scholarly journals Improving prediction of secondary structure, local backbone angles and solvent accessible surface area of proteins by iterative deep learning

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Rhys Heffernan ◽  
Kuldip Paliwal ◽  
James Lyons ◽  
Abdollah Dehzangi ◽  
Alok Sharma ◽  
...  
Keyword(s):  
Deep Learning ◽  
Secondary Structure ◽  
Surface Area ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Accessible Surface ◽  
Solvent Accessible Surface ◽  
Prediction Of Secondary Structure

scholarly journals Screening of druggable conformers of α-synuclein using molecular dynamics simulation

2020 ◽  
Vol 10 (3) ◽  
pp. 5338-5347
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Secondary Structure ◽  
Surface Area ◽  
Accessible Surface Area ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Binding Pockets ◽  
Accessible Surface ◽  
Solvent Accessible Surface

Intrinsically disordered proteins (IDPs) are becoming an engaging prospect for therapeutic intervention by small drug-like molecules. IDPs structural binding pockets and their flexibility exist as a challenging target for standard druggable approaches. Hence, in this study, we have performed and identified the most probable druggable conformers from molecular dynamics simulation on α-synuclein based on the structural parameters: radius of gyration (Rg), solvent accessible surface area (SASA) and the standard secondary structure content. We found the conformers showing lower solvent accessible surface area and higher secondary structure content of α-helical are defined to be suitable binding pockets for druggability.

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