scholarly journals Molecular Dynamics Simulations of Kir2.2 and Cholesterol Reveal State- and Concentration-Dependent Binding Sites

2019 ◽  
Vol 116 (3) ◽  
pp. 41a
Author(s):  
Nicolas Barbera ◽  
Manuela A. Ayee ◽  
Belinda S. Akpa ◽  
Irena Levitan
2020 ◽  
Vol 53 (3) ◽  
pp. 654-661 ◽  
Author(s):  
Antonija Kuzmanic ◽  
Gregory R. Bowman ◽  
Jordi Juarez-Jimenez ◽  
Julien Michel ◽  
Francesco L. Gervasio

Structure ◽  
2004 ◽  
Vol 12 (11) ◽  
pp. 1989-1999 ◽  
Author(s):  
Akshay Bhinge ◽  
Purbani Chakrabarti ◽  
Kavitha Uthanumallian ◽  
Kanika Bajaj ◽  
Kausik Chakraborty ◽  
...  

2021 ◽  
Author(s):  
Wanling Song ◽  
Robin A. Corey ◽  
Bertie Ansell ◽  
Keith Cassidy ◽  
Michael Horrell ◽  
...  

Lipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these protein-lipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements whilst bound from full dissociation events. In addition to the characterization of protein-lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation datasets of multiple species of membrane proteins.


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