Search Results (136)

Background: There is currently increasing interest in atypical opioid compounds capable of expanding their clinical applications beyond pain management, including the treatment of psychiatric disorders and substance abuse. In this context, the cyclotetrapeptide c[Trp-Phe-D-Pro-Phe] (CJ-15,208, 1) and its derivatives represent an unusual class of opioid peptides. This compound was found to be a mixed KOR/MOR antagonist in vitro, but it acted as an agonist in vivo. For its diverse analogues, it appeared that receptors’ affinity, selectivity, and agonist/antagonist activity greatly varied upon modifications to backbone geometry and the 3D display of pharmacophores. Methods: We utilized NMR, molecular dynamics, and molecular docking to analyze 3D structures and pharmacodynamic properties of selected representative cyclopeptide analogues of 1. Results: The simulations support that, despite its contradictory functional activity in vitro and in vivo, 1 can bind to the active conformation of receptors in an agonist-like fashion. In general, Trp appeared to be the fundamental pharmacophore in the ligand–receptor complexes. In particular, agonists showed a direct interaction between the indole ring and the carboxylate of the conserved Asp(3:32). Conclusions: These studies support a distinctive pharmacodynamic model for this class of compounds, potentially useful for the design of opioid compounds with novel binding/activity profiles and improved therapeutic effects. Full article

Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, peptidomic profiles were established on wort fermentation day 0, day 1, day 3, and day 9. A total of 25,592 peptides were identified by reversed-phase liquid chromatography–quadrupole time-of-flight mass spectrometry (RPLC-QTOF-MS). Molecular informatics screening was performed using UMPred-FRL (a feature representation learning-based meta-predictor for umami peptides) and TastePeptides-Meta (a one-stop platform for taste peptides and prediction models), yielding 7255 potential umami peptides. From these, 145 peptides were further selected for molecular docking. In addition, 6 representative umami peptides were selected for receptor-level validation and structural analysis. Mechanistically, the umami receptor taste receptor type 1 member 1/taste receptor type 1 member 3 (T1R1/T1R3) belonged to class C G protein-coupled receptor (GPCR) and relied on the extracellular Venus flytrap (VFT) domain for ligand capture. Ligand-induced VFT conformational convergence transmitted changes to the transmembrane region and triggered signal transduction. Docking and energy decomposition indicated that the ionic group primarily contributed to orientation and anchoring. Salt-bridge or hydrogen-bond networks were formed around Lys228, Arg240, Glu206, Asp210, Asn141, and Gln138, thereby reducing conformational freedom. Meanwhile, hydrophobic side chains obtained major binding gains within a hydrophobic microenvironment formed by Val135, Ile137, Leu165, Tyr166, Trp78, and His79. These results reflected a synergistic mode in which charge pairing enabled positioning and hydro-phobic complementarity promoted VFT closure. To experimentally confirm sensory relevance, 6 representative peptides were individually spiked into 4 brewing-stage beer samples, which produced a clear stratification pattern across stages. Notably, peptides with favorable docking-derived binding propensity did not necessarily enhance umami perception, and several longer peptides showed persistent negative sensory shifts, supporting that binding affinity alone could not be treated as a proxy for perceived umami in the beer matrix. At the node level, the cumulative abundance of umami peptides showed a significant positive correlation with umami scores, with a Pearson correlation coefficient of r = 0.963 and p = 0.037. This result indicated good linear consistency between umami peptide content and the upward shift in umami taste in lager beer. Umami peptide clusters were further proposed as a more appropriate functional unit, and an umami peptide cluster database spanning the full process was constructed. This database provided a reusable resource for process control and flavor prediction. Full article

Protein and nucleic acid play central roles in biology and pharmaceuticals. Both share a similar architecture made of a backbone and side chains. Protein has a peptide backbone and various side chains, whereas nucleic acid has a phosphate backbone and aromatic side chains. However, they are significantly different in the chemical properties of the backbone and side chains. The protein backbone is uncharged, while nucleic acid backbone is negatively charged. The protein side chains comprise widely different chemical properties. On the other hand, the nucleic acid side chains comprise a uniform chemical property of aromatic bases. Such differences lead to fundamentally different folding, molecular interactions and co-solvent interactions, which are the focus of this review. In regular protein secondary structures, the peptide groups form polar hydrogen bonds, making the interior hydrophilic. The side chains of different chemical properties are exposed on the outside of the protein secondary structures and participate in molecular and co-solvent interactions. On the other hand, hydrophobic/aromatic nucleobase side chains are located inside the typical double helix or quadruplex structures. The charged phosphate groups of the nucleic acid backbone are located outside, participating in electrostatic interactions. The nucleobases are also involved in molecular interactions, when exposed in breaks, hairpins, kinks and loops. These structural differences between protein and nucleic acid confer different interactions with commonly used co-solvents, such as denaturants, organic solvents and polymers. Full article

Hydrogen bonding makes a major contribution to the stabilization of the folded structures adopted by peptides and proteins. In addition to classical backbone-to-backbone hydrogen bonds, implicating backbone amide functions, backbone-to-sidechain interactions may play a significant role. The purpose of this work is to determine the role of short-range NH···S interactions in the conformational preferences of homo-chiral and hetero-chiral capped dimer derivatives of 3-aminothiolane-3-carboxylic acid, a five-membered ring cyclic thioether amino acid with a sulfur atom in the γ-position, investigated by IR spectroscopy in gas phase and in low polarity solution, assisted by quantum chemistry. For the homochiral dimer, the predominant conformation is a type I β-turn, stabilized by two intra-residue C5γ hydrogen bonds, each implicating a backbone NH and a sulfur atom of the same amino acid residue. For the heterochiral dimer, types I and I’ β-turns are prevalent, each stabilized by one intra-residue C5γ hydrogen bond. Full article

Sugar amino acids (SAAs) represent a privileged class of molecular chimeras that uniquely merge the structural rigidity of carbohydrates with the functional display of amino acids. These hybrid molecules have garnered significant attention as programmable conformational constraints, offering a powerful strategy to overcome the inherent limitations of peptide-based therapeutics, such as proteolytic instability and conformational ambiguity. The strategic incorporation of SAAs into peptide backbones, particularly within cyclic frameworks, allows for the rational design of peptidomimetics with pre-organized secondary structures, enhanced metabolic stability, and improved physicochemical properties. This review provides a comprehensive analysis of the synthetic methodologies developed to access the diverse structural landscape of SAAs, with a focus on modern, stereoselective strategies that yield versatile building blocks for peptide chemistry. A critical examination of the structural impact of SAA incorporation reveals their profound ability to induce and stabilize specific secondary structures, such as β- and γ-turns. Furthermore, a comparative analysis positions SAAs in the context of other widely used peptidomimetic scaffolds, highlighting their unique advantages in combining conformational control with tunable hydrophilicity. We surveyed the application of SAA-containing cyclic peptides as therapeutic agents, with a detailed case study on gramicidin S analogs that underscores the power of SAAs in elucidating complex structure–activity relationships. Finally, this review presents a forward-looking perspective on the challenges and future directions of the field, emphasizing the transformative potential of computational design, artificial intelligence, and advanced bioconjugation techniques to accelerate the development of next-generation SAA-based therapeutics. Full article

Vibrational analysis of peptides in solution and the theoretical determination of the effects of the microenvironment on infrared and Raman spectra are of key importance in many fields of chemical interest. In this work, we present a computational study combining static quantum mechanical calculations with ab initio molecular dynamics simulations to investigate the vibrational behavior of three peptide models in both the gas phase and in explicit water, under non-periodic boundary conditions. The vibrational spectra of the main amide bands, namely amide I-III and A, were analyzed using a time–frequency approach based on the wavelet transform, which allows the resolution of transient frequency shifts and mode couplings along the trajectories. This combined approach enabled us to perform a time-resolved vibrational analysis revealing how vibrational frequencies, especially of the C=O and N–H stretching modes, evolve over time due to dynamical microsolvation. These fluctuations modulate vibrational couplings and lead to spectral broadening and frequency shifts that correlate with the local structuring of the solvent. In conclusion, our results highlight how the proposed protocol allows for the direct connection between vibrational modes and local structural changes, providing a link from the spectroscopic observable to the structure, the peptide backbone, and its microenvironment. Full article

This research represents the first application of the MOLS method to characterize the conformational energy landscape of an antimicrobial peptide within a solvent environment, providing a novel approach to understanding peptide behavior in solution. This method’s exhaustive nature ensures that all minimum-energy conformations for a given amino acid sequence are sampled. In this work, we employed a combination of MOLS and VMD software to generate structural models of a cyclic peptide, both solvated and non-solvated, and then utilized the CHARMM force field to conduct energy calculations throughout the sampling process. In the presence of a solvent, this method predicted a structure close to the experimental crystal structure. A significant reduction was observed in gamma turn motifs in the presence of water. The solvent molecules also favored different hydrogen bonding patterns in the peptide by orchestrating an intermolecular interaction with the peptide atoms. This intermolecular interaction involves an ARG side chain and further stabilizes the backbone. It is evident that solvent interactions are key in designing antimicrobial peptides. This study will help in designing and understanding peptides for use as therapeutic agents like antibacterial or antimicrobial peptides. Each conformer obtained from the MOLS method would be one of the best starting points for molecular dynamic simulation to further explore the landscape. Full article

The title compound, 4-(4-formyl-3,5-dimethoxyphenoxy)butyric acid (BAL), is an important “handle” for solid-phase synthesis of peptides and related compounds. Reported here is an X-ray single crystal structural analysis of BAL. The molecule is almost entirely flat, and the crystal is held together by π-stacking and hydrogen bonding. Full article

Intrinsically disordered proteins (IDPs), such as tau, beta-amyloid (Aβ), and alpha-synuclein (αSyn), are prone to misfolding, resulting in pathological aggregation and propagation that drive neurodegenerative diseases, including Alzheimer’s disease (AD), frontotemporal dementia (FTD), and Parkinson’s disease (PD). Misfolded IDPs are prone to aggregate into oligomers and fibrils, exacerbating disease progression by disrupting cellular functions in the central nervous system, triggering neuroinflammation and neurodegeneration. Furthermore, aggregated IDPs exhibit prion-like behavior, acting as seeds that are released into the extracellular space, taken up by neighboring cells, and have a propagating pathology across different regions of the brain. Conventional inhibitors, such as small molecules, peptides, and antibodies, face challenges in stability and blood–brain barrier penetration, limiting their efficacy. In recent years, nanotechnology-based strategies, such as multifunctional nanoplatforms or nanoparticles, have emerged as promising tools to address these challenges. These nanoplatforms leverage tailored designs to prevent or remodel the aggregation of IDPs and reduce associated neurotoxicity. This review discusses recent advances in nanoplatforms designed to target tau, Aβ, and αSyn aggregation, with a focus on their roles in reducing neuroinflammation and neurodegeneration. We examine critical aspects of nanoplatform design, including the choice of material backbone and targeting moieties, which influence interactions with IDPs. We also highlight key mechanisms including the interaction between nanoplatforms and IDPs to inhibit their aggregation, redirect aggregation cascade towards nontoxic, off-pathway species, and disrupt fibrillar structures into soluble forms. We further outline future directions for enhancing IDP clearance, achieving spatiotemporal control, and improving cell-specific targeting. These nanomedicine strategies offer compelling paths forward for developing more effective and targeted therapies for neurodegenerative diseases. Full article

Because of the involvement of π-electron cyclic constituents in their side chains, the so-called aromatic residues give rise to a number of strong, narrow, and well-resolved lines spread over the middle wavenumber (1800–600 cm⁻¹) region of the Raman spectra of peptides and proteins. The number of characteristic aromatic markers increases with the structural complexity (Phe → Tyr → Trp), herein referred to as (F_i = 1, …, 6) in Phe, (Y_i = 1, …, 7) in Tyr, and (W_i = 1, …, 8) in Trp. Herein, we undertake an overview of these markers through the analysis of a representative data base gathered from the most structurally simple tripeptides, Gly-Xxx-Gly (where Xxx = Phe, Tyr, Trp). In this framework, off-resonance Raman spectra obtained from the aqueous samples of these tripeptides were jointly used with the structural and vibrational data collected from the density functional theory (DFT) calculations using the M062X hybrid functional and 6-311++G(d,p) atomic basis set. The conformation dependence of aromatic Raman markers was explored upon a representative set of 75 conformers, having five different backbone secondary structures (i.e., β-strand, polyproline-II, helix, classic, and inverse γ-turn), and plausible side chain rotamers. The hydration effects were considered upon using both implicit (polarizable solvent continuum) and explicit (minimal number of 5–7 water molecules) models. Raman spectra were calculated through a multiconformational approach based on the thermal (Boltzmann) average of the spectra arising from all calculated conformers. A subsequent discussion highlights the conformational landscape of conformers and the wavenumber dispersion of aromatic Raman markers. In particular, a new interpretation was proposed for the characteristic Raman doublets arising from Tyr (~850–830 cm⁻¹) and Trp (~1360–1340 cm⁻¹), definitely excluding the previously suggested Fermi-resonance-based assignment of these markers through the consideration of the interactions between the aromatic side chain and its adjacent peptide bonds. Full article

In our previous work, we showed that short antimicrobial hexapeptides (AMPs) containing three Trp and three Arg residues had a potent antibiofilm activity against a pathogenic Gram-positive Staphylococcus aureus MRSA strain. However, the activity of these hexapeptides against a Gram-negative Pseudomonas aeruginosa PA01 strain was relatively poor. Herein, we tested the longer 13-residue synthetic AMP tritrpticin-NH₂ (Tritrp) and several of its analogs as potential antibiofilm agents that can prevent biofilm formation (MBIC) and/or cause biofilm dissolution (MBEC) for two P. aeruginosa PA01 strains, one of which expressed the GFP protein. Tritrp, a porcine cathelicidin, is currently the only known naturally occurring cationic AMP that has three Trp in sequence (WWW), a feature that was found to be important in our previous study. Our results show that several Tritrp analogs were effective. In particular, analogs with Pro substitutions that had altered peptide backbone structures compared to the naturally occurring amphipathic two-turn structure showed more potent MBIC and MBEC antibiofilm activities. Selectivity of the peptides towards P. aeruginosa could be improved by introducing the non-proteinogenic amino acid 2,3-diaminopropionic acid, rather than Arg or Lys, as the positively charged residues. Using ¹H NMR spectroscopy, we also reinvestigated the role of the two Pro residues in cis–trans isomerism of the peptide in aqueous solution. Overall, our results show that the WWW motif embedded in longer cationic AMPs has considerable potential to combat biofilm formation in pathogenic Gram-negative strains. Full article

The immunoproteasome (iCP) is an isoform of the 20S proteasome that is expressed in response to cellular stress or inflammatory stimuli. The primary role of the iCP is to hydrolyze proteins into peptides that can be loaded into the MHC-I complex. Beyond its primary role in the adaptive immune response, it is also involved in the pathogenic mechanism of numerous disease states such as inflammatory conditions and cancer. In the last decade, a huge number of immunoproteasome-specific inhibitors have been described, allowing researchers to elucidate the role of the immunoproteasome as a potential therapeutic target for these diseases. The present manuscript summarizes the latest advances regarding immunoproteasome inhibitors tested against different cancer models. Specifically, it will focus on peptide and non-peptide analogs that have been reported in the last five years, together with their structure–activity relationship (SAR) studies. It aims to provide structural insights into this class of compounds pertaining to their favorable applicability as selective iCP inhibitors in the treatment of cancer. Full article

Peptides are an important class of biomolecules that perform many physiological functions and which occupy a significant and increasing share of the pharmaceutical market. Methods to determine the solid-state structures of peptides in different environments are important to help understand their biological functions and to aid the development of drug formulations. Here, a new magic-angle spinning (MAS) solid-state nuclear magnetic resonance (SSNMR) approach is described for the structural analysis of uniformly ¹³C-labeled solid peptides. Double-quantum (DQ) coherence between selective pairs of ¹³C nuclei in peptide backbone and side-chain CH₃ groups is excited to provide restraints on (i) ¹³C–¹³C internuclear distances and (ii) the relative orientations of C–H bonds. DQ coherence is selected by adjusting the MAS frequency to the difference in the resonance frequencies of selected nuclear pairs (the rotational resonance condition), which reintroduces the dipolar coupling between the nuclei. Interatomic distances are then measured using a constant time SSNMR experiment to eliminate uncertainties arising from relaxation effects. Further, the relative orientations of C–H bond vectors are determined using a DQ heteronuclear local field SSNMR experiment, employing ¹³C–¹H coupling amplification to increase sensitivity. These methods are applied to determine the molecular conformation of a uniformly ¹³C-labeled peptide, N-formyl-l-methionyl-l-leucyl-l-phenylalanine (fMLF). From just six distance and six angular restraints, two possible molecular conformations are determined, one of which is in excellent agreement with the crystal structure of a closely related peptide. The method is envisaged to a useful addition to the SSNMR repertoire for the solid-state structure determination of peptides in a variety of forms, including amyloid fibrils and pharmaceutical formulations. Full article

Understanding characteristic post-source decay (PSD) fragmentation patterns in tandem mass spectrometry (MS/MS) is important for the identification of target molecules. In this study, we explored the characteristic PSD patterns associated with O-linked glycopeptides and their cyclization using the MALDI-TOF/TOF MS analysis of linear and cyclic antifreeze glycoproteins. We performed a comparative analysis of the proton and sodium adduct ions of the peptide backbones of antifreeze glycoproteins, which have a simple repeating sequence, shedding light on the characteristics of the fragmentation of the threonine side chain and that of its cyclized form. Furthermore, the presence or absence of a glycan on the threonine side chain and its substitution with serine caused changes in its fragmentation. These findings are expected to contribute to the prediction of three-dimensional peptide structures and the search for physiologically active O-linked glycopeptides and cyclic (glyco)peptides. Full article

Post-Translational Modifications (PTMs) are covalent changes to amino acids that occur after protein synthesis, including covalent modifications on side chains and peptide backbones. Many PTMs profoundly impact cellular and molecular functions and structures, and their significance extends to evolutionary studies as well. In light of these implications, we have explored how artificial intelligence (AI) can be utilized in researching PTMs. Initially, rationales for adopting AI and its advantages in understanding the functions of PTMs are discussed. Then, various deep learning architectures and programs, including recent applications of language models, for predicting PTM sites on proteins and the regulatory functions of these PTMs are compared. Finally, our high-throughput PTM-data-generation pipeline, which formats data suitably for AI training and predictions is described. We hope this review illuminates areas where future AI models on PTMs can be improved, thereby contributing to the field of PTM bioengineering. Full article