The ongoing COVID-19 pandemic has caused dramatic loss of human life. There is an urgent need for safe and efficient anti-coronavirus infection drugs. Anti-coronavirus peptides (ACovPs) can inhibit coronavirus infection. With high-efficiency, low-toxicity, and broad-spectrum inhibitory effects on coronaviruses, they are promising candidates to be developed into a new type of anti-coronavirus drug. Experiment is the traditional way of ACovPs' identification, which is less efficient and more expensive. With the accumulation of experimental data on ACovPs, computational prediction provides a cheaper and faster way to find anti-coronavirus peptides' candidates. In this study, we ensemble several state-of-the-art machine learning methodologies to build nine classification models for the prediction of ACovPs. These models were pre-trained using deep neural networks, and the performance of our ensemble model, ACP-Dnnel, was evaluated across three datasets and independent dataset. We followed Chou's 5-step rules. (1) we constructed the benchmark datasets data1, data2, and data3 for training and testing, and introduced the independent validation dataset ACVP-M; (2) we analyzed the peptides sequence composition feature of the benchmark dataset; (3) we constructed the ACP-Dnnel model with deep convolutional neural network (DCNN) merged the bi-directional long short-term memory (BiLSTM) as the base model for pre-training to extract the features embedded in the benchmark dataset, and then, nine classification algorithms were introduced to ensemble together for classification prediction and voting together; (4) tenfold cross-validation was introduced during the training process, and the final model performance was evaluated; (5) finally, we constructed a user-friendly web server accessible to the public at http://150.158.148.228:5000/ . The highest accuracy (ACC) of ACP-Dnnel reaches 97%, and the Matthew's correlation coefficient (MCC) value exceeds 0.9. On three different datasets, its average accuracy is 96.0%. After the latest independent dataset validation, ACP-Dnnel improved at MCC, SP, and ACC values 6.2%, 7.5% and 6.3% greater, respectively. It is suggested that ACP-Dnnel can be helpful for the laboratory identification of ACovPs, speeding up the anti-coronavirus peptide drug discovery and development. We constructed the web server of anti-coronavirus peptides' prediction and it is available at http://150.158.148.228:5000/ .

Adenosine deaminase (ADA) is a Zn2+-containing enzyme that catalyzes the irreversible deamination of adenosine to inosine or deoxyadenosine to deoxyinosine. In addition to this enzymatic function, ADA mediates cell-to-cell interactions involved in lymphocyte co-stimulation or endothelial activation. ADA is implicated in cardiovascular pathologies such as atherosclerosis and certain types of cancers, including lymphoma and leukemia. To date, only two drugs (pentostatin and cladribine) have been approved for the treatment of hairy cell leukemia. In search of natural ADA inhibitors, we demonstrated the binding of selected phenolic compounds to the active site of ADA using molecular docking and molecular dynamics simulation. Our results show that phenolic compounds (chlorogenic acid, quercetin, and hyperoside) stabilized the ADA complex by forming persistent interactions with the catalytically essential Zn2+ ion. Furthermore, MM-GBSA ligand binding affinity calculations revealed that hyperoside had a comparable binding energy score (ΔG = - 46.56 ± 8.26 kcal/mol) to that of the cocrystal ligand in the ADA crystal structure (PDB ID: 1O5R) (ΔG = - 51.97 ± 4.70 kcal/mol). Similarly, chlorogenic acid exhibited a binding energy score (ΔG = - 18.76 ± 4.60 kcal/mol) comparable to those of the two approved ADA inhibitor drugs pentostatin (ΔG = - 14.54 ± 2.25 kcal/mol) and cladribine (ΔG = - 25.52 ± 4.10 kcal/mol) while quercetin was found to have modest binding affinity (ΔG = - 8.85 ± 7.32 kcal/mol). This study provides insights into the possible inhibitory potential of these phenolic compounds against ADA.

In this study, we investigated the status of amino acids, their post-translational modifications (PTM), major nitric oxide (NO) metabolites and of malondialdehyde (MDA) as a biomarker of oxidative stress in serum and urine samples of long COVID (LoCo, n = 124) and ex COVID (ExCo, n = 24) human subjects collected in 2022. Amino acids and metabolites were measured by gas chromatography-mass spectrometry (GC-MS) methods using stable-isotope labelled analogs as internal standards. There were no differences with respect to circulating and excretory arginine and asymmetric dimethylarginine (ADMA). LoCo participants excreted higher amounts of guanidino acetate than ExCo participants (17.8 ± 10.4 µM/mM vs. 12.6 ± 8.86 µM/mM, P = 0.005). By contrast, LoCo participants excreted lower amounts of the advanced glycation end-product (AGE) NG-carboxyethylarginine (CEA) than ExCo participants did (0.675 ± 0.781 µM/mM vs. 1.16 ± 2.04 µM/mM, P = 0.0326). The serum concentrations of MDA did not differ between the groups, indicating no elevated oxidative stress in LoCo or ExCo. The serum concentration of nitrite was lower in LoCo compared to ExCo (1.96 ± 0.92 µM vs. 2.56 ± 1.08 µM; AUC, 0.718), suggesting altered NO synthesis in the endothelium. The serum concentration of nitrite correlated inversely with the symptom anxiety (r = - 0.293, P = 0.0003). The creatinine-corrected urinary excretion of Lys and its metabolite L-5-hydroxy-Lys correlated positively with COVID toes (r = 0.306, P = 0.00027) and sore throat (r = 0.302, P = 0.0003). Our results suggest that amino acid metabolism, PTM and oxidative stress are not severely affected in long COVID. LoCo participants may have a lower circulating NO reservoir than ExCo.

About 30% of malignant tumors include KRAS mutations, which are frequently required for the development and maintenance of malignancies. KRAS is now a top-priority cancer target as a result. After years of research, it is now understood that the oncogenic KRAS-G12C can be targeted. However, many other forms, such as the G13D mutant, are yet to be addressed. Here, we used a receptor-based pharmacophore modeling technique to generate potential inhibitors of the KRAS-G13D oncogenic mutant. Using a comprehensive virtual screening workflow model, top hits were selected, out of which CSC01 was identified as a promising inhibitor of the oncogenic KRAS mutant (G13D). The stability of CSC01 upon binding the switch II pocket was evaluated through an exhaustive molecular dynamics simulation study. The several post-simulation analyses conducted suggest that CSC01 formed a stable complex with KRAS-G13D. CSC01, through a dynamic protein-ligand interaction profiling analysis, was also shown to maintain strong interactions with the mutated aspartic acid residue throughout the simulation. Although binding free energy analysis through the umbrella sampling approach suggested that the affinity of CSC01 with the switch II pocket of KRAS-G13D is moderate, our DFT analysis showed that the stable interaction of the compound might be facilitated by the existence of favorable molecular electrostatic potentials. Furthermore, based on ADMET predictions, CSC01 demonstrated a satisfactory drug likeness and toxicity profile, making it an exemplary candidate for consideration as a potential KRAS-G13D inhibitor.

Amino acids not only play a vital role in the synthesis of biological molecules such as proteins in cancer malignant cells, they are also essential metabolites for immune cell activation and antitumor effects in the tumor microenvironment. The abnormal changes in amino acid metabolism are closely related to the occurrence and development of tumors and immunity. Intestinal microorganisms play an essential role in amino acid metabolism, and tryptophan and its intestinal microbial metabolites are typical representatives. However, it is known that the cyclic amino acid profile is affected by specific cancer types, so relevant studies mainly focus on one type of cancer and rarely study different cancer forms at the same time. The objective of this study was to examine the PFAA profile of five cancer patients and the characteristics of tryptophan intestinal microbial metabolites to determine whether there are general amino acid changes across tumors. Plasma samples were collected from esophageal (n = 53), lung (n = 73), colorectal (n = 94), gastric (n = 55), breast cancer (n = 25), and healthy control (HC) (n = 139) subjects. PFAA profile and tryptophan metabolites were measured, and their perioperative changes were examined using high-performance liquid chromatography. Univariate analysis revealed significant differences between cancer patients and HC. Furthermore, multivariate analysis discriminated cancer patients from HC. Regression diagnosis models were established for each cancer group using differential amino acids from univariate analysis. Receiver-operating characteristic analysis was applied to evaluate these diagnosis models. Finally, GABA, arginine, tryptophan, taurine, glutamic acid, and melatonin showed common alterations across all types of cancer patients. Metabolic pathway analysis shows that the most significant enrichment pathways were tryptophan, arginine, and proline metabolism. This study provides evidence that common alterations of the metabolites mentioned above suggest their role in the pathogenesis of each cancer patient. It was suggested that multivariate models based on PFAA profiles and tryptophan metabolites might be applicable in the screening of cancer patients.

Myasthenia gravis (MG) is an autoimmune disease characterized by weakness and rapid fatigue. Diagnostic methods used for myasthenia gravis are not conclusive and satisfactory, therefore it is necessary to develop reliable tools to help diagnose myasthenia gravis as early as possible. The aim of the study was to use HPLC-MS in conjunction with multivariate statistical analyses to investigate changes in the amino acid metabolic profiles between myasthenia gravis patients compared and controls. In addition, the effect of treatment regimens and myasthenia gravis type, on the observed changes in amino acid metabolic profiles were assessed. Serum levels of 29 amino acids were determined in 2 groups of individuals-28 patients with myasthenia gravis and 53 control subjects (CS). The results of our study indicate that serum levels of several amino acids in patients with myasthenia gravis changed significantly compared to the control group. Statistical analysis revealed differences between amino acids concentration in patients with different therapeutic scheme. In conclusion, amino acids may be involved in mechanisms underlying myasthenia gravis pathogenesis as well as may be potential biomarkers in MG patients diagnosis. However, considering the multifactorial, heterogenous and complex nature of this disease, validation on a larger study sample in further research is required before application into diagnostic practice.

Polystyrene-based support Bio-Beads® SM-2 was employed for desalting peptide-p-nitroanilides from Oxone®. Neither tosyl, 9-fluorenyl(methoxycarbonyl), p-nitroanilide groups nor indolyl or p-hydroxyphenyl side-chains of Trp and Tyr ensured an efficient adsorption of peptide-p-nitroanilides onto Bio-Beads® SM-2. Only unsubstituted phenyl-containing protection groups (carbobenzoxy or benzoyl) and Phe residues provided the adsorption of peptides on Bio-Beads® SM-2 and their efficient desalting. This support is well suitable for multiple parallel phenyl group-containing peptide derivative separations and high-throughput screenings.

Diabetic nephropathy (DN) can promote the occurrence of end-stage renal disease (ESRD). The injury of renal tubular epithelial cells is a significant reason for the occurrence of ESRD. A recent research demonstrated that ferroptosis was associated with renal tubular injury in DN. Ferroptosis is a kind of cell death brought on by the buildup of iron ions and lipid peroxidation brought on by ROS. Because carnosine (CAR) is a scavenger of iron ions and reactive oxygen species, we investigated whether CAR can improve DN by regulating ferroptosis. The results show that both CAR and Fer-1 significantly reduced kidney damage and inhibited ferroptosis in STZ mice. In addition, ferroptosis caused by HG or erastin (an inducer of ferroptosis) in human kidney tubular epithelial cell (HK2) was also rescued by CAR treatment. It was discovered that the protective effect of CAR against HG-induced ferroptosis was abolished when NRF2 was specifically knocked down in HK2 cells.

Candida albicans is considered one of the most important opportunistic fungi due to the large arsenal of virulence factors that help throughout the progress of the infection. In this sense, antimicrobial peptides (AMPs) appear as an alternative, with great antifungal action. Among these, aurein 1.2 has been widely explored, becoming the basis for the discovery of new AMPs, such as K-aurein (K-au). Thus, this study evaluated the anti-C. albicans potential of K-au against virulence factors, planktonic growth, and biofilm formation of clinical isolates. Firstly, K-au antifungal activity was determined by the microdilution method and time-kill curve. The inhibition of hydrolytic enzyme secretion (proteinase, phospholipase, and hemolysin) and germ tube formation was tested. Then, the antibiofilm potential of K-au was verified through biomass quantification and scanning electron microscopy (SEM). All tests were compared with the classical antifungal drug, amphotericin B (AmB). The outcomes showed fungicidal action of K-au at 62.50 µg mL-1 for all isolates, with a time of action around 150-180 min, determined by the time-kill curve. K-au-treated cells decreased by around 40% of the germinative tube compared to the control. Additionally, K-au inhibited the biofilm formation by more than 90% compared to AmB and the control group. SEM images show apparent cellular disaggregation without the formation of filamentous structures. Therefore, the findings suggest a promising anti-C. albicans effect of K-au due to its fungicidal activity against planktonic cells, or its ability to inhibit important virulence factors like germ tube and biofilm formation. Thus, this peptide could be explored as a useful compound against C. albicans-related infection.

In this study, we subjected 5,5-diethoxy-4-oxopent-2-enal (DOPE), a model amino acids cross-linking reagent, to reactions with N-acetylcysteine (Ac-Cys) and Nα-acetyllysine (Ac-Lys), and identified three pyrrole cross-links. The compounds were isolated and their structures were rigorously determined by spectrometric and spectroscopic methods, including 2D NMR experiments. The use of 2D NMR spectroscopy was crucial to determine the position of the substituents in the pyrrole rings. The products were identified as 2,4-, 2,3-, and 2,5-substituted pyrroles. The data obtained from their structural characterisation can help similar studies on amino acids modifications induced by analogous bifunctional carbonyl compounds. Our results show that the study of pathways in which model electrophiles modify amino acids may be helpful for similar studies dealing with identification of structural changes in cysteine- and lysine-containing proteins associated with oxidative stress.