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Binding mode of triazole derivatives as aromatase inhibitors based on docking, protein ligand interaction fingerprinting, and molecular dynamics simulation studies.


ABSTRACT: Aromatase inhibitors (AIs) as effective candidates have been used in the treatment of hormone-dependent breast cancer. In this study, we have proposed 300 structures as potential AIs and filtered them by Lipinski's rule of five using DrugLito software. Subsequently, they were subjected to docking simulation studies to select the top 20 compounds based on their Gibbs free energy changes and also to perform more studies on the protein-ligand interaction fingerprint by AuposSOM software. In this stage, anastrozole and letrozole were used as positive control to compare their interaction fingerprint patterns with our proposed structures. Finally, based on the binding energy values, one active structure (ligand 15) was selected for molecular dynamic simulation in order to get information for the binding mode of these ligands within the enzyme cavity. The triazole of ligand 15 pointed to HEM group in aromatase active site and coordinated to Fe of HEM through its N4 atom. In addition, two ?-cation interactions was also observed, one interaction between triazole and porphyrin of HEM group, and the other was 4-chloro phenyl moiety of this ligand with Arg115 residue.

SUBMITTER: Mojaddami A 

PROVIDER: S-EPMC5333476 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Binding mode of triazole derivatives as aromatase inhibitors based on docking, protein ligand interaction fingerprinting, and molecular dynamics simulation studies.

Mojaddami Ayyub A   Sakhteman Amirhossein A   Fereidoonnezhad Masood M   Faghih Zeinab Z   Najdian Atena A   Khabnadideh Soghra S   Sadeghpour Hossein H   Rezaei Zahra Z  

Research in pharmaceutical sciences 20170201 1


Aromatase inhibitors (AIs) as effective candidates have been used in the treatment of hormone-dependent breast cancer. In this study, we have proposed 300 structures as potential AIs and filtered them by Lipinski's rule of five using DrugLito software. Subsequently, they were subjected to docking simulation studies to select the top 20 compounds based on their Gibbs free energy changes and also to perform more studies on the protein-ligand interaction fingerprint by AuposSOM software. In this st  ...[more]

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