On the hydrophobicity of peptides: Comparing empirical predictions of peptide log P values

A New Amino Acid for Improving Permeability and Solubility in Macrocyclic Peptides through Side Chain-to-Backbone Hydrogen Bonding

Despite the notoriously poor membrane permeability of peptides, many cyclic peptide natural products show high passive membrane permeability and potently inhibit a variety of "undruggable" intracellular targets. A major impediment to the design of cyclic peptides with good permeability is the high desolvation energy associated with the peptide backbone amide NH groups. While several strategies have been proposed to mitigate this deleterious effect, only few studies have used polar side chains to sequester backbone NH groups. We investigated the ability of N,N-pyrrolidinylglutamine (Pye), whose side chain contains a powerful hydrogen-bond-accepting C═O amide group but no hydrogen-bond donors, to sequester exposed backbone NH groups in a series of cyclic hexapeptide diastereomers. Analyses revealed that specific Leu-to-Pye substitutions conferred dramatic improvements in aqueous solubility and permeability in a scaffold- and position-dependent manner. Therefore, this approach offers a complementary tool for improving membrane permeability and solubility in cyclic peptides.

In Silico Screening for Pesticide Candidates against the Desert Locust Schistocerca gregaria

Adipokinetic hormone (AKH) is one of the most important metabolic neuropeptides in insects, with actions similar to glucagon in vertebrates. AKH regulates carbohydrate and fat metabolism by mobilizing trehalose and diacylglycerol into circulation from glycogen and triacylglycerol stores, respectively, in the fat body. The short peptide (8 to 10 amino acids long) exerts its function by binding to a rhodopsin-like G protein-coupled receptor located in the cell membrane of the fat body. The AKH receptor (AKHR) is, thus, a potential target for the development of novel specific (peptide) mimetics to control pest insects, such as locusts, which are feared for their prolific breeding, swarm-forming behavior and voracious appetite. Previously, we proposed a model of the interaction between the three endogenous AKHs of the desert locust, Schistocerca gregaria, and the cognate AKHR (Jackson et al., Peer J. 7, e7514, 2019). In the current study we have performed in silico screening of two databases (NCI Open 2012 library and Zinc20) to identify compounds which may fit the endogenous Schgr-AKH-II binding site on the AKHR of S. gregaria. In all, 354 compounds were found to fit the binding site with glide scores < −8. Using the glide scores and binding energies, 7 docked compounds were selected for molecular dynamic simulation in a phosphatidylcholine membrane. Of these 7 compounds, 4 had binding energies which would allow them to compete with Schgr-AKH-II for the receptor binding site and so are proposed as agonistic ligand candidates. One of the ligands, ZINC000257251537, was tested in a homospecific in vivo biological assay and found to have significant antagonistic activity.

Bioconjugation of Active Ingredients to Plant Viral Nanoparticles Is Enhanced by Preincubation with a Pluronic F127 Polymer Scaffold

Proteinaceous nanoparticles can be used to deliver large payloads of active ingredients, which is advantageous in medicine and agriculture. However, the conjugation of hydrophobic ligands to hydrophilic nanocarriers such as plant viral nanoparticles (plant VNPs) can result in aggregation by reducing overall solubility. Given the benefits of hydrophilic nanocarrier platforms for targeted delivery and multivalent ligand display, coupled with the versatility of hydrophobic drugs, contrast agents, and peptides, this is an issue that must be addressed to realize their full potential. Here, we report two preincubation strategies that use a Pluronic F127 polymer scaffold to prevent the aggregation of conjugated plant VNPs: a plant VNP-polymer precoat (COAT) and an active ingredient formulation combined with a plant VNP-polymer precoat (FORMCOAT). The broad applications of these modified conjugation strategies were highlighted by testing their compatibility with three types of bioconjugation chemistry: N-hydroxysuccinimide ester-amine coupling, maleimide-thiol coupling, and copper(I)-catalyzed azide-alkyne cycloaddition (click chemistry). The COAT and FORMCOAT strategies promoted efficient bioconjugation and prevented the aggregation that accompanies conventional bioconjugation methods, thus improving the stability, homogeneity, and translational potential of plant VNP conjugates in medicine and agriculture.

Surface Activity of Alkoxy Ethoxyethyl β-d-Glucopyranosides

Dioxyethene fragment (-(OCH₂CH₂)₂-) was introduced into traditional alkyl β-d-glucopyranosides to ameliorate the water solubility, and eight nonionic surfactants, that is, alkoxy ethoxyethyl β-d-glucopyranosides with alkyl chain lengths (n = 6-16), were synthesized and characterized. Their hydrophilic and lipophilic balance number, water solubility, critical micelle concentration (cmc), γ_cmc, Γ_max, and hygroscopic rate decreased with an increase in the alkyl chain length. Hexadecoxy ethoxyethyl β-d-glucopyranoside had no water solubility at 25 °C. Decoxy ethoxyethyl β-d-glucopyranoside had the best emulsifying property in the toluene/water and n-octane/water systems and the strongest foaming property, whereas dodecoxy ethoxyethyl β-d-glucopyranoside had the best emulsifying property in the rapeseed oil/water system. Such β-d-glucopyranosides (n = 6-12) exhibited excellent surface activity. In addition, for the binary mixture of alkoxy ethoxyethyl β-d-glucopyranosides (n = 8, 10, 12) and sodium dodecyl sulfate or cetyl trimethyl ammonium chloride, their cmc values were lower than the pure β-d-glucopyranosides, indicating that they had synergistic interactions. The fan focal conic textures of alkoxy ethoxyethyl β-d-glucopyranosides (n = 7-16) were observed during the cooling process under a polarizing optical microscope. Alkoxy ethoxyethyl β-d-glucopyranosides (n = 14, 16) had the related melting points and the clear points with differential scanning calorimetry. With β-d-glucopyranosides (n = 6-16) and n-butanol as the surfactant and cosurfactant, respectively, and with cyclohexane as the oil phase, the related microemulsion areas in their pseudoternary phase diagram system were investigated with the visual observation at 25 °C. Along with the slashing requirements of petroleum consumption, environmental protection, and green and sustainable development, nonionic sugar-based alkoxy ethoxyethyl β-d-glucopyranosides should be expected to have their potential practical application because of their strengthened hydrophilicity, improved water solubility, and enhanced surface activity.

Accurate and Efficient Determination of Unknown Metabolites in Metabolomics by NMR-Based Molecular Motif Identification

Knowledge of the chemical identity of metabolite molecules is critical for the understanding of the complex biological systems to which they belong. Since metabolite identities and their concentrations are often directly linked to the phenotype, such information can be used to map biochemical pathways and understand their role in health and disease. A very large number of metabolites however are still unknown; i.e., their spectroscopic signatures do not match those in existing databases, suggesting unknown molecule identification is both imperative and challenging. Although metabolites are structurally highly diverse, the majority shares a rather limited number of structural motifs, which are defined by sets of ¹H and ¹³C chemical shifts of the same spin system. This allows one to characterize unknown metabolites by a divide-and-conquer strategy that identifies their structural motifs first. Here, we present the structural motif-based approach "SUMMIT Motif" for the de novo identification of unknown molecular structures in complex mixtures, without the need for extensive purification, using NMR in tandem with two newly curated NMR molecular structural motif metabolomics databases (MSMMDBs). For the identification of structural motif(s), first, the ¹H and ¹³C chemical shifts of all the individual spin systems are extracted from 2D and 3D NMR spectra of the complex mixture. Next, the molecular structural motifs are identified by querying these chemical shifts against the new MSMMDBs. One database, COLMAR MSMMDB, was derived from experimental NMR chemical shifts of known metabolites taken from the COLMAR metabolomics database, while the other MSMMDB, pNMR MSMMDB, is based on predicted chemical shifts of metabolites of several existing large metabolomics databases. For molecules consisting of multiple spin systems, spin systems are connected via long-range scalar J-couplings. When this motif-based identification method was applied to the hydrophilic extract of mouse bile fluid, two unknown metabolites could be successfully identified. This approach is both accurate and efficient for the identification of unknown metabolites and hence enables the discovery of new biochemical processes and potential biomarkers.

Hitting Undruggable Targets: Viewing Stabilized Peptide Development through the Lens of Quantitative Systems Pharmacology

Stabilized peptide therapeutics have the potential to hit currently undruggable targets, dramatically expanding the druggable genome. However, major obstacles to their development include poor intracellular delivery, rapid degradation, low target affinity, and membrane toxicity. With the emergence of multiple stabilization techniques and screening technologies, the high efficacy of various bioactive peptides has been demonstrated in vitro, albeit with limited success in vivo. We discuss here the chemical and pharmacokinetic barriers to achieving in vivo efficacy, analyze the characteristics of FDA-approved peptide drugs, and propose a developmental tool that considers the molecular properties of stabilized peptides in a comprehensive and quantitative manner to achieve the necessary rates for in vivo delivery to the target, efficacy, and ultimately clinical translation.

Consensus QSAR modeling of toxicity of pharmaceuticals to different aquatic organisms: Ranking and prioritization of the DrugBank database compounds

In the present work, quantitative structure-activity relationship (QSAR) models have been developed for ecotoxicity of pharmaceuticals on four different aquatic species namely Pseudokirchneriella subcapitata, Daphnia magna, Oncorhynchus mykiss and Pimephales promelas using genetic algorithm (GA) for feature selection followed by Partial Least Squares regression technique according to the Organization for Economic Co-operation and Development (OECD) guidelines. Double cross-validation methodology was employed for selecting suitable models. Only 2D descriptors were used for capturing chemical information and model building, whereas validation of the models was performed by considering various stringent internal and external validation metrics. Interestingly, models could be developed even without using any LogP terms in contrary to the usual dependence of toxicity on lipophilicity. However, the current manuscript proposes highly robust and more predictive models employing computed logP descriptors. The applicability domain study was performed in order to set a predefined chemical zone of applicability for the obtained QSAR models, and the test compounds falling outside the domain were not taken for further analysis while making a prioritized list. An additional comparison was made with ECOSAR, an online expert system for toxicity prediction of organic pollutants, in order to prove predictability of the obtained models. The obtained robust consensus models were utilized to predict the toxicity of a large dataset of approximately 9300 drug-like molecules in order to prioritize the existing drug-like substances in accordance to their acute predicted aquatic toxicities following a scaling technique. Finally, prioritized lists of 500 most toxic chemicals obtained by respective consensus models and those predicted from ECOSAR tool have been reported.

Development and Characterization of an 18F-labeled Ghrelin Peptidomimetic for Imaging the Cardiac Growth Hormone Secretagogue Receptor

One-third of patients with heart disease develop heart failure, which is diagnosed through imaging and detection of circulating biomarkers. Imaging strategies reveal morphologic and functional changes but fall short of detecting molecular abnormalities that can lead to heart failure, and circulating biomarkers are not cardiac specific. Thus, there is critical need for biomarkers that are endogenous to myocardial tissues. The cardiac growth hormone secretagogue receptor 1a (GHSR1a), which binds the hormone ghrelin, is a potential biomarker for heart failure. We have synthesized and characterized a novel ghrelin peptidomimetic tracer, an ¹⁸F-labeled analogue of G-7039, for positron emission tomography (PET) imaging of cardiac GHSR1a. In vitro analysis showed enhanced serum stability compared to natural ghrelin and significantly increased cellular uptake in GHSR1a-expressing OVCAR cells. Biodistribution studies in mice showed that tissue uptake of the tracer was independent of circulating ghrelin levels, and there was negligible cardiac uptake and high uptake in the liver, intestines, and kidneys. Specificity of tracer uptake was assessed using ghsr ^−/− mice; both static and dynamic PET imaging revealed no difference in cardiac uptake, and there was no significant correlation between cardiac standardized uptake values and GHSR1a expression. Our study lays the groundwork for further refinement of peptidomimetic PET tracers targeting cardiac GHSR1a.

Hydrophobicity--shake flasks, protein folding and drug discovery

Hydrophobic interactions are some of the most important interactions in nature. They are the primary driving force in a number of phenomena. This is mostly an entropic effect and can account for a number of biophysical events such as protein-protein or protein-ligand binding that are of immense importance in drug design. The earliest studies on this phenomenon can be dated back to the end of the 19(th) century when Meyer and Overton independently correlated the hydrophobic nature of gases to their anesthetic potency. Since then, significant progress has been made in this realm of science. This review briefly traces the history of hydrophobicity research along with the theoretical estimation of partition coefficients. Finally, the application of hydrophobicity estimation methods in the field of drug design and protein folding is discussed.

A covalent peptide inhibitor of RGS4 identified in a focused one-bead, one compound library screen

Background

Regulators of G protein signaling (RGSs) accelerate GTP hydrolysis by Gα subunits and profoundly inhibit signaling by G protein-coupled receptors (GPCRs). The distinct expression patterns and pathophysiologic regulation of RGS proteins suggest that inhibitors may have therapeutic potential. We recently described a focused one-bead, one-compound (OBOC) library screen to identify peptide inhibitors of RGS4. Here we extend our observations to include another peptide with a different mechanism of action.

Results

Peptide 5nd (Tyr-Trp-c [Cys-Lys-Gly-Leu-Cys]-Lys-NH₂, S-S) blocks the RGS4-Gα_o interaction with an IC₅₀ of 28 μM. It forms a covalent, dithiothreitol (DTT) sensitive adduct with a mass consistent with the incorporation of one peptide per RGS. Peptide 5nd activity is abolished by either changing its disulfide bridge to a methylene dithioether bridge, which cannot form disulfide bridges to the RGS, or by removing all cysteines from the RGS protein. However, no single cysteine in RGS4 is completely necessary or sufficient for 5nd activity.

Conclusion

Though it has some RGS selectivity, 5nd appears to be a partially random cysteine modifier. These data suggest that it inhibits RGS4 by forming disulfide bridges with the protein.

Empirical prediction of peptide octanol-water partition coefficients

Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient P (commonly expressed in logarithm form: logP), is useful for screening out unsuitable molecules and also for the development of predictive Quantitative Structure-Activity Relationships (QSARs). In this paper we develop a new approach to the prediction of LogP values for peptides based on an empirical relationship between global molecular properties and measured physical properties. Our method was successful in terms of peptide prediction (total r(2) = 0.641). The final model consisted of 5 physicochemical descriptors (molecular weight, number of single bonds, 2D-VDW volume, 2D-VSA hydrophobic and 2D-VSA polar). The approach is peptide specific and its predictive accuracy was high. Overall, 67% of the peptides were able to be predicted within +/-0.5 log units from the experimental values. Our method thus represents a novel prediction method with proven predictive ability.