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Adding hydrogen atoms to molecular models via fragment superimposition

Kunzmann, Patrick ; Anter, Jacob Marcel ; Hamacher, Kay (2022)
Adding hydrogen atoms to molecular models via fragment superimposition.
In: Algorithms for molecular biology : AMB, 17 (1)
doi: 10.1186/s13015-022-00215-x
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

BACKGROUND

Most experimentally determined structures of biomolecules lack annotated hydrogen positions due to their low electron density. However, thorough structure analysis and simulations require knowledge about the positions of hydrogen atoms. Existing methods for their prediction are either limited to a certain range of molecules or only work effectively on small compounds.

RESULTS

We present a novel algorithm that compiles fragments of molecules with known hydrogen atom positions into a library. Using this library the method is able to predict hydrogen positions for molecules with similar moieties. We show that the method is able to accurately assign hydrogen atoms to most organic compounds including biomacromolecules, if a sufficiently large library is used.

CONCLUSIONS

We bundled the algorithm into the open-source Python package and command line program Hydride. Since usually no additional parametrization is necessary for the problem at hand, the software works out-of-box for a wide range of molecular systems usually within a few seconds of computation time. Hence, we believe that Hydride could be a valuable tool for structural biologists and biophysicists alike.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Kunzmann, Patrick ; Anter, Jacob Marcel ; Hamacher, Kay
Art des Eintrags: Bibliographie
Titel: Adding hydrogen atoms to molecular models via fragment superimposition
Sprache: Englisch
Publikationsjahr: 29 März 2022
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Algorithms for molecular biology : AMB
Jahrgang/Volume einer Zeitschrift: 17
(Heft-)Nummer: 1
DOI: 10.1186/s13015-022-00215-x
Kurzbeschreibung (Abstract):

BACKGROUND

Most experimentally determined structures of biomolecules lack annotated hydrogen positions due to their low electron density. However, thorough structure analysis and simulations require knowledge about the positions of hydrogen atoms. Existing methods for their prediction are either limited to a certain range of molecules or only work effectively on small compounds.

RESULTS

We present a novel algorithm that compiles fragments of molecules with known hydrogen atom positions into a library. Using this library the method is able to predict hydrogen positions for molecules with similar moieties. We show that the method is able to accurately assign hydrogen atoms to most organic compounds including biomacromolecules, if a sufficiently large library is used.

CONCLUSIONS

We bundled the algorithm into the open-source Python package and command line program Hydride. Since usually no additional parametrization is necessary for the problem at hand, the software works out-of-box for a wide range of molecular systems usually within a few seconds of computation time. Hence, we believe that Hydride could be a valuable tool for structural biologists and biophysicists alike.

ID-Nummer: pmid:35351165
Fachbereich(e)/-gebiet(e): 10 Fachbereich Biologie
10 Fachbereich Biologie > Computational Biology and Simulation
Hinterlegungsdatum: 05 Apr 2022 06:56
Letzte Änderung: 27 Mai 2022 06:35
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