Discovery of natural adenosine monophosphate‑activated protein kinase activators through virtual screening and activity verification studies

Molecular Docking Study of Phytosterols in Lygodium microphyllum Towards SIRT1 and AMPK, the in vitro Brine Shrimp Toxicity Test, and the Phenols and Sterols Levels in the Extract

Background

Lygodium microphyllum is a fern plant with various pharmacological activities, and phytosterols were reported contained in the n-hexane and ethyl acetate extract of this plant. Phytosterols are known to inhibit steatosis, oxidative stress, and inflammation. Sirtuin 1 (SIRT1) and adenosine monophosphate-activated protein kinase (AMPK) are the key proteins that control lipogenesis. However, information about L. microphyllum on SIRT1 and AMPK is still lacking.

Purpose

This study aims to investigate the binding mode of phytosterols in L. microphyllum extract towards AMPK and SIRT1, and the toxicity of the extract against brine shrimp (Artemia salina) larvae, and to determine the phenols and sterols levels in the extract.

Methods

The molecular docking was performed towards SIRT1 and AMPK using AutoDock v4.2.6, the toxicity of the extract was assayed against brine shrimp (Artemia salina) larvae, and the phytosterols were analyzed by employing a thin layer chromatography densitometry, and the total phenols were by spectrophotometry.

Results

The molecular docking study revealed that β-sitosterol and stigmasterol could occupy the active allosteric-binding site of SIRT1 and AMPK by binding to important residues similar to the protein's activators. The cold extraction of the plant yields 15.86% w/w. Phytochemical screening revealed the presence of phenols, steroids, flavonoids, alkaloids, and saponins. The total phenols are equivalent to 126 mg gallic acid (GAE)/g dry extract, the total sterols are 954.04 µg/g, and the β-sitosterol level is 283.55 µg/g. The LC50 value of the extract towards A. salina larvae is 203.704 ppm.

Conclusion

Lygodium microphyllum extract may have the potential to be further explored for its pharmacology activities, particularly in the discovery of plant-based anti-dyslipidemic drug candidates. However, further studies are needed to confirm their roles in alleviating lipid disorders.

Modeling Structure-Activity Relationship of AMPK Activation

The adenosine monophosphate activated protein kinase (AMPK) is critical in the regulation of important cellular functions such as lipid, glucose, and protein metabolism; mitochondrial biogenesis and autophagy; and cellular growth. In many diseases-such as metabolic syndrome, obesity, diabetes, and also cancer-activation of AMPK is beneficial. Therefore, there is growing interest in AMPK activators that act either by direct action on the enzyme itself or by indirect activation of upstream regulators. Many natural compounds have been described that activate AMPK indirectly. These compounds are usually contained in mixtures with a variety of structurally different other compounds, which in turn can also alter the activity of AMPK via one or more pathways. For these compounds, experiments are complicated, since the required pure substances are often not yet isolated and/or therefore not sufficiently available. Therefore, our goal was to develop a screening tool that could handle the profound heterogeneity in activation pathways of the AMPK. Since machine learning algorithms can model complex (unknown) relationships and patterns, some of these methods (random forest, support vector machines, stochastic gradient boosting, logistic regression, and deep neural network) were applied and validated using a database, comprising of 904 activating and 799 neutral or inhibiting compounds identified by extensive PubMed literature search and PubChem Bioassay database. All models showed unexpectedly high classification accuracy in training, but more importantly in predicting the unseen test data. These models are therefore suitable tools for rapid in silico screening of established substances or multicomponent mixtures and can be used to identify compounds of interest for further testing.

An efficient protein extraction method applied to mangrove plant Kandelia obovata leaves for proteomic analysis

BACKGROUND

Mangroves plants, an important wetland system in the intertidal shores, play a vital role in estuarine ecosystems. However, there is a lack of a very effective method for extracting protein from mangrove plants for proteomic analysis. Here, we evaluated the efficiency of three different protein extraction methods for proteomic analysis of total proteins obtained from mangrove plant Kandelia obovata leaves.

RESULTS

The protein yield of the phenol-based (Phe-B) method (4.47 mg/g) was significantly higher than the yields of the traditional phenol (Phe) method (2.38 mg/g) and trichloroacetic acid-acetone (TCA-A) method (1.15 mg/g). The Phe-B method produced better two-dimensional electrophoresis (2-DE) protein patterns with high reproducibility regarding the number, abundance and coverage of protein spots. The 2-DE gels showed that 847, 650 and 213 unique protein spots were separated from the total K. obovata leaf proteins extracted by the Phe-B, Phe and TCA-A methods, respectively. Fourteen pairs of protein spots were randomly selected from 2-DE gels of Phe- and Phe-B- extracted proteins for identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS) technique, and the results of three pairs were consistent. Further, oxygen evolving enhancer protein and elongation factor Tu could be observed in the 2-DE gels of Phe and Phe-B methods, but could only be detected in the results of the Phe-B methods, showing that Phe-B method might be the optimized choice for proteomic analysis.

CONCLUSION

Our data provides an improved Phe-B method for protein extraction of K. obovata and other mangrove plant tissues which is rich in polysaccharides and polyphenols. This study might be expected to be used for proteomic analysis in other recalcitrant plants.