Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Virtual Screening of DrugBank Reveals Two Drugs as New BCRP Inhibitors.

ABSTRACT: The breast cancer resistance protein (BCRP) is an ABC transporter playing a crucial role in the pharmacokinetics of drugs. The early identification of substrates and inhibitors of this efflux transporter can help to prevent or foresee drug-drug interactions. In this work, we built a ligand-based in silico classification model to predict the inhibitory potential of drugs toward BCRP. The model was applied as a virtual screening technique to identify potential inhibitors among the small-molecules subset of DrugBank. Ten compounds were selected and tested for their capacity to inhibit mitoxantrone efflux in BCRP-expressing PLB985 cells. Results identified cisapride (IC50 = 0.4 µM) and roflumilast (IC50 = 0.9 µM) as two new BCRP inhibitors. The in silico strategy proved useful to prefilter potential drug-drug interaction perpetrators among a database of small molecules and can reduce the amount of compounds to test.

SUBMITTER: Montanari F

PROVIDER: S-EPMC5302078 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Virtual Screening of DrugBank Reveals Two Drugs as New BCRP Inhibitors.

Montanari Floriane F Cseke Anna A Wlcek Katrin K Ecker Gerhard F GF

SLAS discovery : advancing life sciences R & D 20160711 1

The breast cancer resistance protein (BCRP) is an ABC transporter playing a crucial role in the pharmacokinetics of drugs. The early identification of substrates and inhibitors of this efflux transporter can help to prevent or foresee drug-drug interactions. In this work, we built a ligand-based in silico classification model to predict the inhibitory potential of drugs toward BCRP. The model was applied as a virtual screening technique to identify potential inhibitors among the small-molecules ...[more]

PMID: 27401583

Similar Datasets

Identification of new EphA4 inhibitors by virtual screening of FDA-approved drugs.

Project description:The receptor tyrosine kinase, erythropoietin-producing hepatocellular A4 (EphA4), was recently identified as a molecular target for Alzheimer's disease (AD). We found that blockade of the interaction of the receptor and its ligands, ephrins, alleviates the disease phenotype in an AD transgenic mouse model, suggesting that targeting EphA4 is a potential approach for developing AD interventions. In this study, we identified five FDA-approved drugs-ergoloid, cyproheptadine, nilotinib, abiraterone, and retapamulin-as potential inhibitors of EphA4 by using an integrated approach combining virtual screening with biochemical and cellular assays. We initially screened a database of FDA-approved drugs using molecular docking against the ligand-binding domain of EphA4. Then, we selected 22 candidate drugs and examined their inhibitory activity towards EphA4. Among them, five drugs inhibited EphA4 clustering induced by ephrin-A in cultured primary neurons. Specifically, nilotinib, a kinase inhibitor, inhibited the binding of EphA4 and ephrin-A at micromolar scale in a dosage-dependent manner. Furthermore, nilotinib inhibited the activation of EphA4 and EphA4-dependent growth cone collapse in cultured hippocampal neurons, demonstrating that the drug exhibits EphA4 inhibitory activity in cellular context. As demonstrated in our combined computational and experimental approaches, repurposing of FDA-approved drugs to inhibit EphA4 may provide an alternative fast-track approach for identifying and developing new treatments for AD.

| S-EPMC5943255 | biostudies-literature

Identification of SARS-CoV-2 Main Protease Inhibitors Using Structure Based Virtual Screening and Molecular Dynamics Simulation of DrugBank Database.

Project description:Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly pathogenic to humans and has created an unprecedented global health care threat. Globally, intense efforts are going on to discover a vaccine or new drug molecules to control the COVID-19. However, till today, there is no effective therapeutics or treatment available for COVID-19. In this study, we aim to find out potential small molecule inhibitors for SARS-CoV-2 main protease (Mpro) from the known DrugBank database version 5.1.8. We applied structure-based virtual screening of the database containing 11875 numbers of drug candidates to identify potential hits for SARS-CoV-2 Mpro inhibitors. Seven potential inhibitors having admirable XP glide score ranging from -15.071 to -8.704 kcal/mol and good binding affinity with the active sites amino acids of Mpro were identified. The selected hits were further analyzed with 50 ns molecular dynamics (MD) simulation to examine the stability of protein-ligand complexes. The root mean square deviation and potential energy plot indicates the stability of the complexes during the 50 ns MD simulation. The MM-GBSA analysis also showed good binding energy of the selected hits (-83.2718 to -58.6618 kcal/mol). Further analysis revealed critical hydrogen bonds and hydrophobic interactions between compounds and the target protein. The compounds bind to biologically important regions of Mpro, indicating their potential to inhibit the functionality of this component.

| S-EPMC8441713 | biostudies-literature

A multi-stage virtual screening of FDA-approved drugs reveals potential inhibitors of SARS-CoV-2 main protease.

Project description:Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an ongoing global health emergency. Repurposing of approved pharmaceutical drugs for COVID-19 treatment represents an attractive approach to quickly identify promising drug candidates. SARS-CoV-2 main protease (Mpro) is responsible for the maturation of viral functional proteins making it a key antiviral target. Based on the recently revealed crystal structures of SARS-CoV-2 Mpro, we herein describe a multi-stage virtual screening protocol including pharmacophore screening, molecular docking and protein-ligand interaction fingerprints (PLIF) post-docking filtration for efficient enrichment of potent SARS-CoV-2 Mpro inhibitors. Potential hits, along with a cocrystallized control were further studied via molecular dynamics. A 150-ns production trajectory was followed by RMSD, free energy calculation, and H-bond analysis for each compound. The applied virtual screening protocol led to identification of five FDA-approved drugs with promising binding modes to key subsites of the substrate-binding pocket of SARS-CoV-2 Mpro. The identified compounds belong to different pharmaceutical classes, including several protease inhibitors, antineoplastic agents and a natural flavonoid. The drug candidates discovered in this study present a potential extension of the recently reported SARS-CoV-2 Mpro inhibitors that have been identified using other virtual screening protocols and may be repurposed for COVID-19 treatment.

| S-EPMC7597227 | biostudies-literature

Virtual screening of approved drugs as potential SARS-CoV-2 main protease inhibitors.

Project description:The global emergency caused by COVID-19 makes the discovery of drugs capable of inhibiting SARS-CoV-2 a priority, to reduce the mortality and morbidity of this disease. Repurposing approved drugs can provide therapeutic alternatives that promise rapid and ample coverage because they have a documented safety record, as well as infrastructure for large-scale production. The main protease of SARS-CoV-2 (Mpro) is an excellent therapeutic target because it is critical for viral replication; however, Mpro has a highly flexible active site that must be considered when performing computer-assisted drug discovery. In this work, potential inhibitors of the main protease (Mpro) of SARS-Cov-2 were identified through a docking-assisted virtual screening procedure. A total of 4384 drugs, all approved for human use, were screened against three conformers of Mpro. The ligands were further studied through molecular dynamics simulations and binding free energy analysis. A total of nine currently approved molecules are proposed as potential inhibitors of SARS-CoV-2. These molecules can be further tested to speed the development of therapeutics against COVID-19.

| S-EPMC7316061 | biostudies-literature

Discovery of new butyrylcholinesterase inhibitors via structure-based virtual screening.

Project description:Butyrylcholinesterase (BChE) plays an important role in the progression of the Alzheimer's disease. In this study, we used a structure-based virtual screening (VS) approach to discover new BChE inhibitors. A ligand database was filtered and docked to the BChE protein using Glide program. The outcome from VS was filtered and the top ranked hits were thoroughly examined for their fitting into the protein active site. Consequently, the best 38 hits were selected for in vitro testing using Ellman's method, and six of which showed inhibition activity for BChE. Interestingly, the most potent hit (Compound 4) exhibited inhibitory activity against the BChE enzyme in the low micromolar level with an IC50 value of 8.3?µM. Hits obtained from this work can act as a starting point for future SAR studies to discover new BChE inhibitors as anti-Alzheimer agents.

| S-EPMC6711031 | biostudies-literature

In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2.

Project description:Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC50 values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R2 = 0.897, Q2LOO = 0.854, and Q2ext = 0.876 and complying with all the parameters established in the validation Tropsha's test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC50 value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC50 values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes.

| S-EPMC7923184 | biostudies-literature

Identification of a New Series of STAT3 Inhibitors by Virtual Screening.

Project description:The signal transducer and activator of transcription 3 (STAT3) is considered to be an attractive therapeutic target for oncology drug development. We identified a N-[2-(1,3,4-oxadiazolyl)]-4-quinolinecarboxamide derivative, STX-0119, as a novel STAT3 dimerization inhibitor by a virtual screen using a customized version of the DOCK4 program with the crystal structure of STAT3. In addition, we used in vitro cell-based assays such as the luciferase reporter gene assay and the fluorescence resonance energy transfer-based STAT3 dimerization assay. STX-0119 selectively abrogated the DNA binding activity of STAT3 and suppressed the expression of STAT3-regulated oncoproteins such as c-myc and survivin in cancer cells. In contrast, a truncated inactive analogue, STX-0872, did not exhibit those activities. Oral administration of STX-0119 effectively abrogated the growth of human lymphoma cells in a SCC-3 subcutaneous xenograft model without visible toxicity. Structure-activity relationships of STX-0119 derivatives were investigated using the docking model of the STAT3-SH2 domain/STX-0119.

| S-EPMC4007973 | biostudies-literature

Identification of new classes of ricin toxin inhibitors by virtual screening.

Project description:We used two virtual screening programs, ICM and GOLD, to dock nearly 50,000 compounds into each of two conformations of the target protein ricin A chain (RTA). A limited control set suggests that candidates scored highly by two programs may have a higher probability of being ligands than those in a list from a single program. Based on the virtual screens, we purchased 306 compounds that were subjected to a kinetic assay. Six compounds were found to give modest, but significant, inhibition of RTA. They also tended to inhibit Shiga toxin A chain, with roughly the same IC(50). The compounds generally represent novel chemical platforms that do not resemble RTA substrates, as currently known inhibitors do. These six were also tested in a cell-based assay for their ability to protect cells from intact ricin. Two compounds were effective in this regard, showing modest to strong ricin inhibition, but also showing some cytotoxicity. RTA, with its large, polar active site is a difficult drug design target which is expected to bind small molecules only weakly. The ability of the method to find these novel platforms is encouraging and suggests virtual screening can contribute to the search for ricin and Shiga toxin inhibitors.

| S-EPMC2929769 | biostudies-literature

New classes of potent heparanase inhibitors from ligand-based virtual screening.

Project description:Heparanase is a validated target in cancer therapy and a potential target for several inflammatory pathologies. A ligand-based virtual screening of commercial libraries was performed to expand the chemical space of small-molecule inhibitors. The screening was based on similarity with known inhibitors and was performed in several runs, starting from literature compounds and progressing through newly discovered inhibitors. Among the fifty-five tested compounds, nineteen had IC50 values lower than 5 µM and some showed remarkable potencies. Importantly, tere- and isophthalamides derivatives belong to new structural classes of heparanase inhibitors and some of them showed enzyme affinities (61 and 63, IC50 = 0.32 and 0.12 µM, respectively) similar to those of the most potent small-molecule inhibitors reported so far. Docking studies provided a comprehensive binding hypothesis shared by compounds with significant structural diversity. The most potent inhibitors reduced cell invasiveness and inhibited the expression of proangiogenic factors in tumour cell lines.

| S-EPMC7534336 | biostudies-literature

Identification by shape-based virtual screening and evaluation of new tyrosinase inhibitors.

Project description:Targeting tyrosinase is considered to be an effective way to control the production of melanin. Tyrosinase inhibitor is anticipated to provide new therapy to prevent skin pigmentation, melanoma and neurodegenerative diseases. Herein, we report our results in identifying new tyrosinase inhibitors. The shape-based virtual screening was performed to discover new tyrosinase inhibitors. Thirteen potential hits derived from virtual screening were tested by biological determinations. Compound 5186-0429 exhibited the most potent inhibitory activity. It dose-dependently inhibited the activity of tyrosinase, with the IC50 values 6.2 ± 2.0 µM and 10.3 ± 5.4 µM on tyrosine and L-Dopa formation, respectively. The kinetic study of 5186-0429 demonstrated that this compound acted as a competitive inhibitor. We believe the discoveries here could serve as a good starting point for further design of potent tyrosinase inhibitor.

| S-EPMC5788061 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data