Metal binding site alignment enables network-driven discovery of recurrent geometries across sequence-divergent proteins and drug off-targets.

Simensen V, Almaas E

DOI: 10.1371/journal.pcbi.1014636
Published: 2026 Aug
Container: PLoS computational biology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pcbi.1014636,
  title = {Metal binding site alignment enables network-driven discovery of recurrent geometries across sequence-divergent proteins and drug off-targets.},
  author = {Simensen V and Almaas E},
  year = {2026},
  journal = {PLoS computational biology},
  doi = {10.1371/journal.pcbi.1014636},
  url = {https://doi.org/10.1371/journal.pcbi.1014636}
}

RIS

TY  - JOUR
TI  - Metal binding site alignment enables network-driven discovery of recurrent geometries across sequence-divergent proteins and drug off-targets.
AU  - Simensen V
AU  - Almaas E
PY  - 2026
JO  - PLoS computational biology
DO  - 10.1371/journal.pcbi.1014636
UR  - https://doi.org/10.1371/journal.pcbi.1014636
ER  -

APA

V, S., & E, A. (2026). Metal binding site alignment enables network-driven discovery of recurrent geometries across sequence-divergent proteins and drug off-targets.. PLoS computational biology. https://doi.org/10.1371/journal.pcbi.1014636

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pubmed · retrieved 2026-09-25T22:14:01.999Z