Dataset Information

A virtual screening approach for identifying plants with anti H5N1 neuraminidase activity.

ABSTRACT: Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 ?M. Furthermore, four of the 12 isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources.

SUBMITTER: Ikram NK

PROVIDER: S-EPMC4340357 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A virtual screening approach for identifying plants with anti H5N1 neuraminidase activity.

Ikram Nur Kusaira Khairul NK Durrant Jacob D JD Muchtaridi Muchtaridi M Zalaludin Ayunni Salihah AS Purwitasari Neny N Mohamed Nornisah N Rahim Aisyah Saad Abdul AS Lam Chan Kit CK Normi Yahaya M YM Rahman Noorsaadah Abd NA Amaro Rommie E RE Wahab Habibah A HA

Journal of chemical information and modeling 20150129 2

Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were ...[more]

PMID: 25555059

Similar Datasets

Project description:AimTo identify the critical chemical features, with reliable geometric constraints, that contributes to the inhibition of butyrylcholinesterase (BChE) function.MethodsLigand-based pharmacophore modeling was used to identify the critical chemical features of BChE inhibitors. The generated pharmacophore model was validated using various techniques, such as Fischer's randomization method, test set, and decoy set. The best pharmacophore model was used as a query in virtual screening to identify novel scaffolds that inhibit BChE. Compounds selected by the best hypothesis in the virtual screening were tested for drug-like properties, and molecular docking study was applied to determine the optimal orientation of the hit compounds in the BChE active site. To find the reactivity of the hit compounds, frontier orbital analysis was carried out using density functional theory.ResultsBased on its correlation coefficient (0.96), root mean square (RMS) deviation (1.01), and total cost (105.72), the quantitative hypothesis Hypo1 consisting of 2 HBA, 1 Hy-Ali, and 1 Hy-Ar was selected as the best hypothesis. Thus, Hypo1 was used as a 3D query in virtual screening of the Maybridge and Chembridge databases. The hit compounds were filtered using ADMET, Lipinski's Rule of Five, and molecular docking to reduce the number of false positive results. Finally, 33 compounds were selected based on their critical interactions with the significant amino acids in BChE's active site. To confirm the inhibitors' potencies, the orbital energies, such as HOMO and LUMO, of the hit compounds and 7 training set compounds were calculated. Among the 33 hit compounds, 10 compounds with the highest HOMO values were selected, and this set was further culled to 5 compounds based on their energy gaps important for stability and energy transfer. From the overall results, 5 hit compounds were confirmed to be potential BChE inhibitors that satisfied all the pharmacophoric features in Hypo1.ConclusionThis study pinpoints important chemical features with geometric constraints that contribute to the inhibition of BChE activity. Five compounds are selected as the best hit BchE-inhibitory compounds.

Project description:Medicinal plants containing complex mixtures of several compounds with various potential beneficial biological effects are attractive treatment interventions for a complex multi-faceted disease like diabetes. In this study, compounds identified from African medicinal plants were evaluated for their potential anti-diabetic activity. A total of 867 compounds identified from over 300 medicinal plants were screened in silico with the DIA-DB web server (http://bio-hpc.eu/software/dia-db/) against 17 known anti-diabetic drug targets. Four hundred and thirty compounds were identified as potential inhibitors, with 184 plants being identified as the sources of these compounds. The plants Argemone ochroleuca, Clivia miniata, Crinum bulbispermum, Danais fragans, Dioscorea dregeana, Dodonaea angustifolia, Eucomis autumnalis, Gnidia kraussiana, Melianthus comosus, Mondia whitei, Pelargonium sidoides, Typha capensis, Vinca minor, Voacanga Africana, and Xysmalobium undulatum were identified as new sources rich in compounds with a potential anti-diabetic activity. The major targets identified for the natural compounds were aldose reductase, hydroxysteroid 11-beta dehydrogenase 1, dipeptidyl peptidase 4, and peroxisome proliferator-activated receptor delta. More than 30% of the compounds had five or more potential targets. A hierarchical clustering analysis coupled with a maximum common substructure analysis revealed the importance of the flavonoid backbone for predicting potential activity against aldose reductase and hydroxysteroid 11-beta dehydrogenase 1. Filtering with physiochemical and the absorption, distribution, metabolism, excretion and toxicity (ADMET) descriptors identified 28 compounds with favorable ADMET properties. The six compounds-crotofoline A, erythraline, henningsiine, nauclefidine, vinburnine, and voaphylline-were identified as novel potential multi-targeted anti-diabetic compounds, with favorable ADMET properties for further drug development.

Dataset Information

A virtual screening approach for identifying plants with anti H5N1 neuraminidase activity.

Publications

A virtual screening approach for identifying plants with anti H5N1 neuraminidase activity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets