In silico study directed towards identification of novel high-affinity inhibitors targeting an oncogenic protein: BRD4-BD1

ABSTRACT

Bromodomain-containing protein 4 (BRD4) is a member of the bromodomain and extra-terminal domain (BET) family of proteins. It epigentically regulates the transcription of growth-promoting genes and has become an attractive target for the development of anticancer and anti-inflammatory agents. In the current study, we performed an in silico screening of a small-molecule chemical library against the acetyl–lysine binding site of the first bromodomain (BD1) in BRD4 protein. Potential inhibitors identified through virtual screening were further studied through molecular dynamics simulations, water entrapment analysis and Molecular Mechanics (MM)/Poisson–Boltzmann surface area (PBSA) binding free energy calculations. Many of the identified compounds exhibit better G-score (–11.64 kcal∙mol⁻¹ to –10.31 kcal∙mol⁻¹) and predicted binding affinity (–9.66 kcal∙mol⁻¹ to –6.63 kcal∙mol⁻¹) values towards BRD4-BD1 than that of the reference compound (+)-JQ1. Molecular dynamics simulation studies show that in free-form BRD4 the reported conserved water molecules are not retained at their specific positoins due to flexibiliy in the ZA-loop. In BRD4–ligand complexes the number and positions of conserved water molecules depends on the bound ligand. Identified potential inhibitors bind stably at the acetyl–lysine binding pocket of BRD4 and form direct and water-mediated hydrogen bonds with higher occupancy which may contribute to ligand specificity towards BRD4-BD1. Further, through MM/PBSA we calculated the binding free energies of selected compounds, which shows that they have comparable energies to that of (+)-JQ1, while NSC744713 shows better binding free energy.

KEYWORDS:

• virtual screening
• molecular dynamics
• water entrapment analysis

Acknowledgements

The authors thank PAC-JNU-DST-PURSE-462(Phase-II) and University with Potential for Excellence (UPE-II)-JNU for their support and funding. Roshan Tumdam and Amarjeet Kumar acknowledge Council of Scientific Industrial Research (CSIR), India for providing the scholarship (JRF and SRF, respectively). Prof. Pradipta Bandyopadhyay, SCIS, JNU is acknowledged for allowing us to use AMBER16 package.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplementary material for this article can be accessed at: https://doi.org/10.1080/1062936X.2018.1537301