Dataset Information

PhytoSelectDBT: A database for the molecular models of anti-diabetic targets docked with bioactive peptides from selected ethno-medicinal plants.

ABSTRACT: It is of interest to assess the effectiveness of bioactive peptides derived from 41 ethno-medicinal plants, classify them according to their anti-diabetic protein targets (DPP-IV, alpha-amylase, alpha-glucosidase, GRK2, GSK3B, GLP-1R, and AdipoR1), and create a web tool named PhytoSelectDBT by using the top seven peptides per target. If one of the target-based medicinal plant suggestions made by PhytoSelectDBT is unsuccessful, alternative target-based possibilities are presented by PhytoSelectDBT for treating the condition and any other related complications. The results provide a useful resource for the management of type 2 diabetes and emphasize the significance of utilising ethnomedical knowledge for the identification of potent anti-diabetic plants and their peptides. We used molecular docking to investigate interactions between anti-diabetic targets (DPP-IV, alpha-amylase, alpha-glucosidase, GRK2, GSK3B, GLP-1R, and AdipoR1) and projected bioactive peptides from 41 ethnomedicinal plants. All bioactive peptides were cross-checked against several databases to determine their allergenicity, toxicity, and cross-reactivity. The presence of B and T cell epitopes was also examined in all simulated digested bioactive peptides for reference. This data is archived at the PhytoselectDBT database.

SUBMITTER: Roy S

PROVIDER: S-EPMC10625370 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

PhytoSelectDBT: A database for the molecular models of anti-diabetic targets docked with bioactive peptides from selected ethno-medicinal plants.

Roy Susanta S Teron Robindra R Nikku Linga Raju R

Bioinformation 20230930 9

It is of interest to assess the effectiveness of bioactive peptides derived from 41 ethno-medicinal plants, classify them according to their anti-diabetic protein targets (DPP-IV, alpha-amylase, alpha-glucosidase, GRK2, GSK3B, GLP-1R, and AdipoR1), and create a web tool named PhytoSelectDBT by using the top seven peptides per target. If one of the target-based medicinal plant suggestions made by PhytoSelectDBT is unsuccessful, alternative target-based possibilities are presented by PhytoSelectDB ...[more]

PMID: 37928486

Similar Datasets

Project description:Ethnopharmocological relevanceMembers of 'Mycoplasma mycoides cluster' are important ruminant pathogens in Africa. Diseases caused by these Mycoplasma negatively affect the agricultural sector especially in developing countries through losses in livestock productivity, mortality and international trade restrictions. There is therefore urgent need to develop antimicrobials from alternative sources such as medicinal plants to curb these diseases. In Kenya, smallholder farmers belonging to the Maasai, Kuria and Luo rely on traditional Kenyan herbals to treat respiratory symptoms in ruminants. In the current study extracts from some of these plants were tested against the growth of members of Mycoplasma mycoides cluster.AimThis study aimed at identifying plants that exhibit antimycoplasmal activities using an ethnobotanical approach.Materials and methodsKenyan farmers of Maasai, Luo and Kuria ethnic groups were interviewed for plant remedies given to livestock with respiratory syndromes. The plant materials were thereafter collected and crude extracts prepared using a mixture of 50% of methanol (MeOH) in dichloromethane (CH2Cl2), neat methanol (MeOH), ethanol (EtOH) and water to yield four crude extracts per plant part. The extracts were tested in vitro against five strains of Mycoplasma mycoides subsp. capri, five strains of Mycoplasma mycoides subsp. mycoides and one strain of Mycoplasma capricolum subsp capricolum using broth micro-dilution assays with an initial concentration of 1mg/ml. Minimum inhibitory concentration (MIC) of the most active extracts were determined by serial dilution.ResultsExtracts from five plants namely: Solanum aculeastrum, Albizia coriaria, Ekebergia capensis, Piliostigma thonningii and Euclea divinorum exhibited the highest activities against the Mycoplasma strains tested. Mycoplasma mycoides subsp. mycoides were more susceptible to these extracts than Mycoplasma mycoides subsp. capri and Mycoplasma capricolum susp. capricolum. The activities of the crude extracts varied with the solvent used for extraction. The MICs mean values of the active extracts varied from 0.02 to 0.6mg/ml.ConclusionsThe results suggested that these plants could potentially contain antimicrobial compounds that might be useful for the treatment of respiratory diseases in ruminants. Future work should focus on the isolation and identification of the active compounds from the plant extracts that showed interesting activities and evaluation of their antimicrobial and cytotoxic potential.

Project description:Natural products have been the center of attraction ever since they were discovered. Among them, plant-based natural products were popular as analgesics, anti-inflammatory, antidiabetic, and cosmetics and possess widespread biotechnological applications. The use of plant products as cosmetics and therapeutics is deep-rooted in Nepalese society. Although there are few ethnobotanical studies conducted, extensive research of these valuable medicinal plants has not been a priority due to the limitation of technology and infrastructure. Here, we selected 4 traditionally used medicinal plants to examine their bioactive properties and their enzyme inhibition potential. α-Glucosidase and α-amylase inhibitory activities were investigated using an in vitro model followed up by antioxidant and antimicrobial activities. The present study shows that ethyl acetate fraction of Melastoma melabathrium (IC50 9.1 ± 0.3 µg/mL) and water fraction Acacia catechu (IC50 9.0 ± 0.6 µg/mL) exhibit strong α-glucosidase inhibition. Likewise, the highest α-amylase inhibition was shown by crude extracts of Ficus religiosa (IC50 29.2 ± 1.2 µg/mL) and ethyl acetate fractions of Shorea robusta (IC50 69.3 ± 1.1 µg/mL), and the highest radical scavenging activity was shown by F. religiosa with an IC50 67.4 ± 0.6 µg/mL. Furthermore, to identify the metabolites within the fractions, we employed high-resolution mass spectrometry (LC-HRMS) and annotated 17 known metabolites which justify our assumption on activity. Of 4 medicinal plants examined, ethyl acetate fraction of S. robusta, ethyl acetate fraction of M. melabathrium, and water or ethyl acetate fraction of A. catechu extracts illustrated the best activities. With our study, we set up a foundation that provides authentic evidence to the community for use of these traditional plants. The annotated metabolites in this study support earlier experimental evidence towards the inhibition of enzymes. Further study is necessary to explore the clinical efficacy of these secondary molecules, which might be alternatives for the treatment of diabetes and pathogens.

Project description:Neurodegenerative diseases, for example Alzheimer's, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds' pIC50 values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R2 = 0.86 and Q2 = 0.73), pls_38 (R2 = 0.77 and Q2 = 0.72), kpls_desc_44 (R2 = 0.81 and Q2 = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of -9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of -9.60 and -9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (-6.30 kcal/mol). The docking scores of our standards were -10.40 and -7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.

Dataset Information

PhytoSelectDBT: A database for the molecular models of anti-diabetic targets docked with bioactive peptides from selected ethno-medicinal plants.

Publications

PhytoSelectDBT: A database for the molecular models of anti-diabetic targets docked with bioactive peptides from selected ethno-medicinal plants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets