DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

2021 ◽  
Author(s):  
Rishal Aggarwal ◽  
Akash Gupta ◽  
Vineeth Chelur ◽  
C. V. Jawahar ◽  
U. Deva Priyakumar
Keyword(s):  
Neural Networks ◽  
Ligand Binding ◽  
Binding Site ◽  
Convolutional Neural Networks ◽  
Ligand Binding Site

scholarly journals DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

2021 ◽  
Author(s):  
Rishal Aggarwal ◽  
Akash Gupta ◽  
Vineeth Chelur ◽  
C. V. Jawahar ◽  
U. Deva Priyakumar
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Ligand Binding ◽  
Binding Site ◽  
Convolutional Neural Networks ◽  
Binding Sites ◽  
Protein Structures ◽  
3D Structure ◽  
Ligand Binding Site ◽  
Structure Based Drug Design

<div> A structure-based drug design pipeline involves the development of potential drug molecules or ligands that form stable complexes with a given receptor at its binding site. A prerequisite to this is finding druggable and functionally relevant binding sites on the 3D structure of the protein. Although several methods for detecting binding sites have been developed beforehand, a majority of them surprisingly fail in the identification and ranking of binding sites accurately. The rapid adoption and success of deep learning algorithms in various sections of structural biology beckons the usage of such algorithms for accurate binding site detection. As a combination of geometry based software and deep learning, we report a novel framework, DeepPocket that utilises 3D convolutional neural networks for the rescoring of pockets identified by Fpocket and further segments these identified cavities on the protein surface. Apart from this, we also propose another dataset SC6K containing protein structures submitted in the Protein Data Bank (PDB) from January 2018 till February 2020 for ligand binding site (LBS) detection. DeepPocket's results on various binding site datasets and SC6K highlights its better performance over current state-of-the-art methods and good generalization ability over novel structures. </div><div><br></div>

scholarly journals DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

2021 ◽  
Author(s):  
Rishal Aggarwal ◽  
Akash Gupta ◽  
Vineeth Chelur ◽  
C. V. Jawahar ◽  
U. Deva Priyakumar
Keyword(s):  
Neural Networks ◽  
Ligand Binding ◽  
Binding Site ◽  
Convolutional Neural Networks ◽  
Ligand Binding Site

scholarly journals DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

2021 ◽  
Author(s):  
Rishal Aggarwal ◽  
Akash Gupta ◽  
Vineeth Chelur ◽  
C. V. Jawahar ◽  
U. Deva Priyakumar
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Ligand Binding ◽  
Binding Site ◽  
Convolutional Neural Networks ◽  
Binding Sites ◽  
Protein Structures ◽  
3D Structure ◽  
Ligand Binding Site ◽  
Structure Based Drug Design

<div> A structure-based drug design pipeline involves the development of potential drug molecules or ligands that form stable complexes with a given receptor at its binding site. A prerequisite to this is finding druggable and functionally relevant binding sites on the 3D structure of the protein. Although several methods for detecting binding sites have been developed beforehand, a majority of them surprisingly fail in the identification and ranking of binding sites accurately. The rapid adoption and success of deep learning algorithms in various sections of structural biology beckons the usage of such algorithms for accurate binding site detection. As a combination of geometry based software and deep learning, we report a novel framework, DeepPocket that utilises 3D convolutional neural networks for the rescoring of pockets identified by Fpocket and further segments these identified cavities on the protein surface. Apart from this, we also propose another dataset SC6K containing protein structures submitted in the Protein Data Bank (PDB) from January 2018 till February 2020 for ligand binding site (LBS) detection. DeepPocket's results on various binding site datasets and SC6K highlights its better performance over current state-of-the-art methods and good generalization ability over novel structures. </div><div><br></div>

Constraints of Opsin Structure on the Ligand-binding Site: Studies with Ring-fused Retinals¶

2002 ◽  
Vol 76 (6) ◽  
pp. 606 ◽  
Author(s):  
Takahiro Hirano ◽  
In Taek Lim ◽  
Don Moon Kim ◽  
Xiang-Guo Zheng ◽  
Kazuo Yoshihara ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Binding Site ◽  
Ligand Binding Site

Capturing of the free cysteine residue in the ligand-binding site by affinity labeling of the ORL1 nociceptin receptor

2011 ◽  
Vol 19 (24) ◽  
pp. 7597-7602 ◽  
Author(s):  
Ayami Matsushima ◽  
Hirokazu Nishimura ◽  
Shogo Inamine ◽  
Shiho Uemura ◽  
Yasuyuki Shimohigashi
Keyword(s):  
Ligand Binding ◽  
Binding Site ◽  
Cysteine Residue ◽  
Affinity Labeling ◽  
Ligand Binding Site ◽  
Nociceptin Receptor

A Monoclonal Antibody against the Ligand Binding Site of the Receptor for Mouse Interferon-γ

1989 ◽  
Vol 9 (5) ◽  
pp. 551-562 ◽  
Author(s):  
MITALI BASU ◽  
JUDITH L. PACE ◽  
DAVID M. PINSON ◽  
STEPHEN W. RUSSELL
Keyword(s):  
Monoclonal Antibody ◽  
Ligand Binding ◽  
Binding Site ◽  
Interferon Γ ◽  
Ligand Binding Site
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