Discovery and validation of peptide biomarkers for discrimination of Dendrobium species by label-free proteomics and chemometrics

The role of artificial intelligence in drug screening, drug design, and clinical trials

The role of computational tools in drug discovery and development is becoming increasingly important due to the rapid development of computing power and advancements in computational chemistry and biology, improving research efficiency and reducing the costs and potential risks of preclinical and clinical trials. Machine learning, especially deep learning, a subfield of artificial intelligence (AI), has demonstrated significant advantages in drug discovery and development, including high-throughput and virtual screening, ab initio design of drug molecules, and solving difficult organic syntheses. This review summarizes AI technologies used in drug discovery and development, including their roles in drug screening, design, and solving the challenges of clinical trials. Finally, it discusses the challenges of drug discovery and development based on AI technologies, as well as potential future directions.

Tolerance enhancement of Dendrobium officinale by salicylic acid family-related metabolic pathways under unfavorable temperature

BACKGROUND

Unfavorable temperatures significantly constrain the quality formation of Dendrobium officinale, severely limiting its food demand. Salicylic acid (SA) enhances the resistance of D. officinale to stress and possesses various analogs. The impact and mechanism of the SA family on improving the quality of D. officinale under adverse temperature conditions remains unclear.

RESULTS

Combined with molecular docking analysis, chlorophyll fluorescence and metabolic analysis after treatments with SA analogues or extreme temperatures are performed in this study. The results demonstrate that both heat and cold treatments impede several main parameters of chlorophyll fluorescence of D. officinale, including the ΦPSII parameter, a sensitive growth indicator. However, this inhibition is mitigated by SA or its chemically similar compounds. Comprehensive branch imaging of ΦPSII values revealed position-dependent improvement of tolerance. Molecular docking analysis using a crystal structure model of NPR4 protein reveals that the therapeutic effects of SA analogs are determined by their binding energy and the contact of certain residues. Metabolome analysis identifies 17 compounds are considered participating in the temperature-related SA signaling pathway. Moreover, several natural SA analogs such as 2-hydroxycinnamic acid, benzamide, 2-(formylamino) benzoic acid and 3-o-methylgallic acid, are further found to have high binding ability to NPR4 protein and probably enhance the tolerance of D. officinale against unfavorable temperatures through flavone and guanosine monophosphate degradation pathways.

CONCLUSIONS

These results reveal that the SA family with a high binding capability of NPR4 could improve the tolerance of D. officinale upon extreme temperature challenges. This study also highlights the collaborative role of SA-related natural compounds present in D. officinale in the mechanism of temperature resistance and offers a potential way to develop protective agents for the cultivation of D. officinale.

Engineering Interfacial Integrity with Hydrolytic-Resistant, Self-Reinforcing Dentin Adhesive

The leading cause of composite restoration failure is secondary caries, and although caries is a multifactorial problem, weak, damage-prone adhesives play a pivotal role in the high susceptibility of composite restorations to secondary caries. Our group has developed synthetic resins that capitalize on free-radical polymerization and sol-gel reactions to provide dental adhesives with enhanced properties. The resins contain γ-methacryloxypropyltrimethoxysilane (MPS) as the Si-based compound. This study investigated the properties of methacrylate-based resins containing methacryloxymethyltrimethoxysilane (MMeS) as a short-chain alternative. The degree of conversion (DC), polymerization kinetics, water sorption, mechanical properties, and leachates of MMeS- and MPS-resins with 55 and 30 wt% BisGMA-crosslinker were determined. The formulations were used as model adhesives, and the adhesive/dentin (a/d) interfaces were analyzed using chemometrics-assisted micro-Raman spectroscopy. The properties of the 55 wt% formulations were comparable. In the 30 wt% BisGMA formulations, the MMeS-resin exhibited faster polymerization, lower DC, reduced leachates, and increased storage and loss moduli, glass transition (Tg), crosslink density, and heterogeneity. The spectroscopic results indicated a comparable spatial distribution of resin, mineralized, and demineralized dentin across the a/d interfaces. The hydrolytically stable experimental short-chain-silane-monomer dental adhesive provides enhanced mechanical properties through autonomous strengthening and offers a promising strategy for the development of restorative dental materials with extended service life.

Rapid Measurement of Total Saponins, Mannitol, and Naringenin in Dendrobium officinale by Near-Infrared Spectroscopy and Chemometrics

Dendrobium officinale has drawn increasing attention as a dual-use plant with herbal medicine and food applications. The efficient quality evaluation of D. officinale is essential to ensuring its nutritional and pharmaceutical value. Given that traditional analytical methods are generally time-consuming, expensive, and laborious, this study developed a rapid and efficient approach to assess the quality of D. officinale from different geographical origins by near-infrared (NIR) spectroscopy and chemometrics. Total saponins, mannitol, and naringenin were utilized as quality indicators. Two wavelength selection methods, namely, uninformative variable elimination and competitive adaptive reweighted sampling (CARS), were utilized to enhance the prediction accuracy of the quantification model. Moreover, multiple spectral pretreatment methods were applied for model optimization. Results indicated that the partial least squares (PLS) model constructed based on the wavelengths selected by CARS exhibited superior performance in predicting the contents of the quality indicators. The coefficient of determination (RP2) and root mean square error (RMSEP) in the independent test sets were 0.8949 and 0.1250 g kg-1 for total saponins, 0.9664 and 0.2192 g kg-1 for mannitol, and 0.8570 and 0.003159 g kg-1 for naringenin, respectively. This study revealed that NIR spectroscopy and the CARS-PLS model could be used as a rapid and accurate technique to evaluate the quality of D. officinale.

Exploring peptides from toad venom for source identification by LC-MS/MS using MRM method

Toad venom is a traditional Chinese medicine (TCM) with various sources and wide-ranging preparations. Previous quality assessment studies primarily concentrated on small molecular compounds like toad dienolactones and indole alkaloids, studies on macromolecular peptides and proteins as quality assessment standards remained at the qualitative stage, lacking the development of practical and convenient quantitative methods. In this study, to explore the peptides from toad venom as a new method for identifying and evaluating its source, a complete scan of the water extract of peptides from toad venom was conducted using HPLC-Quadrupole Time-of-Flight Mass Spectrometer (Q-TOF) 5600, leading to the identification of peptides based on mass spectrometry data. Subsequently, HPLC- Quadrupole-Linear Ion Trap Mass Spectrometer (Q-Trap) 5500 employing Multiple Reaction Monitoring (MRM) mode was utilized to quantitatively analyze peptides in various sources of toad venom, followed by Partial Least Squares Discriminant Analysis (PLS-DA) to further analyze the data and evaluate the effectiveness. This study highlights the importance of exploring macromolecular substance in natural products research and provides a foundation for further studies on toad venom.

Determination of adulteration, geographical origins, and species of food by mass spectrometry

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics-based methods) are still in use; however, emerging approaches like mass spectrometry (MS)-based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS-based metabolomics, proteomics and other approaches.

Comprehensive evaluation of Dendrobium officinale from different geographical origins using near-infrared spectroscopy and chemometrics

Dendrobium officinale, often used as a kind of tea for daily drinks, has drawn increasing attention for its beneficial effects. Quality evaluation of D. officinale is of great significance to ensure its health care value and safeguard consumers' interest. Given that traditional analytical methods for assessing D. officinale quality are generally time-consuming and laborious, this study developed a comprehensive strategy, with the advantages of being rapid and efficient, enabling the quality evaluation of D. officinale from different geographical origins using near-infrared (NIR) spectroscopy and chemometrics. As the quality indicators, polysaccharides, polyphenols, total flavonoids, and total alkaloids were quantified. Three types of wavelength selection methods were used for model optimization and these were synergy interval (SI), genetic algorithm (GA), and competitive adaptive reweighted sampling (CARS). From the qualitative perspective, the geographical origins of D. officinale were differentiated by NIR spectroscopy combined with partial least squares-discriminant analysis (PLS-DA) and support vector classification (SVC). The PLS models constructed based on the wavelengths selected by CARS yielded the best performance for prediction of the contents of quality indicators in D. officinale. The root mean square error (RMSEP) and coefficient of determination (R_p²) in the independent test sets were 12.7768 g kg^-1 and 0.9586, 1.1346 g kg^-1 and 0.9670, 0.3938 g kg^-1 and 0.8803, 0.0825 and 0.7031 and for polysaccharides, polyphenols, total flavonoids, and total alkaloids, respectively. As for the origin identification, the nonlinear SVC was superior to the linear PLS-DA, with the correct recognition rates in calibration and prediction sets up to 100% and 100%, respectively. The overall results demonstrated the potential of NIR spectroscopy and chemometrics in the rapid determination of quality parameters and geographical origin. This study could provide a valuable reference for quality evaluation of D. officinale in a more rapid and comprehensive manner.

Utilization of ionic deep eutectic solvent as sustainable mobile phase additive in HPLC for improving the separation of biogenic amines

Biogenic amines are present in large quantities in fermented foods and are a key marker for assessing food safety. This paper proposes a novel method for high-performance liquid chromatography analysis of biogenic amines using deep eutectic solvent as mobile phase additive. After screening eight synthetic deep eutectic solvents and comparing with several common additives, deep eutectic solvents based on choline chloride and ethylene glycol showed significant effects for improving the separation of biogenic amines. A Box-Behnken design of 17 runs was used to screen and optimize the key chromatographic parameters, resulting in an expected composition of the mobile phase of 0.73% deep eutectic solvent, 65% acetonitrile, and a column temperature of 28°C. The proposed method exhibited excellent linearity (0.1-50 μg/mL, R² ≥ 0.9987), limit of detection (0.007-0.031 μg/mL), precision (1.28-5.34%) and accuracy (87.2-110.6%). The method can be applied successfully to the separation and analysis of biogenic amines in cooking wine samples. This article is protected by copyright. All rights reserved.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Analysis method development and health risk assessment of pesticide and heavy metal residues in Dendrobium Candidum

Herbal medicines that are widely used worldwide are easily contaminated by pesticides and heavy metals, threatening human health. In this study, a modified QuEChERS pre-treatment method combined with HPLC/GC-MS/MS was established for the determination of 24 pesticide residues in Dendrobium candidum. The average recoveries of 24 pesticides in D. candidum were 76.9-110.0% with the relative standard deviation (RSD) of 0.28-11.40%, and their limits of detection (LOD) and limits of quantitation (LOQ) were 0.005-10 and 0.011-22 μg kg^-1, respectively. The results showed that 83.33% of all samples had detected pesticide residues with the concentrations of 0.06-312.83 μg kg^-1. Meanwhile, microwave digestion combined with ICP-MS was used to detect the residues of 8 heavy metals in D. candidum. The average recoveries of 8 heavy metals were 82.7-108.1% with an RSD of 1.4-8.0%, and their LOD and LOQ were 0.0001-0.05 mg kg^-1 and 0.0003-0.2 mg kg^-1, respectively. The results indicated that 8 heavy metals were all detected in all samples, and the highest concentration of Zn was 11.97 mg kg^-1. Furthermore, the health risk assessment showed that the risk of the detected pesticides and heavy metals in samples to humans, specifically to the general population including adults and children, was acceptable.

Chemometrics-Assisted Raman Spectroscopy Characterization of Tunable Polymer-Peptide Hybrids for Dental Tissue Repair

The interfaces that biological tissues form with biomaterials are invariably defective and frequently the location where failure initiates. Characterizing the phenomena that lead to failure is confounded by several factors including heterogeneous material/tissue interfaces. To seamlessly analyze across these diverse structures presents a wealth of analytical challenges. This study aims to develop a molecular-level understanding of a peptide-functionalized adhesive/collagen hybrid biomaterial using Raman spectroscopy combined with chemometrics approach. An engineered hydroxyapatite-binding peptide (HABP) was copolymerized in dentin adhesive and dentin was demineralized to provide collagen matrices that were partially infiltrated with the peptide-functionalized adhesive. Partial infiltration led to pockets of exposed collagen-a condition that simulates defects in adhesive/dentin interfaces. The spectroscopic results indicate that co-polymerizable HABP tethered to the adhesive promoted remineralization of the defects. The spatial distribution of collagen, adhesive, and mineral as well as crystallinity of the mineral across this heterogeneous material/tissue interface was determined using micro-Raman spectroscopy combined with chemometrics approach. The success of this combined approach in the characterization of material/tissue interfaces stems from its ability to extract quality parameters that are related to the essential and relevant portions of the spectral data, after filtering out noise and non-relevant information. This ability is critical when it is not possible to separate components for analysis such as investigations focused on, in situ chemical characterization of interfaces. Extracting essential information from complex bio/material interfaces using data driven approaches will improve our understanding of heterogeneous material/tissue interfaces. This understanding will allow us to identify key parameters within the interfacial micro-environment that should be harnessed to develop durable biomaterials.

Research Advances in Multi-Omics on the Traditional Chinese Herb Dendrobium officinale

Dendrobium officinale Kimura et Migo is an important epiphytic plant, belonging to the Orchidaceae family. There are various bioactive components in D. officinale plants, mainly including polysaccharides, alkaloids, and phenolic compounds. These compounds have been demonstrated to possess multiple functions, such as anti-oxidation, immune regulation, and anti-cancer. Due to serious shortages of wild resources, deterioration of cultivated germplasm and the unstable quality of D. officinale, the study has been focused on the biosynthetic pathway and regulation mechanisms of bioactive compounds. In recent years, with rapid developments in detection technologies and analysis tools, omics research including genomics, transcriptomics, proteomics and metabolomics have all been widely applied in various medicinal plants, including D. officinale. Many important advances have been achieved in D. officinale research, such as chromosome-level reference genome assembly and the identification of key genes involved in the biosynthesis of active components. In this review, we summarize the latest research advances in D. officinale based on multiple omics studies. At the same time, we discuss limitations of the current research. Finally, we put forward prospective topics in need of further study on D. officinale.

Pesticide multi-residues in Dendrobium officinale Kimura et Migo: Method validation, residue levels and dietary exposure risk assessment

Dendrobium officinale Kimura et Migo (D. officinale) is a dual-use plant with both botanical medicine and food applications, drawing increasing attentions. Pesticides are inevitably applied on D. officinale in commercial artificial-sheltered cultivation, yet little is known about pesticide residue levels in D. officinale. A modified high through-put QuEChERS method coupled with HPLC-MS/MS was developed and validated to detect 76 pesticides in D. officinale. Graphitized multi-wall carbon nanotubes (g-MWCNTs) was selected as the clean-up sorbent, showing relative weak affinity to triazole fungicide having planar structure in their molecular and low matrix effects of pesticides in D. officinale samples compared to MWCNTs and pesticarb. The validated method was applied to analyze pesticide residues in 86 real D. officinale samples collected from three main producing provinces. 43 different pesticides were detected with highest residue of 6.11 mg/kg for dimethomorph. Given possible health risks related to pesticide residues, accordingly, risk assessment of human exposure to pesticides via intake of D. officinale was thus performed, indicating that the pesticide residue in fresh or dry D. officinale would not cause potential risk to human health either in the long-term or short-term. This work improved our understanding of potential exposure risk of pesticide multi-residues in D. officinale.