Zika virus envelope – heat shock protein A5 (GRP78) binding site prediction

2020 ◽  
pp. 1-13 ◽  
Author(s):  
Abdo A. Elfiky ◽  
Ibrahim M. Ibrahim
Keyword(s):  
Heat Shock ◽  
Heat Shock Protein ◽  
Binding Site ◽  
Zika Virus ◽  
Virus Envelope ◽  
Site Prediction ◽  
Binding Site Prediction

3D U-Net: A voxel-based method in binding site prediction of protein structure

2021 ◽  
Vol 19 (02) ◽  
pp. 2150006
Author(s):  
Fatemeh Nazem ◽  
Fahimeh Ghasemi ◽  
Afshin Fassihi ◽  
Alireza Mehri Dehnavi
Keyword(s):  
Drug Design ◽  
Binding Site ◽  
Binding Sites ◽  
Semantic Segmentation ◽  
Structure Based Drug Design ◽  
Site Prediction ◽  
Binding Site Prediction ◽  
Novel Proteins ◽  
Proposed Model ◽  
Deep Learning Model

Binding site prediction for new proteins is important in structure-based drug design. The identified binding sites may be helpful in the development of treatments for new viral outbreaks in the world when there is no information available about their pockets with COVID-19 being a case in point. Identification of the pockets using computational methods, as an alternative method, has recently attracted much interest. In this study, the binding site prediction is viewed as a semantic segmentation problem. An improved 3D version of the U-Net model based on the dice loss function is utilized to predict the binding sites accurately. The performance of the proposed model on the independent test datasets and SARS-COV-2 shows the segmentation model could predict the binding sites with a more accurate shape than the recently published deep learning model, i.e. DeepSite. Therefore, the model may help predict the binding sites of proteins and could be used in drug design for novel proteins.

Cavity/Binding Site Prediction Approaches and Their Applications

2020 ◽  
pp. 49-69
Author(s):  
Himanshu Avashthi ◽  
Ambuj Srivastava ◽  
Dev Bukhsh Singh
Keyword(s):  
Binding Site ◽  
Site Prediction ◽  
Binding Site Prediction
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