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In Silico Targeting Human Multidrug Transporter ABCG2 in Breast Cancer: Database Screening, Molecular Docking, and Molecular Dynamics Study
- Source :
- Molecular Informatics. 41:2060039
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- ABCG2 is a substantial member of the ABC transporter superfamily that plays a significant role in multidrug resistance in cancer. Until recently, the 3D structure of ABCG2 has not been resolved, which resulted in the limitation of developing potential ABCG2 inhibitors using structure-based drug discovery. Herein, eMolecules, ChEMBL, and ChEBI databases, containing >25 million compounds, were virtually screened against the ABCG2 transporter in homodimer form. Performance of AutoDock4.2.6 software to predict inhibitor-ABCG2 binding mode and affinity were validated on the basis of available experimental data. The explored databases were filtered based on docking scores. The most potent hits with binding affinities higher than that of experimental bound ligand (MZ29) were then selected and subjected to molecular mechanics minimization, followed by binding energy calculation using molecular mechanics-generalized Born surface area (MM-GBSA) approach. Furthermore, molecular dynamics simulations for 50 ns, followed by MM-GBSA binding energy calculations, were performed for the promising compounds, unveiling eight potential inhibitors with binding affinities
- Subjects :
- Abcg2
In silico
Breast Neoplasms
ATP-binding cassette transporter
Molecular Dynamics Simulation
Ligands
computer.software_genre
Molecular mechanics
Structural Biology
Drug Discovery
ATP Binding Cassette Transporter, Subfamily G, Member 2
Humans
Early Detection of Cancer
Database
biology
Chemistry
Drug discovery
Organic Chemistry
chEMBL
Ligand (biochemistry)
Neoplasm Proteins
Computer Science Applications
Molecular Docking Simulation
Docking (molecular)
biology.protein
Molecular Medicine
Female
computer
Subjects
Details
- ISSN :
- 18681751 and 18681743
- Volume :
- 41
- Database :
- OpenAIRE
- Journal :
- Molecular Informatics
- Accession number :
- edsair.doi.dedup.....14c8432f06842b44b50e590dbf87ea7c
- Full Text :
- https://doi.org/10.1002/minf.202060039