Ligand-based pharmacophore modeling and QSAR approach to identify potential dengue protease inhibitors

Frontiers in Molecular Biosciences

Molecular Biosciences

Amutha Ramaswamy¹  Mahesh Samantaray¹  Swati Krishna²  Prithvi S. Prabhu²  Anushka A. Poola²  T. P. Krishna Murthy²  Manikanta Murahari³ 

[1] Department of Bioinformatics, Pondicherry University, Pondicherry, India;Department of Biotechnology, M. S. Ramaiah Institute of Technology, Bengaluru, Karnataka, India;Department of Pharmacy, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India;

关键词: Dengue;    QSAR;    pharmacophore modeling;    docking;    molecular dynamics;   

DOI  :  10.3389/fmolb.2023.1106128

 received in 2022-11-26, accepted in 2023-02-07,  发布年份 2023

来源: Frontiers

【 摘 要 】

The viral disease dengue is transmitted by the Aedes mosquito and is commonly seen to occur in the tropical and subtropical regions of the world. It is a growing public health concern. To date, other than supportive treatments, there are no specific antiviral treatments to combat the infection. Therefore, finding potential compounds that have antiviral activity against the dengue virus is essential. The NS2B-NS3 dengue protease plays a vital role in the replication and viral assembly. If the functioning of this protease were to be obstructed then viral replication would be halted. As a result, this NS2B-NS3 proves to be a promising target in the process of anti-viral drug design. Through this study, we aim to provide suggestions for compounds that may serve as potent inhibitors of the dengue NS2B-NS3 protein. Here, a ligand-based pharmacophore model was generated and the ZINC database was screened through ZINCPharmer to identify molecules with similar features. 2D QSAR model was developed and validated using reported 4-Benzyloxy Phenyl Glycine derivatives and was utilized to predict the IC50 values of unknown compounds. Further, the study is extended to molecular docking to investigate interactions at the active pocket of the target protein. ZINC36596404 and ZINC22973642 showed a predicted pIC50 of 6.477 and 7.872, respectively. They also showed excellent binding with NS3 protease as is evident from their binding energy of −8.3and −8.1 kcal/mol, respectively. ADMET predictionsofcompounds have shown high drug-likeness. Finally, the molecular dynamic simulations integrated with MM-PBSA binding energy calculations confirmedboth identified ZINC compounds as potential hit moleculeswith good stability.

【 授权许可】

Unknown   
Copyright © 2023 Poola, Prabhu, Murthy, Murahari, Krishna, Samantaray and Ramaswamy.

【 图 表 】

FPHAR_fphar-2023-1146668_wc_tfx2.tif

FMOLB_fmolb-2023-1106128_wc_tfx15.tif

FMOLB_fmolb-2023-1106128_wc_tfx14.tif

FMOLB_fmolb-2023-1106128_wc_tfx13.tif

FMOLB_fmolb-2023-1106128_wc_tfx12.tif

FEART_feart-2023-1057982_wc_tfx1.tif

FMOLB_fmolb-2023-1106128_wc_tfx10.tif

FMOLB_fmolb-2023-1106128_wc_tfx9.tif

FMOLB_fmolb-2023-1106128_wc_tfx8.tif

FMOLB_fmolb-2023-1106128_wc_tfx7.tif

FEART_feart-2023-1169258_wc_tfx18.tif

FMOLB_fmolb-2023-1106128_wc_tfx5.tif

FPHAR_fphar-2023-1202128_wc_tfx5.tif

FMOLB_fmolb-2023-1106128_wc_tfx3.tif

FPHAR_fphar-2023-1202128_wc_tfx2.tif

FMOLB_fmolb-2023-1106128_wc_tfx1.tif