Search Results (111)

The design and synthesis of a small library of 2-styrylquinoline derivatives containing a push-pull system, aimed at displacing their fluorescence emission towards the NIR region, is described. We describe here their synthesis, fluorescent characterization and pharmacological evaluation against different amyloid proteins. Their study showed that these compounds are capable to change their spectroscopic properties upon protein interaction, resulting in changes in the absorption and emission wavelengths, together with increased fluorescence intensity. They also showed sensitivity to pH and environment polarity, exhibiting red shifts in lower polarity environments with regard to aqueous media. Inner charge transfer is observed and employed for detecting the interaction of these compounds with protein aggregates. The study of the alterations in the fluorescence intensity allows to calculate the dissociation constant values for the protein-sensor interaction. These spectroscopic results were the basis for the use of these compounds to visualize β-amyloid plates with selectivity over phosphorylated tau in samples of cerebral tissue from deceased Alzheimer patients under fluorescence microscopy, using immunofluorescence techniques. Pharmacological assays showed that the compounds inhibit the aggregation of the Aβ_1–42 and AcPHF6 peptides, representing tau protein. They also showed neuroprotective activity following okadaic acid insult. Full article

Conventional methods for generating knock-out or knock-in mammalian cell models using CRISPR-Cas9 genome editing often require tedious single-cell clone selection and expansion. In this study, we develop and optimise rapid and robust strategies to engineer homozygous fluorescent reporter knock-in cell pools with precise genome editing, circumventing clonal variability inherent to traditional approaches. To reduce false-positive cells associated with random integration, we optimise the design of donor DNA by removing the start codon of the fluorescent reporter and incorporating a self-cleaving T2A peptide system. Using fluorescence-assisted cell sorting (FACS), we efficiently identify and isolate the desired homozygous fluorescent knock-in clones, establishing stable cell pools that preserve parental cell line heterogeneity and faithfully reflect endogenous transcriptional regulation of the target gene. We evaluate the knock-in efficiency and rate of undesired random integration in the electroporation method with either a dual-plasmid system (sgRNA and donor DNA in two separate vectors) or a single-plasmid system (sgRNA and donor DNA combined in one vector). We further demonstrate that coupling our single-plasmid construct with an integrase-deficient lentivirus vector (IDLV) packaging system efficiently generates fluorescent knock-in reporter cell pools, offering flexibility between electroporation and lentivirus transduction methods. Notably, compared to the electroporation methods, the IDLV system significantly minimises random integration. Moreover, the resulting reporter cell lines are compatible with most of the available genome-wide sgRNA libraries, enabling unbiased CRISPR screens to identify key transcriptional regulators of a gene of interest. Overall, our methodologies provide a powerful genetic tool for rapid and robust generation of fluorescent reporter knock-in cell pools with precise genome editing by CRISPR-Cas9 for various research purposes. Full article

Phage display has advanced the discovery of peptides that selectively bind to a wide variety of cell surface molecules, offering new modalities to modulate disease-related protein–protein interactions (PPIs). These cell-binding peptides occupy a unique pharmaceutical space between small molecules and large biologics, and their growing popularity has opened up new avenues for targeting cell surface proteins that were previously considered undruggable. This work provides an overview of methods for identifying cell-selective peptides using phage display combinatorial libraries, covering in vitro, ex vivo, and in vivo biopanning approaches. It addresses key considerations in library design, including the peptide conformation (linear vs. cyclic) and length, and highlights examples of clinically approved peptides developed through phage display. It also discusses the on-phage chemical cyclization of peptides to overcome the limitations of genetically encoded disulfide bridges and emphasizes advances in combining next-generation sequencing (NGS) with phage display to improve peptide selection and analysis workflows. Furthermore, due to the often suboptimal binding affinity of peptides identified in phage display selections, this article discusses affinity maturation techniques, including random mutagenesis and rational design through structure–activity relationship (SAR) studies to optimize initial peptide candidates. By integrating these developments, this review outlines practical strategies and future directions for harnessing phage display in targeting challenging cell surface proteins. Full article

The development of orally bioavailable non-peptidomimetic glucagon-like peptide-1 receptor agonists (GLP-1RAs) offers a promising therapeutic avenue for the treatment of type 2 diabetes mellitus (T2DM) and obesity. An extensive in silico approach combining structure-based drug design and ligand-based strategies together with pharmacokinetic properties and drug-likeness predictions is implemented to identify novel non-peptidic GLP-1RAs from the COCONUT and Marine Natural Products (CMNPD) libraries. More than 700,000 compounds were screened by shape-based similarity filtering in combination with precision docking against the orthosteric site of the GLP-1 receptor (PDB ID: 6X1A). The docked candidates were further assessed with the molecular mechanics MM-GBSA tool to check the binding affinities; the final list of candidates was validated by running a 500 ns long MD simulation. Twenty final hits were identified, ten from each database. The hits contained compounds with reported antidiabetic effects but with no evidence of GLP-1 agonist activity, including hits 1, 6, 7, and 10. These findings proposed a novel mechanism for these hits through GLP-1 activity and positioned the other hits as potential promising scaffolds. Among the studied compounds—especially hits 1, 5, and 9—possessed strong and stable interactions with critical amino acid residues such as TRP-203, PHE-381, and GLN-221 at the active site of the 6X1A-substrate along with favorable pharmacokinetic profiles. Moreover, the RMSF and RMSD plots further suggested the possibility of stable interactions. Specifically, hit 9 possessed the best docking score with a ΔG_bind value of −102.78 kcal/mol, surpassing even the control compound in binding affinity. The ADMET profiling also showed desirable drug-likeness and pharmacokinetic characteristics for hit 9. The pipeline of computational integration underscores the potential of non-peptidic alternatives in natural product libraries to pursue GLP-1-mediated metabolic therapy into advanced preclinical validation. Full article

Background: Peptide receptor radionuclide therapy (PRRT) could be a therapeutic option for patients with advanced, recurrent or progressing meningiomas overexpressing somatostatin receptors. The aim of this study is to perform an updated meta-analysis to establish the disease control rate of PRRT in these patients. Methods: A comprehensive literature search of studies on PRRT in patients with advanced, recurrent or progressing meningioma was carried out. Four different databases (PubMed/MEDLINE, EMBASE, Cochrane library, Google Scholar) were screened until April 2025. Only original articles about PRRT in advanced, progressive or refractory meningiomas were selected. Case reports were excluded. Three review authors independently performed the literature search, the article selection and the data extraction. Main findings of eligible studies were summarized and a proportion meta-analysis on the disease control rate was carried out using a random-effects model. Results: In total, 18 studies (269 patients) published from 2006 to 2025 were included in the analysis. In most of the included studies, PRRT was performed using [¹⁷⁷Lu]Lu-DOTATATE. The pooled disease control rate was 67.7% (95% confidence interval values: 59.6–75.7%). PRRT was well-tolerated in most patients with advanced, recurrent or progressive meningioma. Moderate statistical heterogeneity was found in the meta-analysis (I-square: 53%). Conclusions: PRRT is an effective and well-tolerated treatment in patients with advanced, progressive or recurrent meningiomas, showing a significant disease control rate (in about two-thirds of patients). Even if well-designed clinical trials are needed to corroborate these findings, evidence-based data seem to support the clinical use of PRRT for this indication. Full article

Objective: We developed a targeted integration-based CHO cell platform for simultaneous antibody display and secretion, enabling a streamlined transition from antibody library screening to production without requiring the re-cloning of antibody genes. Methods: The platform consists of a CHO master cell line with a single-copy landing pad, a helper vector expressing FLPe recombinase, and bi-functional targeting vectors. Recombinase-mediated cassette exchange was utilized to integrate targeting vectors into the landing pad. Bi-functional vectors were designed by incorporating a minimal furin cleavage sequence (mFCS), RRKR, and various 2A peptides between the heavy chain (HC) and a membrane anchor. Results: Incomplete cleavage at the mFCS and 2A sites facilitated the expression of both membrane-bound and secreted antibodies, while mutations in the 2A peptide produced a range of display-to-secretion ratios. However, a fraction of secreted antibodies retained 2A residues attached to the HC polypeptides. Further analysis demonstrated that modifying the first five amino acids of the 2A peptide significantly influenced furin cleavage efficiency, resulting in different display-to-secretion ratios for targeting vectors containing mFCS-2A variant combinations. To overcome this, we designed nine-amino-acid FCS variants that, when placed between the HC and membrane anchor, provided a range of display-to-secretion ratios and eliminated the issue of attached 2A residues in the secreted antibodies. Vectors with lower display levels proved more effective at distinguishing cells expressing high-affinity antibodies with closely matched binding affinities. The platform also demonstrated high sensitivity in isolating high-affinity antibody-expressing cells and supported robust antibody production. Conclusion: This targeted integration-based CHO platform enables efficient, in-format screening and production of antibodies with tunable display-to-secretion profiles. It provides a powerful and scalable tool for accelerating the development of functional, manufacturable therapeutic antibodies. Full article

Molecular modelling is a vital tool in the discovery and characterisation of bioactive peptides, providing insights into their structural properties and interactions with biological targets. Many models predicting bioactive peptide function or structure rely on their intrinsic properties, including the influence of amino acid composition, sequence, and chain length, which impact stability, folding, aggregation, and target interaction. Homology modelling predicts peptide structures based on known templates. Peptide–protein interactions can be explored using molecular docking techniques, but there are challenges related to the inherent flexibility of peptides, which can be addressed by more computationally intensive approaches that consider their movement over time, called molecular dynamics (MD). Virtual screening of many peptides, usually against a single target, enables rapid identification of potential bioactive peptides from large libraries, typically using docking approaches. The integration of artificial intelligence (AI) has transformed peptide discovery by leveraging large amounts of data. AlphaFold is a general protein structure prediction tool based on deep learning that has greatly improved the predictions of peptide conformations and interactions, in addition to providing estimates of model accuracy at each residue which greatly guide interpretation. Peptide function and structure prediction are being further enhanced using Protein Language Models (PLMs), which are large deep-learning-derived statistical models that learn computer representations useful to identify fundamental patterns of proteins. Recent methodological developments are discussed in the context of canonical peptides, as well as those with modifications and cyclisations. In designing potential peptide therapeutics, the main outstanding challenge for these methods is the incorporation of diverse non-canonical amino acids and cyclisations. Full article

Background: Proteolytic cleavage of inactive pathogen proteins by furin is critical for their entry into human cells, and thus furin cleavage of the SARS-CoV-2 spike protein was identified as a prerequisite for virus binding and the subsequent infection of human cells in the recent COVID-19 pandemic. We report a water-aware structure-based protease inhibitor design study. Methods: Our efforts focused on the biological evaluation of small molecule inhibitors that emerged from a conserved water-aware virtual screening campaign of a library of compounds that shared structural or physicochemical properties with known furin inhibitors exhibiting newly recognized binding modes. Results: We identified a novel small-molecule furin protease inhibitor with a 1,3-thiazol-2-ylaminosulfonyl scaffold. Namely, the compound N-[4-(1,3-thiazol-2-ylaminosulfonyl)phenyl]-3-{(E)-5-[(2-methoxyphenyl)methylene]-4-oxo-2-thioxo-1,3-thiazolidin-3-yl}propionamide showed an IC₅₀ value of 17.58 μM, comparable to other published inhibitors. Conclusions: This compound could represent a starting point for the further design and development of non-peptidic, small-molecule furin inhibitors that could assist in furin cleavage studies and coronaviral pathogenesis. Full article

Snakebite is a critical global public health issue, causing substantial mortality and morbidity, particularly in tropical and subtropical regions. The development of innovative antivenoms targeting snake venom toxins is therefore of paramount importance. In this study, we adopted an epitope-directed approach to design three degenerate 15-mer peptides based on amino acid sequence alignments of snake venom phospholipase A₂s (PLA₂s) and snake venom serine proteases (SVSPs) from snake (Crotalus atrox). By leveraging their immunogenic and inhibitory profiles, these peptides were specifically designed to target the Asp49 and Lys49 variants of PLA₂ and SVSP toxins. Groups of five mice were immunized with each peptide, and IgG mRNA was subsequently extracted from peripheral blood mononuclear cells (PBMCs) and spleen lymphocytes of the top three responders. The extracted mRNA was reverse-transcribed into complementary DNA (cDNA), and the variable regions of the IgG heavy and kappa chains were amplified using polymerase chain reaction (PCR). These amplified regions were then linked with a 66-nucleotide spacer to construct single-chain variable fragments (scFvs). Sequence analysis of 48 randomly selected plasmids from each PLA₂ and SVSP scFv library revealed that over 80% contained scFv sequences with notable diversity observed in the complementarity-determining regions (CDRs), particularly CDR3. Enzyme-linked immunosorbent assay (ELISA) results demonstrated that the SP peptide elicited a broader immune response in mice compared to the Asp49 peptide, implying the strong immunogenicity of the SP peptide. These scFvs represent a promising foundation for the development of recombinant human monoclonal antibodies targeting snake PLA₂ and SVSP toxins, providing a potential therapeutic strategy for the treatment of snakebites. Full article

Small-molecule probes are powerful tools for studying biological systems and can serve as lead compounds for developing new therapeutics. Especially, nitrogen heterocycles are of considerable importance in the pharmaceutical field. These compounds are found in numerous bioactive structures. Their synthesis often requires several steps or the use of functionalized starting materials. This review describes the use of vicinal diamines generated from modified short peptides to access substituted diaza- and triazacyclic compounds. Small-molecule diaza- and triazacyclic compounds with different substitution patterns and embedded in various molecular frameworks constitute important structure classes in the search for bioactivity. The compounds are designed to follow known drug likeness rules, including “Lipinski’s Rule of Five”. The screening of diazacyclic and traizacyclic libraries has shown the utility of these classes of compounds for the de novo identification of highly active compounds, including antimalarials, antimicrobial compounds, antifibrotic compounds, potent analgesics, and antitumor agents. Examples of the synthesis of diazacyclic and triazacyclic small-molecule libraries from vicinal chiral polyamines generated from modified short peptides and their application for the identification of highly active compounds are described. Full article

Background: The persistence of antibiotic resistance has incited a strong interest in the discovery of agents with novel antimicrobial mechanisms. The direct killing of multidrug-resistant bacteria by cationic antimicrobial peptides (AMPs) underscores their importance in the fight against infections associated with antibiotic resistance. Despite a vast body of AMP literature demonstrating a plurality in structural classes, AMP engineering has been largely skewed toward peptides with idealized amphipathic helices (H-amphipathic). In contrast to helical amphipathicity, we designed a series of peptides that display the amphipathic motifs in the primary structure. We previously developed a rational framework for designing AMP libraries of H-amphipathic peptides consisting of Arg, Trp, and Val (H-RWV, with a confirmed helicity up to 88% in the presence of membrane lipids) tested against the most common MDR organisms. Methods: In this study, we re-engineered one of the series of the H-RWV peptides (8, 10, 12, 14, and 16 residues in length) to display the amphipathicity in the primary structure by side-by-side (linear) alignment of the cationic and hydrophobic residues into the 2 separate linear amphipathic (L-amphipathic) motifs. We compared the 2 series of peptides for antibacterial activity, red blood cell (RBC) lysis, killing and membrane-perturbation properties. Results: The L-RWV peptides achieved the highest antibacterial activity at a minimum length of 12 residues (L-RWV12, minimum optimal length or MOL) with the lowest mean MIC of 3–4 µM, whereas the MOL for the H-RWV series was reached at 16 residues (H-RWV16). Overall, H-RWV16 displayed the lowest mean MIC at 2 µM but higher levels of RBC lysis (25–30%), while the L-RWV series displayed minor RBC lytic effects at the test concentrations. Interestingly, when the S. aureus strain SA719 was chosen because of its susceptibility to most of the peptides, none of the L-RWV peptides demonstrated a high level of membrane perturbation determined by propidium iodide incorporation measured by flow cytometry, with <50% PI incorporation for the L-RWV peptides. By contrast, most H-RWV peptides displayed almost up to 100% PI incorporation. The results suggest that membrane perturbation is not the primary killing mechanism of the L-amphipathic RWV peptides, in contrast to the H-RWV peptides. Conclusions: Taken together, the data indicate that both types of amphipathicity may provide different ideal pharmacological properties that deserve further investigation. Full article

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability. Full article

Foot-and-mouth disease (FMD) is a highly infectious disease of cloven-hoofed animals with a significant economic impact. Early diagnosis and effective prevention and control could reduce the spread of the disease which could possibly minimize economic losses. Epitope characterization based on monoclonal antibodies provide essential information for developing diagnostic assays and vaccine designs. In this study, monoclonal antibodies raised against FMD virus (FMDV) were produced. Sixty-six monoclonal antibodies demonstrated strong reactivity and specificity to FMDV. The purified monoclonal antibodies were further used for bio-panning to select phage expressing specific epitopes from phage-displayed 12 mer-peptide library. The phage peptide sequences were analyzed using multiple sequence alignment and evaluated by peptide ELISA. Two hybridoma clones secreted monoclonal antibodies recognizing linear epitopes on VP2 of FMDV serotype O. The non-neutralizing monoclonal antibody 6F4.D11.B6 recognized the residues 67–78 on antigenic site 2 resinding in VP2, while the neutralizing monoclonal antibody 8D6.B9.C3 recognized a novel linear epitope encompassing residues 115–126 on VP2. This information and the FMDV-specific monoclonal antibodies provide valuable sources for further study and application in diagnosis, therapeutics and vaccine designs to strengthen the disease prevention and control measures. Full article

In the realm of quantitative proteomics, data-independent acquisition (DIA) has emerged as a promising approach, offering enhanced reproducibility and quantitative accuracy compared to traditional data-dependent acquisition (DDA) methods. However, the analysis of DIA data is currently hindered by its reliance on project-specific spectral libraries derived from DDA analyses, which not only limits proteome coverage but also proves to be a time-intensive process. To overcome these challenges, we propose ProPept-MT, a novel deep learning-based multi-task prediction model designed to accurately forecast key features such as retention time (RT), ion intensity, and ion mobility (IM). Leveraging advanced techniques such as multi-head attention and BiLSTM for feature extraction, coupled with Nash-MTL for gradient coordination, ProPept-MT demonstrates superior prediction performance. Integrating ion mobility alongside RT, mass-to-charge ratio (m/z), and ion intensity forms 4D proteomics. Then, we outline a comprehensive workflow tailored for 4D DIA proteomics research, integrating the use of 4D in silico libraries predicted by ProPept-MT. Evaluation on a benchmark dataset showcases ProPept-MT’s exceptional predictive capabilities, with impressive results including a 99.9% Pearson correlation coefficient (PCC) for RT prediction, a median dot product (DP) of 96.0% for fragment ion intensity prediction, and a 99.3% PCC for IM prediction on the test set. Notably, ProPept-MT manifests efficacy in predicting both unmodified and phosphorylated peptides, underscoring its potential as a valuable tool for constructing high-quality 4D DIA in silico libraries. Full article

SARS-CoV-2 is the pathogen responsible for the most recent global pandemic, which has claimed hundreds of thousands of victims worldwide. Despite remarkable efforts to develop an effective vaccine, concerns have been raised about the actual protection against novel variants. Thus, researchers are eager to identify alternative strategies to fight against this pathogen. Like other opportunistic entities, a key step in the SARS-CoV-2 lifecycle is the maturation of the envelope glycoprotein at the RARR685↓ motif by the cellular enzyme Furin. Inhibition of this cleavage greatly affects viral propagation, thus representing an ideal drug target to contain infection. Importantly, no Furin-escape variants have ever been detected, suggesting that the pathogen cannot replace this protease by any means. Here, we designed a novel fluorogenic SARS-CoV-2-derived substrate to screen commercially available and custom-made libraries of small molecules for the identification of new Furin inhibitors. We found that a peptide substrate mimicking the cleavage site of the envelope glycoprotein of the Omicron variant (QTQTKSHRRAR-AMC) is a superior tool for screening Furin activity when compared to the commercially available Pyr-RTKR-AMC substrate. Using this setting, we identified promising novel compounds able to modulate Furin activity in vitro and suitable for interfering with SARS-CoV-2 maturation. In particular, we showed that 3-((5-((5-bromothiophen-2-yl)methylene)-4-oxo-4,5 dihydrothiazol-2-yl)(3-chloro-4-methylphenyl)amino)propanoic acid (P3, IC₅₀ = 35 μM) may represent an attractive chemical scaffold for the development of more effective antiviral drugs via a mechanism of action that possibly implies the targeting of Furin secondary sites (exosites) rather than its canonical catalytic pocket. Overall, a SARS-CoV-2-derived peptide was investigated as a new substrate for in vitro high-throughput screening (HTS) of Furin inhibitors and allowed the identification of compound P3 as a promising hit with an innovative chemical scaffold. Given the key role of Furin in infection and the lack of any Food and Drug Administration (FDA)-approved Furin inhibitor, P3 represents an interesting antiviral candidate. Full article