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Identification of novel VP35 inhibitors: Virtual screening driven new scaffolds - 03/01/17

Doi : 10.1016/j.biopha.2016.09.034 
Ji-Xia Ren a, b, 1, Rui-Tao Zhang c, 1, Hui Zhang d, Xue-Song Cao a, Li-Ke Liu a, Yong Xie b,
a College of Life Science, Liaocheng University, Liaocheng 252059, People’s Republic of China 
b Institute of Medicinal Plant Development, Chinese Academy of Medical Science & Peking Union Medical college, 151 Malianwa North Road, Haidian District, Beijing 100193, People’s Republic of China 
c Black Donkey Research Institute, Dongeejiao Company Limited, Liaocheng 252000, Shandong, People’s Republic of China 
d College of Life Science, Northwest Normal University, Lanzhou 730070, Gansu, People’s Republic of China 

Corresponding author.

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Graphical abstract

A combined virtual screening method which involves the pharmacophore model, the 3D QSAR model and docking study was applied for identification of novel VP35 inhibitors from a large chemical database including 105,145,5 compounds, finally, seven potential active inhibitors with novel scaffolds were selected.




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Highlights

Two pharmacophore models were built, one was used for alignment of VP35 inhibitors, the other was applied for virtual screening.
3D QSAR model of 141 VP35 inhibitors was built, which gave good predictive ability.
A combined virtual screening method was employed for identification of novel VP35 inhibitors.
Seven hit compounds with novel scaffolds were selected for further study.

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Abstract

Ebola virus is a single-stranded, negative-sense RNA virus that causes acute and serious life-threatening illness. In recent years the Ebola virus has spread through several countries in Africa, highlighting the need to develop new treatments for this disease and boosting a new research effort on this subject. However, so far there is no valid treatment for disease created by this pathogen. The Ebola virus Viral Protein 35 (VP35) is a multifunctional protein which is critical for virus replication and infection, and it is considered as a future target for drug development. In this study, we collected 144 VP35 inhibitors which shared the same core scaffold, and a common feature pharmacophore model HypoA was built based on inhibitor-receptor complexes. All 141 compounds were aligned based on the common feature pharmacophore model HypoA (three compounds could not map onto HypoA). The pharmacophore model HypoA was further optimized according to the actual interactions between inhibitors and VP35 protein, resulting in a new pharmacophore model HypoB which was applied for virtual screening. A 3D QSAR model was established by applying the 141 aligned compounds. For the training set, the 3D QSAR model gave a correlation coefficient r2 of 0.897, for the test set, the correlation coefficient r2 was 0.757. Then a virtual screening was carried out, which comprehensively employing the common feature pharmacophore model, 3D QSAR model and docking study, their combination in a hybrid protocol could help to mutually compensate for their limitations and capitalized on their mutual strengths. After the above three virtual screening methods orderly filtering, seven potential inhibitors with novel scaffolds were identified as new VP35 inhibitors. The mapping results of hit compounds onto pharmacophore model and 3D QSAR model, and the molecular interactions of the potential inhibitors with the active site residues have been discussed in detail.

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Keywords : Ebola virus, Viral Protein 35, Pharmacophore, 3D QSAR, Docking study


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Vol 84

P. 199-207 - décembre 2016 Retour au numéro
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