a Derringer desirability function was used, whereby six single and multiple chromatographic response values were rescaled into one overall D-value per column. Using this approach, the YMC Pack Pro C18 column was ranked as the best column for general MS-compatible lipopeptide separation. Secondly, the kinetic plot approach was used to compare the different columns at different flow rate ranges. As the optimal kinetic column performance is obtained at its maximal pressure, the length elongation factor λ (Pmax/Pexp) was used to transform the obtained experimental data (retention times and peak capacities) and construct kinetic performance limit (KPL) curves, allowing a direct visual and unbiased comparison of the selected columns, whereby the YMC Triart C18 UPLC and ACE C18 columns performed as best. Finally, differences in column performance and the (dis)advantages of both approaches are discussed. Keywords: Lipopeptide, Hierarchical cluster analysis (HCA), Principal component analysis (PCA), LCâMS, Kinetic plot, Derringer desirability function

Cyclic depsipeptides (CDPs) are a family of cyclic peptide-related compounds, of which the ring is mainly composed of amino- and hydroxy acid residues joined by amide and ester bonds (at least one), leading to a wide diversity of fascinating chemical structures. They differ in both their ring structure and their side chains, especially by the nature of the unusual and non-amino acid building blocks. To date, however, there is no overall uniform chemical classification system available for CDPs and naming of the diverse family members is done rather arbitrarily. Therefore, a broad evaluation of different CDP structures is done, i.e., 1348 naturally occurring CDPs were included, and a straightforward chemical classification system using apparent chemical characteristics is proposed in order to organize the currently scattered CDP data. The overall validity of the classification approach is verified and the compounds categorized in the same groups are considered to be structurally related. This evaluation also revealed that traditionally formed CDP subfamilies, like the dolastatins, might be misleading from a chemical point of view given the structural differences in this subfamily. This up-to-date CDP overview enables peptide and natural product scientists to study the wide diversity in CDP structures, their chemical interrelationships and identification of existing and newly found CDPs. Together with the available information on the species producing these CDPs and their reported biological activities, this paper provides a useful tool to gain new insights into this diverse group of peptides.

HEPES is a zwitterionic buffer component used as a raw material in the GMP-manufacturing of advanced therapy medicinal products (ATMPs), hence requiring an adequate assay method with sufficient selectivity toward related impurities. Therefore, a hydrophilic interaction chromatography (HILIC) method was developed. Different factors were investigated towards the retention behavior of HEPES, its analogue EPPS and its starting material isethionate: pH, ion concentration and organic solvent ratio of the mobile phase, as well as column temperature. Moreover, stress testing resulted in the N-oxide degradant, identified by high resolution MS. The final method consisted of an isocratic system with an aqueous (pH 2.0 with H3PO4) acetonitrile (35:65, v/v) mobile phase on a zwitterionic HILIC (Obelisc N) column with a flow rate of 0.5 mL/min and UV detection at 195 nm. The assay method of HEPES was validated, obtaining adequate linearity (R2 = 0.999), precision (RSD of 0.5%) and accuracy (recovery of 100.08%). Finally, the applicability of the validated method was demonstrated by analysis of samples from different suppliers.

The neuromedin peptides are peripherally and centrally produced, but until now, it is generally believed that they only function as locally acting compounds without any quantitative knowledge about their blood-brain barrier (BBB) passage. Here, we characterize the transport kinetics of four neuromedins (NMU, NMN, NMB and NT) across the BBB, as well as their metabolization profile, and evaluate if they can act as endocrine hormones. Using the in vivo mouse model, multiple time regression (MTR), capillary depletion (CD) and brain efflux studies were performed. Data was fitted using linear (NMU, NT and NMB) or biphasic modeling (NMU and NMN). Three of the four investigated peptides, i.e. NMU, NT and NMN, showed a significant influx into the brain with unidirectional influx rate constants of 1.31 and 0.75 μL/(g × min) for NMU and NT respectively and initial influx constants (K1) of 72.14 and 7.55 μL/(g × min) and net influx constants (K) of 1.28 and 1.36 x 10(-16) μL/(g x min) for NMU and NMN respectively. The influx of NMB was negligible. Only NMN and NT showed a significant efflux out of the brain with an efflux constant (kout) of 0.042 min(-1) and -0.053 min(-1) respectively. Our results indicate that locally produced neuromedin peptides and/or fragments can be transported through the whole body, including passing the BBB, and taken up by different organs/tissues, supporting the idea that the neuromedins could have a much bigger role in the regulation of biological processes than currently assumed.

Buserelin is a GnRH agonist peptide drug, comprising a nine amino acid sequence (pGlu-His-Trp-Ser-Tyr-D-Ser(tBu)-Leu-Arg-Pro-NH-Et) and most commonly known for its application in hormone dependent cancer therapy, e.g. prostate cancer. In order to evaluate its hot-melt extrusion (HME) capabilities, buserelin powder in its solid state was exposed to elevated temperatures for prolonged time periods. A stability indicating UPLC-PDA method was used for quantification of buserelin and the formed degradants. Different solid state kinetic models were statistically evaluated of which the Ginstling-Brounshtein model fitted the data best. Extrapolation to and experimental verification of typical HME-related conditions, i.e. 5 min at 100°C and 125°C, showed no significant degradation, thus demonstrating the HME capabilities of buserelin. Mass spectrometric identification of the buserelin-related degradants formed under solid state heat stress was performed. Based upon the identity of these degradants, different degradation hypotheses were raised. First, direct β-elimination of the hydroxyl moiety at the serine residue, followed by fragmentation into an amide (pGlu-His-Trp-NH2) and pyruvoyl (pyruvoyl-Tyr-D-Ser(tBu)-Leu-Arg-Pro-NH-Et) peptide fragments, was postulated. Alternatively, internal esterification due to nucleophilic attack of the unprotected serine residue, followed by β-elimination or hydrolysis would yield pGlu-His-Trp, pGlu-His-Trp-NH2 and the pyruvoyl peptide fragment. Degradant pGlu-His-Trp-Ser-Tyr-NH2 is believed to be formed in a similar way. Secondly, direct backbone hydrolysis would yield pGlu-His-Trp and Tyr-D-Ser(tBu)-Leu-Arg-Pro-NH-Et peptide fragments. Moreover, the presence of Ala-Tyr-D-Ser(tBu)-Leu-Arg-Pro-NH-Et can be explained by hydrolysis of the Trp-Ser peptide bond and conversion of the serine moiety to an alanine moiety. Third and finally, isomerisation of aforementioned peptide fragments and buserelin itself was also observed.

Different fused-core stationary phase chemistries (C18, Amide, Phenyl-hexyl and Peptide ES-C18) were used for the analysis of 21 structurally representative model peptides. In addition, the effects of the mobile phase composition (ACN or MeOH as organic modifier; formic acid or acetic acid, as acidifying component) on the column selectivity, peak shape and overall chromatographic performance were evaluated. The RP-amide column, combined with a formic acidâacetonitrile based gradient system, performed as best. A peptide reversed-phase retention model is proposed, consisting of 5 variables: log SumAA, log Sv, clog P, log nHDon and log nHAcc. Quantitative structure-retention relationship (QSRR) models were constructed for 16 different chromatographic systems. The accuracy of this peptide retention model was demonstrated by the comparison between predicted and experimentally obtained retention times, explaining on average 86% of the variability. Moreover, using an external set of 5 validation peptides, the predictive power of the model was also demonstrated. This peptide retention model includes the novel in-silico calculated amino acid descriptor, AA, which was calculated from log P, 3D-MoRSE, RDF and WHIM descriptors. Keywords: Peptides, Fused-core (core-shell, core-enhanced, poro-shell, HALO®) stationary phases, RP-HPLC peptide retention model, In-silico amino acid descriptor