Your browser doesn't support javascript.
loading
Kartograf: A Geometrically Accurate Atom Mapper for Hybrid-Topology Relative Free Energy Calculations.
Ries, Benjamin; Alibay, Irfan; Swenson, David W H; Baumann, Hannah M; Henry, Michael M; Eastwood, James R B; Gowers, Richard J.
Affiliation
  • Ries B; Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co KG, Birkendorfer Str 65, 88397 Biberach an der Riss, Germany.
  • Alibay I; Open Free Energy, Open Molecular Software Foundation, Davis, 95616 California, United States.
  • Swenson DWH; Open Free Energy, Open Molecular Software Foundation, Davis, 95616 California, United States.
  • Baumann HM; Open Free Energy, Open Molecular Software Foundation, Davis, 95616 California, United States.
  • Henry MM; Open Free Energy, Open Molecular Software Foundation, Davis, 95616 California, United States.
  • Eastwood JRB; Open Free Energy, Open Molecular Software Foundation, Davis, 95616 California, United States.
  • Gowers RJ; Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, 1275 New York, United States.
J Chem Theory Comput ; 20(5): 1862-1877, 2024 Mar 12.
Article in En | MEDLINE | ID: mdl-38330251
ABSTRACT
Relative binding free energy (RBFE) calculations have emerged as a powerful tool that supports ligand optimization in drug discovery. Despite many successes, the use of RBFEs can often be limited by automation problems, in particular, the setup of such calculations. Atom mapping algorithms are an essential component in setting up automatic large-scale hybrid-topology RBFE calculation campaigns. Traditional algorithms typically employ a 2D subgraph isomorphism solver (SIS) in order to estimate the maximum common substructure. SIS-based approaches can be limited by time-intensive operations and issues with capturing geometry-linked chemical properties, potentially leading to suboptimal solutions. To overcome these limitations, we have developed Kartograf, a geometric-graph-based algorithm that uses primarily the 3D coordinates of atoms to find a mapping between two ligands. In free energy approaches, the ligand conformations are usually derived from docking or other previous modeling approaches, giving the coordinates a certain importance. By considering the spatial relationships between atoms related to the molecule coordinates, our algorithm bypasses the computationally complex subgraph matching of SIS-based approaches and reduces the problem to a much simpler bipartite graph matching problem. Moreover, Kartograf effectively circumvents typical mapping issues induced by molecule symmetry and stereoisomerism, making it a more robust approach for atom mapping from a geometric perspective. To validate our method, we calculated mappings with our novel approach using a diverse set of small molecules and used the mappings in relative hydration and binding free energy calculations. The comparison with two SIS-based algorithms showed that Kartograf offers a fast alternative approach. The code for Kartograf is freely available on GitHub (https//github.com/OpenFreeEnergy/kartograf). While developed for the OpenFE ecosystem, Kartograf can also be utilized as a standalone Python package.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Chem Theory Comput Year: 2024 Document type: Article Affiliation country: Germany Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Chem Theory Comput Year: 2024 Document type: Article Affiliation country: Germany Country of publication: United States