Title:Lead Molecules as Novel Aromatase Inhibitors: In Silico De Novo Designing and Binding Affinity Studies
VOLUME: 17 ISSUE: 5
Author(s):Laxmi Banjare, Sant Kumar Verma, Akhlesh Kumar Jain and Suresh Thareja*
Affiliation:School of Pharmaceutical Sciences, Guru Ghasidas Central University, Bilaspur- 495009 (C.G.), School of Pharmaceutical Sciences, Guru Ghasidas Central University, Bilaspur- 495009 (C.G.), School of Pharmaceutical Sciences, Guru Ghasidas Central University, Bilaspur- 495009 (C.G.), School of Pharmaceutical Sciences, Guru Ghasidas Central University, Bilaspur- 495009 (C.G.)
Keywords:Aromatase inhibitors, breast cancer, de novo drug design, drug likeness, e-LEA3D, molecular docking.
Abstract:Background: Aromatase inhibitors emerged as a pivotal moiety to selectively block
estrogen production, prevention and treatment of tumour growth in breast cancer. De novo drug
design is an alternative approach to blind virtual screening for successful designing of the novel
molecule against various therapeutic targets.
Objective: In the present study, we have explored the de novo approach to design novel aromatase
inhibitors.
Methods: The e-LEA3D, a computational-aided drug design web server was used to design novel
drug-like candidates against the target aromatase. For drug-likeness ADME parameters (molecular
weight, H-bond acceptors, H-bond donors, LogP and number of rotatable bonds) of designed
molecules were calculated in TSAR software package, geometry optimization and energy
minimization was accomplished using Chem Office. Further, molecular docking study was
performed in Molegro Virtual Docker (MVD).
Results: Among 17 generated molecules using the de novo pathway, 13 molecules passed the
Lipinski filter pertaining to their bioavailability characteristics. De novo designed molecules with
drug-likeness were further docked into the mapped active site of aromatase to scale up their affinity
and binding fitness with the target. Among de novo fabricated drug like candidates (1-13), two
molecules (5, 6) exhibited higher affinity with aromatase in terms of MolDock score
(-150.650, -172.680 Kcal/mol, respectively) while molecule 8 showed lowest target affinity (-85.588
Kcal/mol).
Conclusion: The binding patterns of lead molecules (5, 6) could be used as a pharmacophore for
medicinal chemists to explore these molecules for their aromatase inhibitory potential.
