Sketching microprotein portraits
Abstract
The illustrations of intricate molecular machineries inside cells created by David Goodsell continue to inspire the scientific community. Here, we aim to extend his artworks to include microproteins, a newly recognized class of small proteins with less than 100 amino acids, encoded by small open reading frames. Given the rapidly expanding number of identified microproteins, potentially exceeding the number of canonical proteins, we highlight, in this perspective article, diverse computational approaches to classify these proteins. By predicting localization, assessing structural homology, and modeling environments and dynamics of microproteins, these methods could provide clues about the subcellular localization of these microproteins and their structural domain homology, guiding further investigation into their biological functions in living systems.
BibTeX
@article{diaz2026sketching,
title = {{Sketching microprotein portraits}},
author = {Gabriel Diaz and Philippe Valenti and Marc Gueroult and Simon Marques-Prieto and Kenza Benachenhou and Jennifer Zanet and Matthieu Chavent},
journal = {Protein Science},
year = {2026},
month = may,
doi = {10.1002/pro.70636},
url = {https://hal.science/hal-05782474v1},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Sketching microprotein portraits
AU - Gabriel Diaz
AU - Philippe Valenti
AU - Marc Gueroult
AU - Simon Marques-Prieto
AU - Kenza Benachenhou
AU - Jennifer Zanet
AU - Matthieu Chavent
PY - 2026
DA - 2026/05/20
JO - Protein Science
DO - 10.1002/pro.70636
UR - https://hal.science/hal-05782474v1
AB - The illustrations of intricate molecular machineries inside cells created by David Goodsell continue to inspire the scientific community. Here, we aim to extend his artworks to include microproteins, a newly recognized class of small proteins with less than 100 amino acids, encoded by small open reading frames. Given the rapidly expanding number of identified microproteins, potentially exceeding the number of canonical proteins, we highlight, in this perspective article, diverse computational approaches to classify these proteins. By predicting localization, assessing structural homology, and modeling environments and dynamics of microproteins, these methods could provide clues about the subcellular localization of these microproteins and their structural domain homology, guiding further investigation into their biological functions in living systems.
SN - 0961-8368
SN - 1469-896X
ER -