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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. (Publisher's Version)
In: Algorithms for Molecular Biology, 17, BioMed Central, ISSN 1748-7188,
DOI: 10.26083/tuprints-00021427,

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Item Type: Article
Origin: Secondary publication via sponsored Golden Open Access
Status: Publisher's Version
Title: Adding hydrogen atoms to molecular models via fragment superimposition
Language: English

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.

Journal or Publication Title: Algorithms for Molecular Biology
Volume of the journal: 17
Place of Publication: Darmstadt
Publisher: BioMed Central
Collation: 8 Seiten
Classification DDC: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie
Divisions: 10 Department of Biology > Computational Biology and Simulation
Date Deposited: 25 May 2022 12:27
Last Modified: 22 Aug 2022 08:34
DOI: 10.26083/tuprints-00021427
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-214279
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21427
PPN: 495025917
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