I am trying to explain the allosteric pathway using molecular dynamics. I have tried to do a contact, correlation and hydrogen bond analysis to determine that path (using holo and apo forms). Is there any software that can help suggest an allosteric path?
Thank you Suji George . Unfortunately, the program you mention is old and its installation is difficult in recent operating systems. I found the author is working on a new version. When it’s ready, I’ll try it.
Thanks Angeles, but it seems it's not the right tool for this problem.
You can read the book chapter
Detecting Allosteric Networks Using Molecular Dynamics Simulation
S.
It is good you have done an appropriate analysis. In this chapter, they specifically not mentioned any particular software but they giving an overview of the data analysis and help the way of Allosteric regulation.
Hi, RIN (residue interaction network) types analysis, network topology analysis (betweenness centrality etc) can be performed. If you are fine with R, bio3D, IGraphs are there to help you. MD-TASK (PMID:28575169) is also a good option.
I hope these will be helpful.
Good luck
Aashish Bhatt and Ayaz Anwar thank you both. I'll look at your recommendations.
Hi,
You can try the Generalized correlation-based dynamical network analysis. Follow the paper: Article Generalized correlation-based dynamical network analysis: A ...
They have a Jupyter Notebook with everything explained. It is straightforward.
I hope it helps.
Best,
Pablo
Do you have any idea on the time length your allosteric action happens?
This may not be the best current approach, but it worked for us in combining SAXS and molecular dynamics to examine allostery for AIF - see open access paper - Defining NADH-Driven Allostery Regulating Apoptosis-Inducing Factor. Brosey CA, Ho C, Long WZ, Singh S, Burnett K, Hura GL, Nix JC, Bowman GR, Ellenberger T, Tainer JA. Structure. 2016 Dec 6;24(12):2067-2079. doi: 10.1016/j.str.2016.09.012.
RMSD calculations were generated with the RMSDTT plugin (Luis Gracia, https://github.com/luisico/rmsdtt) of the VMD molecular visualization program.
Electrostatic interactions between residues were quantified based on occupancy using the HBonds plugin (JC Gumbart and Dong Luo http://www.ks.uiuc.edu/Research/vmd/plugins/hbonds/) and Salt Bridges (Leonardo Trabuco and Elizabeth Villa http://www.ks.uiuc.edu/Research/vmd/plugins/saltbr/) analysis modules within VMD. Communication between active site residues and the rest of AIF was quantified using Mutual Information (MI) between backbone and side chain dihedral angles. MI measures the dependence between two variables, X and Y, by quantifying probability of knowing the state of X given the state of Y. For each simulation, angles for each residue were extracted using the MDTraj library (Version 1.5.1) (McGibbon et al., 2015).
Ramin Ekhteiari Salmas If you mean total action time, we have no way of measuring it. If you mean how long we observe allosteric effects, it is almost immediately (when compared with the basal structure), since we start from a crystallized structure with inhibitor.
John Tainer It is a very interesting and very useful article. Thank you.
You can use this approach if looking for an adventure: Article Machine Learning Prediction of Allosteric Drug Activity from...
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