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Konnektor: A Framework for Using Graph Theory to Plan Networks for Free Energy Calculations.

Authors :
Ries B
Gowers RJ
Baumann HM
Swenson DWH
Henry MM
Eastwood JRB
Alibay I
Mobley D
Source :
Journal of chemical information and modeling [J Chem Inf Model] 2024 Nov 25; Vol. 64 (22), pp. 8396-8403. Date of Electronic Publication: 2024 Nov 05.
Publication Year :
2024

Abstract

Alchemical free energy campaigns can be planned using graph theory by building networks that contain nodes representing molecules that are connected by possible transformations as edges. We introduce Konnektor, an open-source Python package, for systematically planning, modifying, and analyzing free energy calculation networks. Konnektor is designed to aid in the drug discovery process by enabling users to easily setup free energy campaigns using complex graph manipulation methods. The package contains functions for network operations including concatenation of networks, deletion of transformations, and clustering of molecules along with a framework for combining these tools with existing network generation algorithms to enable the development of more complex methods for network generation. A comparison of the various network layout features offered is carried out using toy data sets. Additionally, Konnektor contains visualization and analysis tools, making the investigation of network features much simpler. Besides the content of the package, the paper also offers application examples, demonstrating how Konnektor can be used and how the different networks perform from a graph theory perspective. Konnektor is freely available via GitHub at https://github.com/OpenFreeEnergy/konnektor under the permissive MIT License.

Details

Language :
English
ISSN :
1549-960X
Volume :
64
Issue :
22
Database :
MEDLINE
Journal :
Journal of chemical information and modeling
Publication Type :
Academic Journal
Accession number :
39501568
Full Text :
https://doi.org/10.1021/acs.jcim.4c01710