Molecular mechanism of inhibitor bindings to bromodomain-containing protein 9 explored based on molecular dynamics simulations and calculations of binding free energies

ABSTRACT

Recently, bromodomain-containing protein 9 (BRD9) has been a prospective therapeutic target for anticancer drug design. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were adopted to explore binding modes of three inhibitors (5SW, 5U2, and 5U6) to BRD9 and identify the hot spot of the inhibitor-BRD9 binding. The results indicate that the inhibitor 5SW has the strongest binding ability to BRD9 among the current three inhibitors. Furthermore, the rank of the binding free energies predicted by MM-GBSA approach agrees with that determined by the experimental values. In addition, inhibitor-residue interactions were computed by using residue-based free-energy decomposition method and the results suggest that residue His42 produces the CH-H interactions, residues Asn100, Ile53 and Val49 produce the CH-$\pi$ interactions with three inhibitors and Tyr106, Phe45 and Phe44 generate the π-π interactions with inhibitors. Notably, the residue Asn140 forms hydrogen bonding interactions with three inhibitors. This research is expected to provide useful molecular basis and dynamics information at atomic levels for the design of potent inhibitors inhibiting the activity of BRD9.

KEYWORDS:

• Bromodomain-containing protein 9
• binding free energy
• molecular dynamics
• principal component analysis
• MM-GBSA method

Acknowledgements

This work is supported by the National Natural Science Foundation (No. 11504206) and Science Foundation of Shandong Jiaotong University (No. Z201703 and Z201202). The authors sincerely thank Prof. Jianzhong Chen (School of Science, Shandong Jiaotong University, Jinan 250357, China) for useful discussions and invaluable comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation on China [11504206] and Science Foundation of Shandong Jiaotong University [Z201703; Z201202].