Dataset Information

Assessing Spectral Analysis of Phytoconstituents and Their In Silico Interactions with Target Proteins in Plant Seed Extracts.

ABSTRACT: The pharmacological and preventive attributes of extracts from vegetable seeds have garnered widespread recognition within the scientific community. This study systematically assessed the in vitro antibacterial, antioxidant, and anti-breast cancer properties of phytochemicals present in various solvent-based vegetable seed extracts. We also conducted molecular docking simulations to ascertain their interactions with specific target proteins. Besides, nine distinct chemical constituents were identified using gas chromatography-mass spectrometry (GCMS). Remarkably, the ethyl acetate extract exhibited robust inhibitory effects against Gram-positive and Gram-negative bacterial strains. Furthermore, its capacity for 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging was found to be noteworthy, with an IC₅₀ value of 550.82 ± 1.7 µg/mL, representing a scavenging efficiency of 64.1 ± 2.8%. Additionally, the ethyl acetate extract demonstrated significant hydrogen peroxide (H₂O₂) scavenging activity, with a maximal scavenging rate of 44.1 ± 1.70% (IC₅₀) at a concentration of 761.17 ± 1.8 µg/mL. Intriguingly, in vitro cytotoxicity assays against human breast cancer (MCF-7) cells revealed varying levels of cell viability at different extract concentrations, suggesting potential anticancer properties. Importantly, these ethyl acetate extracts did not display toxicity to L929 cells across the concentration range tested. Subsequently, we conducted in-silico molecular docking experiments utilizing Discovery Studio 4.0 against the c-Met kinase protein (hepatocyte growth factor; PDB ID: 1N0W). Among the various compounds assessed, 3,4-Dihydroxy-1,6-bis-(3-methoxy-phenyl)-hexa-2,4-diene-1,6-dione exhibited a notable binding energy of -9.1 kcal/mol, warranting further investigation into its potential anticancer properties, clinical applications, and broader pharmacological characteristics.

SUBMITTER: Babu V

PROVIDER: S-EPMC10574034 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Assessing Spectral Analysis of Phytoconstituents and Their <i>In Silico</i> Interactions with Target Proteins in Plant Seed Extracts.

Babu Venkatadri V Ahamed J Irshad JI Paul Agastian A Ali Sajad S Rather Irfan A IA Sabir Jamal S M JSM

Plants (Basel, Switzerland) 20230922 19

The pharmacological and preventive attributes of extracts from vegetable seeds have garnered widespread recognition within the scientific community. This study systematically assessed the in vitro antibacterial, antioxidant, and anti-breast cancer properties of phytochemicals present in various solvent-based vegetable seed extracts. We also conducted molecular docking simulations to ascertain their interactions with specific target proteins. Besides, nine distinct chemical constituents were iden ...[more]

PMID: 37836092

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Project description:Amomum nilgiricum is one of the plant species reported from Western Ghats of India, belonging to the family Zingiberaceae, with ethno-botanical values, and is well-known for their ethno medicinal applications. In the present investigation, ethyl acetate and methanol extracts of A. nilgiricum were analyzed by Fourier transform infrared spectrometer (FTIR) and gas chromatography-mass spectrometry (GC-MS) to identify the important functional groups and phytochemical constituents. The FTIR spectra revealed the occurrence of functional characteristic peaks of aromatic amines, carboxylic acids, ketones, phenols and alkyl halides group from leaf and rhizome extracts. The GC-MS analysis of ethyl acetate and methanol extracts from leaves, and methanol extract from rhizomes of A. nilgiricum detected the presence of 25 phytochemical compounds. Further, the leaf and rhizome extracts of A. nilgiricum showed remarkable antibacterial and antifungal activities at 100 mg/mL. The results of DPPH and ferric reducing antioxidant power assay recorded maximum antioxidant activity in A. nilgiricum methanolic leaf extract. While, ethyl acetate leaf extract exhibited maximum α-amylase inhibition activity, followed by methanolic leaf extract exhibiting aldose reductase inhibition. Subsequently, these 25 identified compounds were analyzed for their bioactivity through in silico molecular docking studies. Results revealed that among the phytochemical compounds identified, serverogenin acetate might have maximum antibacterial, antifungal, antiviral, antioxidant and antidiabetic properties followed by 2,4-dimethyl-1,3-dioxane and (1,3-13C2)propanedioic acid. To our best knowledge, this is the first description on the phytochemical constituents of the leaves and rhizomes of A. nilgiricum, which show pharmacological significance, as there has been no literature available yet on GC-MS and phytochemical studies of this plant species. The in silico molecular docking of serverogenin acetate was also performed to confirm its broad spectrum activities based on the binding interactions with the antibacterial, antifungal, antiviral, antioxidant and antidiabetic target proteins. The results of the present study will create a way for the invention of herbal medicines for several ailments by using A. nilgiricum plants, which may lead to the development of novel drugs.

Project description:BackgroundComputational approaches in the identification of drug targets are expected to reduce time and effort in drug development. Advances in genomics and proteomics provide the opportunity to uncover properties of druggable genomes. Although several studies have been conducted for distinguishing drug targets from non-drug targets, they mainly focus on the sequences and functional roles of proteins. Many other properties of proteins have not been fully investigated.MethodsUsing the DrugBank (version 3.0) database containing nearly 6,816 drug entries including 760 FDA-approved drugs and 1822 of their targets and human UniProt/Swiss-Prot databases, we defined 1578 non-redundant drug target and 17,575 non-drug target proteins. To select these non-redundant protein datasets, we built four datasets (A, B, C, and D) by considering clustering of paralogous proteins.ResultsWe first reassessed the widely used properties of drug target proteins. We confirmed and extended that drug target proteins (1) are likely to have more hydrophobic, less polar, less PEST sequences, and more signal peptide sequences higher and (2) are more involved in enzyme catalysis, oxidation and reduction in cellular respiration, and operational genes. In this study, we proposed new properties (essentiality, expression pattern, PTMs, and solvent accessibility) for effectively identifying drug target proteins. We found that (1) drug targetability and protein essentiality are decoupled, (2) druggability of proteins has high expression level and tissue specificity, and (3) functional post-translational modification residues are enriched in drug target proteins. In addition, to predict the drug targetability of proteins, we exploited two machine learning methods (Support Vector Machine and Random Forest). When we predicted drug targets by combining previously known protein properties and proposed new properties, an F-score of 0.8307 was obtained.ConclusionsWhen the newly proposed properties are integrated, the prediction performance is improved and these properties are related to drug targets. We believe that our study will provide a new aspect in inferring drug-target interactions.

Dataset Information

Assessing Spectral Analysis of Phytoconstituents and Their In Silico Interactions with Target Proteins in Plant Seed Extracts.

Publications

Assessing Spectral Analysis of Phytoconstituents and Their <i>In Silico</i> Interactions with Target Proteins in Plant Seed Extracts.

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