SPSignal: a web tool for structure-assisted prediction of nuclear localization and nuclear export signals in proteins
Engler, Camila (Centre de Recerca en Agrigenòmica)
Abriata, Luciano A. (École Polytechnique Fédérale de Lausanne)
Bologna, Nicolás (Centre de Recerca en Agrigenòmica)

Date:	2026
Abstract:	Nuclear localization signals (NLSs) and nuclear export signals (NESs) mediate nucleocytoplasmic transport of proteins through the nuclear pore complex and are essential determinants of protein function. However, their short and degenerate sequence patterns frequently lead to high false-positive rates in sequence-based prediction methods, as similar motifs occur widely in proteins without mediating nuclear transport. Here, we present SPSignal, a webserver for improved identification of NLS and NES motifs by integrating sequence-based predictions with structural features. SPSignal combines curated datasets of experimentally validated signals with analyses of solvent accessibility, intrinsic disorder, and structural context derived from experimental or predicted protein structures. Using these features, interpretable machine-learning models based on the RuleFit algorithm prioritize candidate motifs that are structurally exposed and therefore more likely to be functional. The web server integrates sequence predictors with structure-informed analyses in a unified workflow that accepts protein sequences or structures as input and provides interactive visualization of predicted signals within their three-dimensional context. SPSignal assigns confidence scores to candidate motifs and allows users to explore their spatial distribution along protein sequences and structures. Application to proteins with validated localization signals shows that SPSignal improves prediction accuracy by reducing false positives without compromising sensitivity. SPSignal is available at https://sps. cragenomica. es .
Grants:	European Commission 101081581 Agencia Estatal de Investigación CEX2019-000902-S Agencia Estatal de Investigación PID2022-143130NB-I00 Agencia Estatal de Investigación CNS2022-136187
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Published in:	Nucleic acids research, May 2026, art. gkag421, ISSN 0305-1048

DOI: 10.1093/nar/gkag421

10 p, 1.7 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Experimental sciences > CRAG (Centre for Research in Agricultural Genomics)
Articles > Research articles
Articles > Published articles