Design of novel DABO derivatives as HIV-1 RT inhibitors using molecular docking, molecular dynamics simulations and ADMET properties

Abstract

HIV-1 reverse transcriptase is an important target for developing effective anti-HIV-1 inhibitors. Different types of small molecules have been designed based on this target, showing different levels of inhibitory activity against various types of HIV-1 strains. The relationship between structure and activity of DABO derivatives was investigated by means of 3D-QSAR molecular model, molecular docking, molecular dynamics and ADMET properties. The statistical results of molecular models show that the CoMFA and CoMSIA models have good internal stability (CoMFA: q² = 0.623, r² = 0.946; CoMSIA: q² = 0.668, r² = 0.983) and external prediction ability (CoMFA: r_pred² = 0.961; CoMSIA: r_pred² = 0.961). In addition, molecular docking has explored the mechanism of action between small molecules and receptor proteins, and the results show that hydrogen bonding between amino acid Lys101 and small molecules can improve the affinity of ligands to receptor binding. A total of 12 novel molecules were designed and their activities were predicted based on the 3D-QSAR model and molecular docking results. The results showed that the designed molecules had higher predictive activity. Subsequently, 100 ns MD simulation and binding free energy verified the stability of molecular docking results. Finally, the pharmacokinetic properties of the novel designed molecule were verified by using ADMET to predict its properties. These results can provide reference for the design and development of novel and effective HIV-1 RT inhibitors, and provide new ideas for the design of subsequent drugs.

Communicated by Ramaswamy H. Sarma

KEYWORDS:

• DABO derivative
• molecular docking
• molecular dynamics simulation
• ADMET
• MM/PBSA binding energy

Author contributions

Yanjun Zhang prepared the first draft of the manuscript. Lu Chen and Zhonghua Wang performed the simulation. Yiren Zhu, Huifang Jiang and Jie Xu analyzed data and Fei Xiong revised the manuscript and approved for publication.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the financial support of the National Natural Science Foundation of China (NO. 81172918, 51707122), Shanghai Municipal Education Commission (NO. SLG14033) and the open project program of Hubei Key Laboratory of Drug Synthesis and Optimization, Jing Chu University of Technology (NO. OPP2014ZD01).