An in silico scheme for optimizing the enzymatic acquisition of natural biologically active peptides based on machine learning and virtual digestion.

BACKGROUND: As a potential natural active substance, natural biologically active peptides (NBAPs) are recently attracting increasing attention. The traditional proteolysis methods of obtaining effective NBAPs are considerably vexing, especially since multiple proteases can be used, which blocks the exploration of available NBAPs. Although the development of virtual digesting brings some degree of convenience, the activity of the obtained peptides remains unclear, which would still not allow efficient access to the NBAPs. It is necessary to develop an efficient and accurate strategy for acquiring NBAPs. RESULTS: A new in silico scheme named SSA-LSTM-VD, which combines a sparrow search algorithm-long short-term memory (SSA-LSTM) deep learning and virtually digested, was presented to optimize the proteolysis acquisition of NBAPs. Therein, SSA-LSTM reached the highest Efficiency value reached 98.00 % compared to traditional machine learning algorithms, and basic LSTM algorithm. SSA-LSTM was trained to predict the activity of peptides in the proteins virtually digested results, obtain the percentage of target active peptide, and select the appropriate protease for the actual experiment. As an application, SSA-LSTM was employed to predict the percentage of neuroprotective peptides in the virtual digested result of walnut protein, and trypsin was ultimately found to possess the highest value (85.29 %). The walnut protein was digested by trypsin (WPTrH) and the peptide sequence obtained was analyzed closely matches the theoretical neuroprotective peptide. More importantly, the neuroprotective effects of WPTrH had been demonstrated in nerve damage mouse models. SIGNIFICANCE: The proposed SSA-LSTM-VD in this paper makes the acquisition of NBAPs efficient and accurate. The approach combines deep learning and virtually digested skillfully. Utilizing the SSA-LSTM-VD based strategy holds promise for discovering and developing peptides with neuroprotective properties or other desired biological activities.

Effects of an Akt-activating peptide obtained from walnut protein degradation on the prevention of memory impairment in mice.

Akt acts as a central protein influencing multiple pathologies in neurodegenerative diseases including AD and PD, and using Akt activators is a promising management strategy. The current study characterized the effects of an Akt-activating peptide (Glu-Pro-Glu-Val-Leu-Pro, EPEVLR) obtained from walnut protein degradation on D-gal-induced memory impairment in mice. EPEVLR was obtained by hydrolysis of walnut proteins, identification of peptide sequences, and screening for molecular docking sequentially. The MWM test in mice indicated that the oral administration of EPEVLR (80, 200 and 400 mg per kg per day) significantly (p < 0.05) reversed D-gal-induced memory impairment. WB tests of the mouse hippocampus confirmed that EPEVLR could activate Akt by promoting its phosphorylation. In addition, further characterization (including TEM, ELISA, and immunohistochemistry) related to Akt phosphorylation showed lower Aß and p-tau levels, as well as more autophagosomes than those in the model group. Moreover, the EPEVLR treatment significantly increased Lactobacillus abundance and reduced Helicobacter abundance in the gut microbiome and caused up-regulation of SCFAs and down-regulation of LPS of serum metabolites. Therefore, EPEVLR ingestion reversed cognitive impairment symptoms, possibly related to the activation of Akt and regulation of the intestinal flora pathway. Consumption of an EPEVLR-containing diet is beneficial for treating cognitive dysfunction.

Multi-dimensional deep learning drives efficient discovery of novel neuroprotective peptides from walnut protein isolates.

Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are multi-factor induced neurological disorders that require management from multiple pathologies. The peptides from natural proteins with diverse physiological activity can be candidates as multifunctional neuroprotective agents. However, traditional methods for screening neuroprotective peptides are not only time-consuming and laborious but also poorly accurate, which makes it difficult to effectively obtain the needed peptides. In this case, a multi-dimensional deep learning model called MiCNN-LSTM was proposed to screen for multifunctional neuroprotective peptides. Compared to other multi-dimensional algorithms, MiCNN-LSTM reached a higher accuracy value of 0.850. The MiCNN-LSTM was used to acquire candidate peptides from walnut protein hydrolysis. Following molecular docking, behavioral and biochemical index experimental validation eventually found 4 hexapeptides (EYVTLK, VFPTER, EPEVLR and ELEWER) demonstrating excellent multifunctional neuroprotective properties. Therein, EPEVLR performed the best and can be investigated in depth as a multifunctional neuroprotective agent. This strategy will greatly improve the efficiency of screening multifunctional bioactive peptides, and it will be beneficial for the development of food functional peptides.

Amelioration of walnut-derived novel peptides against D-galactose-induced cognitive impairment by modulating the gut microbiota composition.

In this work, RLWPF (Arg-Leu-Trp-Pro-Phe) and VLRLF (Val-Leu-Arg-Leu-Phe) were investigated for the effects against D-galactose (D-gal) induced cognitive impairment by modulating the gut microbiota composition. The effects on serum metabolite production were further investigated. The two novel peptides derived from walnut protein alkaline protease hydrolysates were predicted by docking to acetylcholinesterase (AChE) with the highest binding affinities, -10.3 and -9.9 kcal mol-1, considered as the potential neuroprotective peptides. In behavioral experiments, RLWPF and VLRLF treatment significantly restored spatial learning and memory impairment induced by D-gal. The results showed that RLWPF and VLRLF could alleviate cholinergic dysfunction, oxidative stress, and inflammation to varying degrees caused by D-gal-induced aging. Furthermore, 16S rRNA analysis revealed that RLWPF and VLRLF treatment improved cognitive impairment by regulating the composition of the gut microbiota and the abundance of harmful bacteria, including the ratio of Firmicutes to Bacteroidetes, Helicobacter, Allobaculum, Alistipes, Mucispirillum, and Odoribacter. In addition to the same regulation, RLWPF and VLRLF had their marker and regulatory flora. Studies based on the gut microbiota would allow a better understanding of the neuroprotective effects of walnut-derived peptides, supporting that walnut-derived peptides could be potential functional ingredients in foods and nutraceuticals or drug candidates in the treatment of cognitive dysfunction.

Detection of walnut oil adulterated with high-linoleic acid vegetable oils using triacylglycerol pseudotargeted method based on SFC-QTOF-MS.

Authentication of walnut oil (WO) is challenging due to the adulteration of high-linoleic acid vegetable oils (HLOs) with similar fatty acid composition. To allow the discrimination of WO adulteration, a rapid, sensitive and stable scanning method based on supercritical fluid chromatography quadrupole time-of-flight mass spectrometry (SFC-QTOF-MS) was established to profile 59 potential triacylglycerol (TAGs) in HLOs samples within 10 min. Limit of quantitation of the proposed method is 0.002 µg mL-1 and the relative standard deviations range from 0.7% to 12.0%. TAGs profiles of WO samples from various varieties, geography origins, ripeness, and processing methods were used to construct orthogonal partial least squares-discriminant analysis (OPLS-DA) and OPLS models that were highly accurate in both qualitative and quantitative prediction at adulteration levels as low as 5% (w/w). This study advances the TAGs analysis to characterize vegetable oils and holds promise as an efficient method for oil authentication.

Separation, identification, and design of α-glucosidase inhibitory peptides based on the molecular mechanism from Paeonia ostii 'Feng Dan' seed protein.

Peptides are considered promising sources of nutraceuticals. In this study, a mixture of peptides was prepared from Paeonia ostii 'Feng Dan' seed meal protein by continuous enzymolysis. Successive separation and purification procedures, including ultrafiltration and reversed-phase high-performance liquid chromatography (RP-HPLC), were performed, and six novel peptides were identified by liquid chromatography-electrospray ionization source-mass spectrometry/mass spectrometry (LC-ESI-MS/MS). In an in vitro antidiabetic activity test, Tyr-Phe-Phe-Met exhibited stronger α-glucosidase inhibitory activity (48.17 ± 3.34% at 1 mg/mL) than the other peptides. Docking studies of this peptide into the active site of α-glucosidase showed that the formation of hydrogen bonds could be critical for the enzymatic trapping of inhibitory peptides. Furthermore, two novel peptides, Phe-Phe-Phe-Met (IC50  = 245.46 ± 44.01 µM) and Tyr-Tyr-Phe-Met (IC50  = 306.71 ± 48.17 µM), with improved α-glucosidase inhibitory activity, were designed based on molecular docking. Therefore, the seed meal of Paeonia ostii could be considered a functional food ingredient for the management of hyperglycemia, and three novel peptides were identified as α-glucosidase inhibitors.

Strain-tunable magnetic and electronic properties of a CuCl3 monolayer.

Recently, theoretical search has found that a two-dimensional CuCl3 monolayer is a ferromagnetic semiconductor. Here, we apply density functional theory to study its geometrical structure, magnetic and electronic properties under the influence of a biaxial strain ε. It is found that the CuCl3 monolayer exhibits ferromagnetic ordering at the ground state with ε = 0 and its Curie temperature increases monotonously with respect to the biaxial strain, which can be increased to about 100 K at 10% tensile strain. When a compressive strain of about 6.8% is applied, a transition from the ferromagnetic to the antiferromagnetic state occurs. In addition to the transition of the magnetic ground state, the electronic band gaps of spin-up and spin-down electrons undergo direct-indirect and indirect-direct-indirect transitions at the tensile strains, respectively. The tunable magnetic and electronic properties investigated in this work are helpful in understanding the magnetism in the CuCl3 monolayer, which is useful for the design of spintronic devices based on ferromagnetic semiconductors.

Nanoscaled and Atomic Ruthenium Electrocatalysts Confined Inside Super-Hydrophilic Carbon Nanofibers for Efficient Hydrogen Evolution Reaction.

A series of Ru-based catalysts have been developed for the hydrogen evolution reaction (HER) by the facile impregnation of copious and eco-friendly bacterial cellulose (BC) with Ru(bpy)3 Cl2 (bpy = 2,2'-bipyridine) followed by pyrolysis. After the oxidation and molecular recomposition processes that occur within the BC precursors during pyrolysis, sub-2 nm Ru nanoparticles (NPs) and atomic Ru species confined within surface-oxidized N-doped carbon nanofibers (CNFs) can be observed in the derived catalysts. The surface oxidation of CNFs leads the derived catalysts with super hydrophilicity and water-absorbing capacity, and also provides dimensional confinement for the nanoscaled and atomic Ru species. With these added structural advantages and the component synergy, the derived catalysts show superior HER activities, for which the overpotentials are as low as 19.6 mV (1 m KOH) and 55.0 mV (0.5 m H2 SO4 ) for the most active case at the current density of 10 mA cm-2 . Moreover, superior HER activity can be also achieved for the catalysts derived with a wide range of Ru loadings. Finally, the influence of Ru NP size on HER activity is investigated by density functional theory simulations. This method provides a reliable protocol for preparing highly active HER catalysts for scale-up applications.

Selective extraction of perfluorooctane sulfonate in real samples by superparamagnetic nanospheres coated with a polydopamine-based molecularly imprinted polymer.

Superparamagnetic core-shell structured molecularly imprinted polydopamine nanospheres were constructed via self-polymerization of dopamine to attach the template onto the surface of magnetic Fe3 O4 substrate in tris-HCl solution. Then they were used for the specific recognition and extraction of perfluorooctane sulfonate from environmental water and human serum samples. The structural features and morphological characterization of the magnetic imprinting nanospheres were assessed, indicating that the magnetic polydopamine imprinted composite was successfully prepared and featured excellent magnetic separation characteristics. Adsorption experiments revealed that the magnetic adsorbents exhibited rapid adsorption kinetics and highly selective recognition properties toward perfluorooctane sulfonate. The stability and regeneration experiments indicated the materials had repeatable activity retention after repeated reuse. As a magnetic solid-phase extraction adsorbent, it was successfully applied for the extraction and quantification of perfluorooctane sulfonate in environmental water and human serum samples combined with liquid chromatography tandem mass spectrometry, with recoveries of ∼70-101.5% obtained in real samples. These results demonstrate that the prepared magnetic imprinting nanospheres are effective for the selective separation of perfluorooctane sulfonate from real samples. The synthesis technique is an effective and facile method that is conducted in aqueous solution and at ambient temperature, which is low cost, environmentally benign, and easy for scaling-up.

Nitrogen-doped carbon dots as an effective fluorescence enhancing system for the determination of perfluorooctyl sulfonate.

Nitrogen-doped carbon dots (NCDs) were synthesized via hydrothermal treatment of vitamin B1 and triethylamine. The NCDs exhibit strong blue fluorescence (with a peak at 437 nm at an excitation wavelength of 370 nm), good water solubility and excellent fluorescence stability in the pH 3~12 range, at ionic strengths between 0.01 and 1 M, and under UV illumination for 6 h, as well as incubation temperature of 15~60 °C. The nanoparticles respond selectively and sensitively to trace concentrations of perfluorooctane sulfonate (PFOS) through electrostatic interactions between PFOS and NCDs. This is accompanied by the aggregation of NCDs to yield enhanced fluorescence. The nanoprobe has high selectivity for PFOS even in presence of other common ions such as metal ions, anions, and structural analogues such as surfactants. Under the optimal conditions, the response is linear in the 0.3 to 160 nM PFOS concentration range with a detection limit of 0.3 nM. Satisfactory results were achieved for determination of PFOS in spiked real water samples. Graphical abstract Schematic presentation of the synthetic route to nitrogen-doped carbon dots (NCDs) starting from vitamin B1 and triethylamine, and its application for selective and sensitive fluorometric determination of perfluorooctane sulfonate (PFOS).