Targeting natural compounds against HER2 kinase domain as potential anticancer drugs applying pharmacophore based molecular modelling approaches.
Comput Biol Chem
; 74: 327-338, 2018 Jun.
Article
en En
| MEDLINE
| ID: mdl-29702367
ABSTRACT
Human epidermal growth factor receptors are implicated in several types of cancers characterized by aberrant signal transduction. This family comprises of EGFR (ErbB1), HER2 (ErbB2, HER2/neu), HER3 (ErbB3), and HER4 (ErbB4). Amongst them, HER2 is associated with breast cancer and is one of the most valuable targets in addressing the breast cancer incidences. For the current investigation, we have performed 3D-QSAR based pharmacophore search for the identification of potential inhibitors against the kinase domain of HER2 protein. Correspondingly, a pharmacophore model, Hypo1, with four features was generated and was validated employing Fischer's randomization, test set method and the decoy test method. The validated pharmacophore was allowed to screen the colossal natural compounds database (UNPD). Subsequently, the identified 33 compounds were docked into the proteins active site along with the reference after subjecting them to ADMET and Lipinski's Rule of Five (RoF) employing the CDOCKER implemented on the Discovery Studio. The compounds that have displayed higher dock scores than the reference compound were scrutinized for interactions with the key residues and were escalated to MD simulations. Additionally, molecular dynamics simulations performed by GROMACS have rendered stable root mean square deviation values, radius of gyration and potential energy values. Eventually, based upon the molecular dock score, interactions between the ligands and the active site residues and the stable MD results, the number of Hits was culled to two identifying Hit1 and Hit2 has potential leads against HER2 breast cancers.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Mama
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Receptor ErbB-2
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Inhibidores de Proteínas Quinasas
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Simulación del Acoplamiento Molecular
/
Antineoplásicos
Tipo de estudio:
Clinical_trials
/
Prognostic_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Comput Biol Chem
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
/
QUIMICA
Año:
2018
Tipo del documento:
Article