2023

Roca-Martínez, J., Dhondge, H. , Sattler, M. , Vranken, W.F. Deciphering the RRM-RNA recognition code: A computational analysis. PLoS Comput Biol 19(1): e1010859. DOI: 10.1371/journal.pcbi.1010859

  • RRM
  • RNA binding
  • Predictor
  • Protein alignment

2022

Roca-Martínez, J., Lazar, T., Gavaldá-García, J., Bickel, D., Pancsa, R., Dixit, B., Tzavella, K., Ramasamy, P., Sanchez-Fornaris, M., Grau, I. Vranken, W.F. Challenges in describing the conformation and dynamics of proteins with ambiguous behavior. Front. Mol. Biosci. 2022 Aug 3;(9).
DOI: 10.3389/fmolb.2022.959956

  • Protein dynamics and conformation
  • Sequence-based prediction
  • Biophysical characteristics
  • Post-translational modification (PTM)
  • Deleterious mutation
  • Folding-upon-binding
  • Fold switching

Ciani, C., Pérez-Ràfols, A., Bonomo, I., Micaelli, M., Esposito, A., Zucal, C., Belli, R., D’Agostino, V.G., Bianconi, I., Calderone, V., Cerofolini, L., Massidda, O., Whalen, M.B., Fragai, M., Provenzani, A. Identification and Characterization of an RRM-Containing, RNA Binding Protein in Acinetobacter baumannii. Biomolecules 2022, 12, 922. DOI: https://doi.org/10.3390/biom12070922

  • Acinetobacter baumannii
  • RNA recognition motif
  • ELAVL1

Dolcemascolo, R., Goiriz, L., Montagud-Martínez, R., Rodrigo, G. Gene regulation by a protein translation factor at the single-cell level. PLOS Computational Biology, 18(5): e1010087. DOI: 10.1371/journal.pcbi.1010087

  • Protein translation
  • Gene expression
  • Gene regulation
  • Transcriptional control
  • Post-transcriptional gene regulation
  • Protein synthesis
  • Mathematical models
  • mRNA

2021

Kagami, L.P., Orlando, G., Raimondi, D., Ancien, F., Dixit, B., Gavaldá-García, J., Ramasamy, P., Roca-Martínez, J., Tzavella, K., Vranken, W.F. b2bTools: online predictions for protein biophysical features and their conservation. Nucleic Acids Res., gkab425 (2021). DOI: 10.1093/nar/gkab425

  • Protein
  • Sequence based predictions
  • Biophysics
  • Machine learning
  • Conservation

Kagami, L., Roca-Martínez, J., Gavaldá-García, J., Ramasamy, P., Feenstra, K.A., Vranken, W.F. Online biophysical predictions for SARS-CoV-2 proteins. BMC Mol and Cell Biol 22, 23 (2021). DOI: 10.1186/s12860-021-00362-w

  • Proteins
  • Single sequence based predictions
  • Biophysical features
  • SARS-CoV-2
  • COVID-19