NDLI: Revealing the binding mode between respiratory syncytial virus fusion protein and benzimidazole-based inhibitors.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Ji, Dingjue Ye, Wei Chen, HaiFeng
Description	Country affiliation: China Author Affiliation: Ji D ( State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, College of Life Sciences and Biotechnology, Shanghai Jiaotong University, 800 Dongchuan Road, Shanghai, 200240, China. haifengchen@sjtu.edu.cn.)
Abstract	Human respiratory syncytial virus (HRSV) is a major respiratory pathogen in newborn infants and young children and can also be a threat to some elderly and high-risk adults with chronic pulmonary disease and the severely immunocompromised. The RSV fusion (RSVF) protein has been an attractive target for vaccine and drug development. Experimental results indicate a series of benzimidazole-based inhibitors which target RSVF protein to inhibit the viral entry of RSV. To reveal the binding mode between these inhibitors and RSVF protein, molecular docking and molecular dynamics simulations were used to investigate the interactions between the inhibitors and the core domain of RSVF protein. MD results suggest that the active molecules have stronger π-π stacking, cation-π, and other interactions than less active inhibitors. The binding free energy between the active inhibitor and RSVF protein is also found to be significantly lower than that of the less active one using MM/GBSA. Then, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods were used to construct three dimensional quantitative structure-activity (3D-QSAR) models. The cross-validated q(2) values are found to be 0.821 and 0.795 for CoMFA and CoMSIA, respectively. And the non-cross-validated r(2) values are 0.973 and 0.961. Ninety-two test set compounds validated these models. The results suggest that these models are robust with good prediction abilities. Furthermore, these models reveal possible methods to improve the bioactivity of inhibitors.
File Format	HTM / HTML
ISSN	1742206X
Issue Number	7
Volume Number	11
e-ISSN	17422051
Journal	Molecular BioSystems
Language	English
Publisher	Royal Society of Chemistry
Publisher Date	2015-07-01
Publisher Place	Great Britain (UK)
Access Restriction	Subscribed
Subject Keyword	Discipline Molecular Biology Discipline Biochemistry Antiviral Agents Chemistry Benzimidazoles Respiratory Syncytial Viruses Viral Fusion Proteins Binding Sites Hydrogen Bonding Molecular Docking Simulation Molecular Dynamics Simulation Protein Binding Protein Structure, Secondary Quantitative Structure-activity Relationship Antagonists & Inhibitors Journal Article Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biotechnology

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