Sökning: WFRF:(Kamerlin S. C. Lynn)
> (2023) >
KIF-Key Interaction...
KIF-Key Interactions Finder : A program to identify the key molecular interactions that regulate protein conformational changes
-
- Crean, Rory M. (författare)
- Uppsala universitet,Biokemi
-
- Slusky, Joanna S. G. (författare)
- Univ Kansas, Ctr Computat Biol, Lawrence, KS 66047 USA.;Univ Kansas, Dept Mol Biosci, Lawrence, KS 66045 USA.
-
- Kasson, Peter M. (författare)
- Uppsala universitet,Molekylär biofysik,Univ Virginia, Dept Mol Physiol & Biomed Engn, Charlottesville, VA 22908 USA.
-
visa fler...
-
- Kamerlin, Shina C. Lynn, 1981- (författare)
- Uppsala universitet,Biokemi,Georgia Inst Technol, Sch Chem & Biochem, 901 Atlantic Dr NW, Atlanta, GA 30332 USA.
-
visa färre...
-
(creator_code:org_t)
- 2023-03-29
- 2023
- Engelska.
-
Ingår i: Journal of Chemical Physics. - : American Institute of Physics (AIP). - 0021-9606 .- 1089-7690. ; 158:14
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://uu.diva-port... (primary) (Raw object)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics.
Ämnesord
- NATURVETENSKAP -- Biologi -- Biokemi och molekylärbiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Biochemistry and Molecular Biology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas