Search Results (1,869)

Antibody–drug conjugates (ADCs) are a rapidly advancing class of targeted cancer therapeutics that couple the antigen specificity of monoclonal antibodies (mAbs) with the potent cytotoxicity of small-molecule drugs. In their core design, a tumor-targeting antibody is covalently linked to a cytotoxic payload via a chemical linker, enabling the selective delivery of highly potent agents to malignant cells while sparing normal tissues, thereby improving the therapeutic index. Humanized and fully human immunoglobulin G1(IgG1) antibodies are the most common ADC backbones due to their stability in systemic circulation, robust Fcγ receptor engagement for immune effector functions, and reduced immunogenicity. Antibody selection requires balancing tumor specificity, internalization rate, and binding affinity to avoid barriers to tissue penetration, such as the binding-site barrier effect, while emerging designs exploit tumor-specific antigen variants or unique post-translational modifications to further enhance selectivity. Advances in antibody engineering, linker chemistry, and payload innovation have reinforced the clinical success of ADCs, with more than a dozen agents FDA approved for hematologic malignancies and solid tumors and over 200 in active clinical trials. This review critically examines established and emerging conjugation strategies, including lysine- and cysteine-based chemistries, enzymatic tagging, glycan remodeling, non-canonical amino acid incorporation, and affinity peptide-mediated methods, and discusses how conjugation site, drug-to-antibody ratio (DAR) control, and linker stability influence pharmacokinetics, efficacy, and safety. Innovations in site-specific conjugation have improved ADC homogeneity, stability, and clinical predictability, though challenges in large-scale manufacturing and regulatory harmonization remain. Furthermore, novel ADC architectures such as bispecific ADCs, conditionally active (probody) ADCs, immune-stimulating ADCs, protein-degrader ADCs, and dual-payload designs are being developed to address tumor heterogeneity, drug resistance, and off-target toxicity. By integrating mechanistic insights, preclinical and clinical data, and recent technological advances, this work highlights current progress and future directions for next-generation ADCs aimed at achieving superior efficacy, safety, and patient outcomes, especially in treating refractory cancers. Full article

A novel Gram-negative bacterium, designated strain SN16^T, was isolated from a harmful algal bloom (HAB). Strain SN16^T exhibited potent, broad-spectrum algicidal activity against the colony-forming alga Phaeocystis globosa and eight other HAB-causing species, highlighting its potential as a promising candidate for the biological control of HABs. A phylogenetic analysis of 16S rRNA gene sequences placed strain SN16^T within the genus Flagellimonas. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between strain SN16^T and its relatives were 75.4–91.4% and 19.3–44.0%, respectively. These values fall below the established thresholds for species delineation, confirming that SN16^T represents a novel species. A chemotaxonomic analysis revealed its dominant cellular fatty acids to be iso-C_15:0 and iso-C_15:1 G. The major polar lipid was phosphatidylethanolamine, and the primary respiratory quinone was menaquinone-6. Genome mining identified 11 biosynthetic gene clusters (BGCs), including those encoding for terpenes, ribosomal peptide synthetases, and non-ribosomal peptide synthetases. By integrating BGC analysis with the observed algicidal activities, we predicted that pentalenolactone and xiamycin analogues are the likely causative compounds. Based on this polyphasic evidence, strain SN16^T is proposed as a novel species of the genus Flagellimonas, named Flagellimonas algicida sp. nov. This is the first report of Flagellimonas species exhibiting broad-spectrum algicidal activity, including activity against the colonial form of P. globosa—a key ecological challenge in HAB mitigation. Full article

The potential of N-terminal mitochondrial-targeting sequences (MTSs) as potent antimicrobial peptides (AMPs) has been previously reported. Building on this, 3923 mitochondrial proteins were identified from various marine organisms, among which 470 MTSs were predicted using MitoFates. Of these, 25 MTSs were synthesized and assessed for antimicrobial activity. All MTSs exhibited antifungal activity against Candida albicans, while 22 and 20 MTSs demonstrated activity against Escherichia coli and Staphylococcus aureus, respectively. Notably, the MTS of methylcrotonyl-CoA carboxylase subunit 1 (MCCC1-MTS) derived from swimming crab (Portunus trituberculatus) and the MTS of dihydrolipoamide branched-chain transacylase E2 (DBT-MTS) derived from herring (Oncorhynchus keta) showed strong antimicrobial activity against both Gram-positive and Gram-negative bacteria, as well as fungi. In addition, MCCC1-MTS markedly reduced the viability of multiple cancer cell lines with minimal cytotoxicity toward HaCaT cells and effectively suppressed the growth of A549-xenografted tumors in BALB/c nude mice without inducing weight loss. These findings demonstrate that MTSs derived from marine organisms function as potent AMPs with selective cytotoxicity toward cancer cells, further supporting previous evidence that protozoan MTSs represent novel AMP candidates. Full article

Bioactive peptides have significant potential for applications in pharmaceuticals, the food industry, and cosmetics due to their wide spectrum of biological activities. However, their pronounced structural and functional heterogeneity complicates the classification and prediction of biological activity. This study uses data from the PepLab platform, comprising 2748 experimentally confirmed bioactive peptides distributed across 15 functional classes, including ACE inhibitors, antimicrobial, anticancer, antioxidant, toxins, and others. For each peptide, the amino acid sequence and key physicochemical descriptors are provided, calculated via the integrated DMPep module, such as GRAVY index, aliphatic index, isoelectric point, molecular weight, Boman index, and sequence length. The dataset exhibits class imbalance, with class sizes ranging from 14 to 524 peptides. An innovative methodology is proposed, combining descriptive statistical analysis, structural modeling via DEMATEL, and structural equation modeling with neural networks (SEM-NN), where SEM-NN is used to capture complex nonlinear causal relationships between descriptors and functional classes. The results of these dependencies are integrated into a multi-class machine learning model to improve interpretability and predictive performance. Targeted data augmentation was applied to mitigate class imbalance. The developed classifier achieved predictive accuracy of up to 66%, a relatively high value given the complexity of the problem and the limited dataset size. These results confirm that integrating structured dependency modeling with artificial intelligence is an effective approach for functional peptide classification and supports the rational design of novel bioactive molecules. Full article

This study valorized camel milk residue (CMR) via optimized bacterial fermentation to produce bioactive peptides with hypoglycemic potential. Screening of eleven bacterial strains identified four optimal starters. Artificial neural network (ANN) simulation significantly outperformed response surface methodology (RSM) in modeling and prediction, as evidenced by its superior performance in key statistical metrics, including R², RMSE, and AAD(%), ultimately achieving a maximized yield of TCA-soluble nitrogen (TCA). Under optimized conditions, a TCA yield of 39.8% was achieved and experimentally validated. Ultrafiltration yielded a highly bioactive peptide fraction (<1 kDa), which exhibited significant inhibition of α-amylase (80.7%) and α-glucosidase (32.0%). The peptides exhibited high stability under various conditions, highlighting their industrial potential. This study explores the application of ANN-RSM optimization for the valorization of camel milk residue (CMR). Our findings provide a sustainable strategy for transforming CMR into a high-value anti-diabetic ingredient, which could contribute to extending the camel milk value chain. Full article

Background: Skin aging is mainly associated with oxidative stress and enzymatic degradation of collagen and elastin by protease activity. Peptides have antioxidant capacity and inhibitory effects on protease enzymes. Objective: The purpose of this study was to obtain peptides with in vitro anti-aging activity from the enzymatic hydrolysis of bovine casein with actinidin, a protease extracted from the green kiwi fruit (Actinidia deliciosa) Methodology: The enzyme actinidin was extracted from the pulp of the kiwi fruit, purified by ion exchange chromatography and characterized by polyacrylamide electrophoresis (SDS-PAGE). Subsequently, the extracted enzyme was used to hydrolyze commercial bovine casein at 37 °C for 30 min, precipitating the peptide fraction with trichloroacetic acid (TCA), and centrifuged. To determine the anti-aging potential of the peptides in vitro, antioxidant activity was evaluated using the ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) radical. Additionally, the inhibitory capacity of the peptides against collagenase and elastase enzymes was also studied. To complement the in vitro results, the enzymatic hydrolysis of casein with actinidin was simulated. The binding energy (ΔG) of each of the hydrolysates with the collagenase and elastase enzymes was calculated using molecular docking to predict the peptide sequences with the highest probability of interaction. Results: Actinidin was extracted and purified exhibiting a molecular weight close to 27 kDa. The enzyme hydrolyzed the substrate by 91.6%, and the resulting hydrolysates showed moderate in vitro anti-aging activity: antioxidant (17.5%), anticollagenase (18.55%), and antielastase (28.6%). In silico results revealed 66 peptide sequences of which 30.3% consisted of 4–8 amino acids, a suitable size to facilitate interaction with structural targets. The sequences with the highest affinity were FALPQYLK and VIPYVRYL for collagenase and elastase, respectively. Conclusions: Despite the modest inhibition values, the use of a fruit-derived enzyme and a food-grade substrate is in line with current trends in sustainable and natural cosmetics. These findings highlight the great potential for laying the groundwork for future research into actinidin-derived peptides as multifunctional and eco-conscious ingredients for the development of next-generation anti-aging formulations. Full article

Bacillus cereus AS_3 and Bacillus cereus AS_5 are bacterial endophytes isolated from sterilized leaves of the medical plant Alectra sessiliflora, which were previously identified using 16S rRNA sequencing. Here, we present the whole-genome sequencing and annotation of strains AS_3 and AS_5, the first genome report of Bacillus cereus strains from A. sessiliflora. The genome of strain AS_3 has 59 contigs, 5 503 542 bp draft circular chromosome, an N₅₀ of 211,274 bp, and an average G+C content of 35.2%; whereas strain AS_5 has 38 contigs, 5,510,121 bp draft circular chromosome, an N₅₀ of 536,033 bp, and an average G+C content of 35.2%. A total of 5679 protein-coding genes, 62 genes coding for RNAs, and 122 pseudogenes in the strain AS_3 genome were identified by the National Center for Biotechnology Information Prokaryotic Annotation pipeline, whereas a total of 5688 gene protein-coding genes were identified in AS_5, with 60 genes coding for RNAs and 120 pseudogenes. Phenotypic analysis and whole-genome sequencing analysis showed that AS_3 and AS_5 share similar characteristics, including Gram-positive, motile, rod-shaped, and endospore-forming have shown a high sequence similarity with Bacillus cereus, type strain ATCC 14579^T. Strains AS_3 and AS_5 had genomic digital DNA–DNA hybridization (dDDH) with the type strain Bacillus cereus ATCC 14579^T of 85.8% and 86%, respectively, and average nucleotide identities (ANIs) of 98% and 98.01%, respectively. Phylogenomic analysis confirmed that strains AS_3 and AS_5 share very similar genomic and phenotypic characteristics, and are closely related to the type strain Bacillus cereus type strain ATCC 14579^T, supporting their classification within the Bacillus cereus species. A total of 10 secondary metabolite gene clusters, including siderophore type petrobactin, terpene type molybdenum cofactor, non-ribosomal peptide synthetase (NRPS) type bacillibactin, and β-lactone type fengycin, were predicted using AntiSMASH software (version 5.0). Putative genes potentially involved in bioremediation and endophytic lifestyle were identified in the genome analysis. Genome sequencing of Bacillus cereus AS_3 and Bacillus cereus AS_5 has provided genomic information and demonstrated potential biotechnological applications. Full article

Rugulopteryx okamurae is an invasive brown alga that has colonised Mediterranean and northeastern Atlantic coastlines, posing significant ecological and economic challenges. Its biomass is rich in structurally diverse metabolites—including polysaccharides (alginate, fucoidan, laminaran), phlorotannins, diterpenoids, fatty acids, and peptides—many of which exhibit notable antioxidant, anti-inflammatory, antimicrobial, and anticancer activities. Comparative assessment of extraction yields, structural features, and bioactivity data highlights phlorotannins and diterpenoids as particularly promising, demonstrating low-micromolar potencies and favourable predicted interactions with key inflammatory and apoptotic targets. Algal polysaccharides exhibit various bioactivities but hold strong potential for scalable and sustainable industrial applications. Emerging compound classes such as fatty acids and peptides display niche bioactivities; however, their structural diversity and mechanisms of action remain insufficiently explored. Insights from in vitro and in silico studies suggest that phlorotannins may modulate NF-κB and MAPK signalling pathways, while diterpenoids are implicated in the induction of mitochondrial apoptosis. Despite these findings, inconsistent extraction methodologies and a lack of in vivo pharmacokinetic and efficacy data limit translational potential. To overcome these limitations, standardized extraction protocols, detailed structure–activity relationship (SAR) and pharmacokinetic studies, and robust in vivo models are urgently needed. Bioactivity-guided valorisation strategies, aligned with ecological management, could transform R. okamurae biomass into a sustainable source for functional foods, cosmetics, and pharmaceuticals applications. Full article

Peptide therapeutics often fall outside classical small-molecule heuristics, such as Lipinski’s Rule of Five (Ro5), motivating the development of adapted filters and data-driven approaches to early drug-likeness assessment. We curated >300 k drug (small and peptide) and non-drug molecules from PubChem, extracted key molecular descriptors with RDKit, and generated three rule-violation counters for Ro5, the peptide-oriented beyond-Ro5 (bRo5) extension, and Muegge’s criteria. Random Forest (RF) classifier and regressor models (with 10, 20, and 30 trees) were trained and evaluated. Predictions for 26 peptide test molecules were compared with those from SwissADME, Molinspiration, and manual calculations. Model metrics were uniformly high (Ro5 accuracy/precision/recall = 1.0; Muegge ≈ 0.99), indicating effective learning. Ro5 violation counts matched reference values for 23/26 peptides; the remaining cases differed by +1 violation, reflecting larger structures and platform limits. bRo5 predictions showed near-complete agreement with manual values; minor discrepancies occurred in isolated peptides. Muegge’s predictions were internally consistent but tended to underestimate SwissADME by ~1 violation in several molecules. Four peptides (ML13–16) satisfied bRo5 boundaries; three also fully met Ro5. RF models thus provide fast and reliable in silico filters for peptide drug-likeness and can support the prioritisation of orally developable candidates. Full article

Background/Objectives: Anaerobic gut fungi (Neocallimastigomycota) are biotechnologically relevant, lignocellulose-degrading microbes with under-explored biosynthetic potential for secondary metabolites. Untargeted metabolomic profiling with gas chromatography–mass spectrometry (GC-MS) was applied to two gut fungal strains, Anaeromyces robustus and Caecomyces churrovis, to establish a foundational metabolomic dataset to identify metabolites and provide insights into gut fungal metabolic capabilities. Methods: Gut fungi were cultured anaerobically in rumen-fluid-based media with a soluble substrate (cellobiose), and metabolites were extracted using the Metabolite, Protein, and Lipid Extraction (MPLEx) method, enabling metabolomic and proteomic analysis from the same cell samples. Samples were derivatized and analyzed via GC-MS, followed by compound identification by spectral matching to reference databases, molecular networking, and statistical analyses. Results: Distinct metabolites were identified between A. robustus and C. churrovis, including 2,3-dihydroxyisovaleric acid produced by A. robustus and maltotriitol, maltotriose, and melibiose produced by C. churrovis. C. churrovis may polymerize maltotriose to form an extracellular polysaccharide, like pullulan. GC-MS profiling potentially captured sufficiently volatile products of proteomically detected, putative non-ribosomal peptide synthetases and polyketide synthases of A. robustus and C. churrovis. The triterpene squalene and triterpenoid tetrahymanol were putatively identified in A. robustus and C. churrovis. Their conserved, predicted biosynthetic genes—squalene synthase and squalene tetrahymanol cyclase—were identified in A. robustus, C. churrovis, and other anaerobic gut fungal genera. Conclusions: This study provides a foundational, untargeted metabolomic dataset to unmask gut fungal metabolic pathways and biosynthetic potential and to prioritize future efforts for compound isolation and identification. Full article

Background: Chronic heart failure (CHF) continues to present significant prognostic challenges despite advances in diagnosis and therapy. While the N-terminal prohormone of brain natriuretic peptide (NT-proBNP) is widely recognized as a key marker of cardiac stress, and serum albumin reflects systemic inflammation and nutritional status, their integration into a single parameter—the NT-proBNP-to-albumin ratio (NTAR)—may improve risk stratification. This study aimed to evaluate the NTAR as a novel biomarker for predicting in-hospital mortality in patients with CHF. Methods: We performed an exploratory, retrospective, observational, single-center study involving 542 patients (306 males) admitted for CHF between January 2022 and August 2024. NTAR was calculated as log₁₀(NT-proBNP/albumin). Statistical analyses included ROC curves, univariate and multivariable Cox regression, and Kaplan–Meier survival analysis. Sex-specific performance of NTAR was compared against NT-proBNP and serum albumin alone. Results: Females had significantly lower serum albumin levels than males, while NT-proBNP levels were similar across sexes. NTAR increased with NYHA functional class and was highest in patients with heart failure with reduced ejection fraction (HFrEF). NTAR showed very good discriminatory performance for predicting in-hospital mortality (AUC = 0.840, 95% CI: 0.794–0.879, p < 0.001), marginally but statistically outperforming NT-proBNP in the male subgroup. In univariate Cox regression analyses, higher serum albumin was significantly associated with reduced in-hospital mortality risk in males (HR = 0.352; 95% CI: 0.154–0.803; p = 0.010) and females (HR = 0.169; 95% CI: 0.072–0.399; p < 0.001). Elevated NT-proBNP levels were associated with increased mortality risk in males (HR = 8.627; 95% CI: 1.956–38.042; p < 0.001) and females (HR = 6.060; 95% CI: 1.498–24.521; p = 0.002) with similar findings in NTAR (HR_males = 10.318, 95% CI: 2.452–43.417, p < 0.001 and HR_females = 7.542, 95% CI: 1.874–30.358, p < 0.001). Multivariable analysis identified NTAR as the strongest independent predictor for in-hospital mortality among males. Conclusions: These findings suggest that NTAR effectively integrates cardiac and systemic dysfunction to improve mortality risk stratification in CHF, particularly in male patients. Its ease of calculation from routinely available biomarkers supports its clinical applicability. Full article

Obesity is an epidemic that currently impacts many nations. The persistence of this disease is shaped by both genetic and epigenetic factors that extend beyond calorie balance. Research in the past year has revealed that epigenetic and cellular memory within adipose tissue can predispose individuals to weight regain after initial fat loss, as shown by studies indicating persistent transcriptional and chromatin changes even after fat mass reduction. Independent studies also demonstrate long-lasting metabolic shifts, such as those triggered by glucose-dependent insulinotropic polypeptide receptor (GIPR)-induced thermogenesis and sarcolipin (SLN) stabilization that also support a form of “metabolic memory” that is associated with sustained weight loss. At the neural level, rare variants in synaptic genes like BSN (Bassoon presynaptic cytomatrix protein), a presynaptic scaffold protein, and APBA1 (amyloid beta precursor protein binding family A member 1), a neuronal adaptor involved in vesicular trafficking, disrupt communication in feeding circuits, elevating obesity risk and illustrating how synaptic integrity influences food intake regulation. Similarly, the spatial compartmentalization of metabolic signaling within neuronal cilia is emerging as crucial, with cilia-localized receptors G protein-coupled receptor 75 (GPR75) and G protein-coupled receptor 45 (GPR45) exerting opposing effects on energy balance and satiety. Meanwhile, genome-wide association studies (GWAS) have advanced through larger, more diverse cohorts and better integration of environmental and biological data. These studies have identified novel obesity-related loci and demonstrated the value of polygenic risk scores (PRS) in predicting treatment responses. For example, genetic variants in GLP-1R (glucagon-like peptide-1 receptor) and GIPR (glucose-dependent insulinotropic polypeptide receptor) may modulate the effectiveness of incretin-based therapies, while PRS for satiation can help match individuals to the most appropriate anti-obesity medications. This review focuses on studies in the last two years that highlight how advances in obesity genetics are driving a shift toward more personalized and mechanism-based treatment strategies. Full article

Voltage-gated Na⁺ channels (Nav) are the molecular determinants of action potential initiation and propagation. Among the nine voltage-gated Na⁺ channel isoforms (Nav1.1–Nav1.9), Nav1.2 and Nav1.6 are of particular interest because of their developmental expression profile throughout the central nervous system (CNS) and their association with channelopathies. Although the α-subunit coded by each of the nine isoforms can sufficiently confer transient Na⁺ currents (I_Na), in vivo these channels are modulated by auxiliary proteins like intracellular fibroblast growth factor (iFGFs) through protein–protein interaction (PPI), and probes developed from iFGF/Nav PPI complexes have been shown to precisely modulate Nav channels. Previous studies identified ZL0177, a peptidomimetic derived from a short peptide sequence at the FGF14/Nav1.6 PPI interface, as a functional modulator of Nav1.6-mediated I_Na⁺. However, the isoform specificity, binding sites, and putative physiological impact of ZL0177 on neuronal excitability remain unexplored. Here, we used automated planar patch-clamp electrophysiology to assess ZL0177’s functional activity in cells stably expressing Nav1.2 or Nav1.6. While ZL0177 was found to suppress I_Na in both Nav1.2- and Nav1.6-expressing cells, ZL0177 elicited functionally divergent effects on channel kinetics that were isoform-specific and supported by differential docking of the compound to AlphaFold structures of the two channel isoforms. Computational modeling predicts that ZL0177 modulates Nav1.2 and Nav1.6 in an isoform-specific manner, eliciting phenotypically divergent effects on action potential discharge. Taken together, these results highlight the potential of PPI derivatives for isoform-specific regulation of Nav channels and the development of therapeutics for channelopathies. Full article

Background: Diagnosing and predicting outcomes in elderly patients with heart failure (HF) is challenging due to atypical symptoms and the limited value of natriuretic peptides, highlighting the need to search for new risk stratification biomarkers in this population. Aim: We aimed to analyze factors associated with the composite endpoint (all-cause mortality or decompensated HF-related hospitalization) within six months of follow-up in elderly patients with left ventricular systolic dysfunction and decompensated HF, with particular emphasis on copeptin concentration. Methods: This is a retrospective observational study based on prospectively collected data of 279 consecutive elderly patients hospitalized between 2018 and 2023 due to decompensated HF. Inclusion criteria were age > 65 years, history of HF diagnosed at least two years before the index hospitalization, and left ventricular ejection fraction < 40% on admission echocardiography. Serum copeptin levels were measured using an Enzyme-Linked Immunosorbent Assay (ELISA) (Human Copeptin ELISA kit, Sunred Biological Technology Co, Shanghai, China). The primary endpoint was all-cause mortality or decompensated HF-related hospitalization during the six-month follow-up. Results: The median age of the study population was 77 years (IQR: 69–79), and 221 (79.2%) were male. The composite endpoint occurred in 110 patients (38.1%). Multivariable analysis showed that serum concentrations of copeptin [hazard ratio (HR) 1.053 (1.042–1.064), p < 0.0001], bilirubin [HR 1.085 (1.057–1.114), p < 0.0001], uric acid [HR 1.005 (1.003–1.006), p < 0.0001], high-sensitivity C-reactive protein (hs-CRP) [HR 1.208 (1.088–1.342), p < 0.0001], and sodium [HR 1.111 (1.025–1.203), p = 0.01], as well as ischemic etiology of HF [HR 3.969 (2.396–6.575), p < 0.0001], were independently associated with worse outcomes. Conclusions: Our study demonstrated that higher concentrations of copeptin, bilirubin, hs-CRP, and uric acid, as well as lower sodium levels and ischemic etiology of HF, were independently associated with all-cause mortality or HF-related hospitalization during a six-month follow-up in elderly patients with decompensated HF. Full article

Background/Objectives: Human milk provides essential nutrients and immune factors with beneficial impact on term, but especially preterm infants’ development. Therefore, this study focuses on the quantification of differences in the peptidome composition of breast milk from mothers of preterm and term infants, keeping in mind that this could reflect different biological needs of these infants or indicate nutritional gaps for healthy development. Methods: In a prospective observational study, breast milk samples were collected from 10 mothers of preterm infants (29–36 weeks gestational age,) and 13 mothers of term infants (37–41 weeks) at day 4 to 6 postnatally. A non-targeted tandem mass spectrometry approach was employed to analyze the milk peptidome. Results: In total, 4570 peptides were quantified. Adjusting the results for maternal age, weight, and height revealed a significant difference for 130 peptides derived from 19 different proteins between preterm and term milk. Proteins comprised high abundant proteins (e.g., α_S1-casein, κ- casein, or ß-casein), but also proteins that are less prominent in milk but of high functional importance (e.g., Hypoxia-inducible factor 1-alpha, Olfactory receptor 4M1). The differentially abundant peptides included peptides derived from ß-casein, which have already been described as being involved in antimicrobial functions as well as proliferation stimulating. For another 32 peptides, bioactivity was predicted. Conclusions: The current study provides a comprehensive overview on the differences in the milk peptidome at different gestational ages independent from common maternal phenotypes and improved the database for future peptide functionality studies. Full article