Computer-Aided Screening for Potential Coronavirus 3-Chymotrypsin-like Protease (3CLpro) Inhibitory Peptides from Putative Hemp Seed Trypsinized Peptidome

Computational Screening for the Dipeptidyl Peptidase-IV Inhibitory Peptides from Putative Hemp Seed Hydrolyzed Peptidome as a Potential Antidiabetic Agent

Dipeptidyl peptidase-IV (DPPIV) inhibitory peptides are a class of antihyperglycemic drugs used in the treatment of type 2 diabetes mellitus, a metabolic disorder resulting from reduced levels of the incretin hormone GLP-1. Given that DPPIV degrades incretin, a key regulator of blood sugar levels, various antidiabetic medications that inhibit DPPIV, such as vildagliptin, sitagliptin, and linagliptin, are employed. However, the potential side effects of these drugs remain a matter of debate. Therefore, we aimed to investigate food-derived peptides from Cannabis sativa (hemp) seeds. Our developed bioinformatics pipeline was used to identify the putative hydrolyzed peptidome of three highly abundant proteins: albumin, edestin, and vicilin. These proteins were subjected to in silico digestion by different proteases (trypsin, chymotrypsin, and pepsin) and then screened for DPPIV inhibitory peptides using IDPPIV-SCM. To assess potential adverse effects, several prediction tools, namely, TOXINpred, AllerCatPro, and HemoPred, were employed to evaluate toxicity, allergenicity, and hemolytic effects, respectively. COPID was used to determine the amino acid composition. Molecular docking was performed using GalaxyPepDock and HPEPDOCK, 3D visualizations were conducted using the UCSF Chimera program, and MD simulations were carried out with AMBER20 MD software. Based on the predictive outcomes, FNVDTE from edestin and EAQPST from vicilin emerged as promising candidates for DPPIV inhibitors. We anticipate that our findings may pave the way for the development of alternative DPPIV inhibitors.

Conformation-Activity Mechanism of Alcalase Hydrolysis for Reducing In Vitro Allergenicity of Instant Soy Milk Powder

Effective reduction of the allergenicity of instant soy milk powder (ISMP) is practically valuable for expanding its applications. This study optimized the enzymolysis technology of ISMP using single-factor experiments and response surface methodology, combined serological analysis, cellular immunological models, bioinformatics tools, and multiple spectroscopy techniques to investigate the effects of alcalase hydrolysis on allergenicity, spatial conformation, and linear epitopes of ISMP. Under the optimal process, special IgE and IgG1 binding abilities and allergenic activity to induce cell degranulation of alcalase-hydrolyzed ISMP were reduced by (64.72 ± 1.76)%, (56.79 ± 3.72)%, and (73.3 ± 1.19)%, respectively (P < 0.05). Moreover, the spatial conformation of instant soy milk powder hydrolysates (ISMPH) changed, including decreased surface hydrophobicity, a weaker peak of amide II band, lower contents of α-helix and β-sheet, and an enhanced content of random coil. Furthermore, the linear epitopes of major soy allergens, 9 from glycinin and 13 from β-conglycinin, could be directionally disrupted by alcalase hydrolysis. Overall, the structure-activity mechanism of alcalase hydrolysis to reduce ISMP allergenicity in vitro was preliminarily clarified. It provided a new research direction for the breakthrough in the desensitization of ISMP and a theoretical basis for revealing the potential mechanism of alcalase enzymolysis to reduce the allergenicity of ISMP.

Antiviral peptides inhibiting the main protease of SARS-CoV-2 investigated by computational screening and in vitro protease assay

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays an important role in viral replication and transcription and received great attention as a vital target for drug/peptide development. Therapeutic agents such as small-molecule drugs or peptides that interact with the Cys-His present in the catalytic site of Mpro are an efficient way to inhibit the protease. Although several emergency-approved vaccines showed good efficacy and drastically dropped the infection rate, evolving variants are still infecting and killing millions of people globally. While a small-molecule drug (Paxlovid) received emergency approval, small-molecule drugs have low target specificity and higher toxicity. Besides small-molecule drugs, peptide therapeutics are thus gaining increasing popularity as they are easy to synthesize and highly selective and have limited side effects. In this study, we investigated the therapeutic value of 67 peptides targeting Mpro using molecular docking. Subsequently, molecular dynamics (MD) simulations were implemented on eight protein-peptide complexes to obtain molecular-level information on the interaction between these peptides and the Mpro active site, which revealed that temporin L, indolicidin, and lymphocytic choriomeningitis virus (LCMV) GP1 are the best candidates in terms of stability, interaction, and structural compactness. These peptides were synthesized using the solid-phase peptide synthesis protocol, purified by reversed-phase high-performance liquid chromatography (RP-HPLC), and authenticated by mass spectrometry (MS). The in vitro fluorometric Mpro activity assay was used to validate the computational results, where temporin L and indolicidin were observed to be very active against SARS-CoV-2 Mpro with IC50 values of 38.80 and 87.23 μM, respectively. A liquid chromatography-MS (LC-MS) assay was developed, and the IC50 value of temporin L was measured at 23.8 μM. The solution-state nuclear magnetic resonance (NMR) structure of temporin L was determined in the absence of sodium dodecyl sulfate (SDS) micelles and was compared to previous temporin structures. This combined investigation provides critical insights and assists us to further develop peptide inhibitors of SARS-CoV-2 Mpro through structural guided investigation.

Marine Brown Algae-Derived Compounds as Potential Inhibitors of Japanese Encephalitis Virus RNA-Dependent RNA Polymerase

The Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus that primarily affects people in Asia and seriously threatens public health. Considering the rising occurrence rates and lack of targeted antiviral treatments, it is essential to comprehend and tackle obstacles related to JEV in order to lessen its influence on world health. This investigation explores compounds derived from marine brown algae (Phaeophyceae) as potential inhibitors of JEV RNA-dependent RNA polymerase (RdRp), a critical enzyme in the virus's replication cycle. Employing the computational virtual screen approach, four compounds, i.e., CMNPD16749, CMNPD2606, CMNPD27817, and CMNPD23662, with favorable binding energies ranging from -15.7 Kcal/mol to -13.9 kcal/mol were identified. Subsequently, through molecular docking analysis, the interactions responsible for the binding stability between the target protein and hit molecules compared to the reference molecule Galidesvir were studied. Further, through extensive molecular dynamic (MD) simulation studies at 200 ns, it was confirmed that each docked complex showed acceptable dynamic stability compared to the reference molecule. These findings were further validated using MM/PBSA free binding energy calculations, PCA analysis and free energy landscape construction. These computational findings suggested that the brown algae-derived compounds may act as an antiviral drug against JEV infection and lay a crucial foundation for future experimental studies against JEV.

TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides

BACKGROUND

Tyrosinase is an enzyme involved in melanin production in the skin. Several hyperpigmentation disorders involve the overproduction of melanin and instability of tyrosinase activity resulting in darker, discolored patches on the skin. Therefore, discovering tyrosinase inhibitory peptides (TIPs) is of great significance for basic research and clinical treatments. However, the identification of TIPs using experimental methods is generally cost-ineffective and time-consuming.

RESULTS

Herein, a stacked ensemble learning approach, called TIPred, is proposed for the accurate and quick identification of TIPs by using sequence information. TIPred explored a comprehensive set of various baseline models derived from well-known machine learning (ML) algorithms and heterogeneous feature encoding schemes from multiple perspectives, such as chemical structure properties, physicochemical properties, and composition information. Subsequently, 130 baseline models were trained and optimized to create new probabilistic features. Finally, the feature selection approach was utilized to determine the optimal feature vector for developing TIPred. Both tenfold cross-validation and independent test methods were employed to assess the predictive capability of TIPred by using the stacking strategy. Experimental results showed that TIPred significantly outperformed the state-of-the-art method in terms of the independent test, with an accuracy of 0.923, MCC of 0.757 and an AUC of 0.977.

CONCLUSIONS

The proposed TIPred approach could be a valuable tool for rapidly discovering novel TIPs and effectively identifying potential TIP candidates for follow-up experimental validation. Moreover, an online webserver of TIPred is publicly available at http://pmlabstack.pythonanywhere.com/TIPred .

Computer-Aided Virtual Screening and In Vitro Validation of Biomimetic Tyrosinase Inhibitory Peptides from Abalone Peptidome

Hyperpigmentation is a medical and cosmetic problem caused by an excess accumulation of melanin or the overexpression of the enzyme tyrosinase, leading to several skin disorders, i.e., freckles, melasma, and skin cancer. Tyrosinase is a key enzyme in melanogenesis and thus a target for reducing melanin production. Although abalone is a good source of bioactive peptides that have been used for several properties including depigmentation, the available information on the anti-tyrosinase property of abalone peptides remains insufficient. This study investigated the anti-tyrosinase properties of Haliotis diversicolor tyrosinase inhibitory peptides (hdTIPs) based on mushroom tyrosinase, cellular tyrosinase, and melanin content assays. The binding conformation between peptides and tyrosinase was also examined by molecular docking and dynamics study. KNN1 showed a high potent inhibitory effect on mushroom tyrosinase with an IC₅₀ of 70.83 μM. Moreover, our selected hdTIPs could inhibit melanin production through the reductions in tyrosinase activity and reactive oxygen species (ROS) levels by enhancing the antioxidative enzymes. RF1 showed the highest activity on both cellular tyrosinase inhibition and ROS reduction. leading to the lower melanin content in B16F10 murine melanoma cells. Accordingly, it can be assumed that our selected peptides exhibited high potential in medical cosmetology applications.