Development of a generative adversarial neural network for identification of potential HIV-1 inhibitors by deep learning methods

Development of a generative adversarial neural network for identification of potential HIV-1 inhibitors by deep learning methods

A generative adversarial autoencoder for the rational design of potential HIV-1 entry inhibitors able to block the region of the viral envelope protein gp120 critical for the virus binding to cellular receptor CD4 was developed using deep learning methods. The research were carried out to create the...

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Bibliographic Details
Main Authors: G. I. Nikolaev, N. A. Shuldov, A. I. Anishenko, A. V. Tuzikov, A. M. Andrianov
Format: Article
Language:Russian
Published: National Academy of Sciences of Belarus, the United Institute of Informatics Problems 2020-03-01
Series:Informatika
Subjects:
deep learning methods
a generative adversarial neural network
gp120 protein
hiv-1 entry inhibitors
molecular modeling
Online Access:https://inf.grid.by/jour/article/view/1045
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