Quantitative structure–chromatographic retention relationship of synthesized peptides (HGRFG, NPNPT) and their derivatives

Yang, Xiangrong; Peng, Huan; Han, Ning; Zhang, Zhongqi; Bai, Xuejuan; Zhao, Te; Zhao, Jinli; Liu, Jianli

doi:10.1016/j.ab.2020.113653

Cited by 4 publications

(2 citation statements)

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“…Comprehensive models that consider the influence of different chromatographic conditions are more accurate in predicting the retention times of compounds. However, previous studies have generally predicted the chromatographic retention or lipophilicity by using the quantitative structure–retention relationship (QSRR) models ( Yang X. et al, 2020 ; Fouad et al, 2022 ; Xu et al, 2023 ). The QSRR models mainly focus on the molecular descriptors of the solutes, with less emphasis on the influence of different chromatographic conditions.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT)

et al. 2023

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Introduction: Oligopeptides exhibit great prospects for clinical application and its separation is of great importance in new drug development.Methods: To accurately predict the retention of pentapeptides with analogous structures in chromatography, the retention times of 57 pentapeptide derivatives in seven buffers at three temperatures and four mobile phase compositions were measured via reversed-phase high-performance liquid chromatography. The parameters (kHA, kA, and pKa) of the acid–base equilibrium were obtained by fitting the data corresponding to a sigmoidal function. We then studied the dependence of these parameters on the temperature (T), organic modifier composition (φ, methanol volume fraction), and polarity (PmN parameter). Finally, we proposed two six-parameter models with (1) pH and T and (2) pH and φ or PmN as the independent variables. These models were validated for their prediction capacities by linearly fitting the predicted retention factor k-value and the experimental k-value.Results: The results showed that logkHA and logkA exhibited linear relationships with 1/T, φ or PmN for all pentapeptides, especially for the acid pentapeptides. In the model of pH and T, the correlation coefficient (R2) of the acid pentapeptides was 0.8603, suggesting a certain prediction capability of chromatographic retention. Moreover, in the model of pH and φ or PmN, the R2 values of the acid and neutral pentapeptides were greater than 0.93, and the average root mean squared error was approximately 0.3, indicating that the k-values could be effectively predicted.Discussion: In summary, the two six-parameter models were appropriate to characterize the chromatographic retention of amphoteric compounds, especially the acid or neutral pentapeptides, and could predict the chromatographic retention of pentapeptide compounds.

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Section: Introductionmentioning

confidence: 99%

Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT)

et al. 2023

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“…[6,7] Emerging studies have indicated that Carapax Trionycis extracted peptides are the main active substances against liver fibrosis, and isolated and identified several peptides with anti-hepatic fibrosis activity. [8][9][10] About a decade ago, Lei's group extracted and isolated a heptapeptide from aqueous extract of Carapax trionycis, and found that it had hepatoprotective activity in the mouse model of carbon tetrachloride-induced acute liver injury. [11] Then, in another study, Sun et al discovered that the peptide inhibited liver fibrosis by blocking NF-κB pathway and Wnt/β-catenin pathway in vivo and in vitro.…”

Section: Introductionmentioning

confidence: 99%

A network pharmacology approach to explore the molecular mechanism of active peptide ingredients of Carapax Trionycis on liver fibrosis

Yan,

Zhao,

Lin

et al. 2023

Peptide Science

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Carapax Trionycis is a traditional Chinese medicine and it has been clear that oligo‐peptides from Carapax Trionycis extract (CTP) are the main active substances for the treatment of liver diseases. However, little is known about the mechanism of CTP against liver fibrosis. Here, network pharmacology combined with molecular docking were performed to identify the in‐silico molecular mechanism and the potential targets for CTP to ameliorate liver fibrosis. We collected eight active peptides ingredients that published in public databases and predicted the targets. Liver fibrosis related genes were acquired from the GeneCards and DisGeNET platform. Then, we identified a total of 52 peptides‐liver fibrosis‐related genes. KEGG and GO enrichment analyses indicated that these targets are significantly enriched in relaxin signaling pathway, IL‐17 signaling pathway, TNF signaling pathway. We identified the top 10 genes with high centrality measures from the network by CytoHubba, including CASP3, AKT1, IL1B, MMP9, and PTGS2. The molecular docking between these hub genes and the corresponding CTP was performed in GRAMM and visualized by PyMOL. Our results provide an important reference and scientific basis for treating liver fibrosis with CTP.

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QSRR modelling aimed on the HPLC retention prediction of dimethylamino- and pyrrolidino-substitued esters of alkoxyphenylcarbamic acid

et al. 2021

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Quantitative structure–chromatographic retention relationship of synthesized peptides (HGRFG, NPNPT) and their derivatives

Cited by 4 publications

References 20 publications

Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT)

Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT)

A network pharmacology approach to explore the molecular mechanism of active peptide ingredients of Carapax Trionycis on liver fibrosis

QSRR modelling aimed on the HPLC retention prediction of dimethylamino- and pyrrolidino-substitued esters of alkoxyphenylcarbamic acid

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