AllosterIt is an academic organisation for the computational study of allostery in proteins. We simulate proteins and explore methods to extract allosteric of structural couplings and signal transmissions. In particular, information-theoretic methods are evaluated, as they provide non-parametric and model-free means to extract signals from complex systems.
Our code is available on the GitHub site of the organisation: AllosterIt on GitHub
Below is a list of our previous work in this field.
For further information, please contact us via email: allosterit@jkleinj.eu
O.G. Carmona, J. Kleinjung, D. Anastasiou, C. Oostenbrink, F. Fraternali
AllohubPy: Detecting allosteric signals through an information-theoretic approach.
Journal of Molecular Biology (2025) 168969.
doi
J.A. Macpherson, A. Theisen, L. Masino, L. Fets, P.C. Driscoll, V. Encheva, A.P. Snijders, S.R. Martin,
J. Kleinjung, P. E. Barran, F. Fraternali, D. Anastasiou
Functional cross-talk between allosteric effects of activating and inhibiting ligands underlies PKM2 regulation.
eLife 8 (2019) e45068.
doi
A. Pandini, A. Fornili, F. Fraternali, J. Kleinjung
GSATools: analysis of allosteric communication and functional local motions using a structural alphabet.
Bioinformatics 29 (2013) 2053-2055.
doi
A. Pandini, A. Fornili, F. Fraternali, J. Kleinjung
Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics.
FASEB Journal 26 (2001) 868-881.
doi
A. Pandini, A. Fornili, J. Kleinjung
Structural alphabets derived from attractors in conformational space.
BMC Bioinformatics 11 (2010) 97.
doi