References
If you use any of our tools in the PROTEAN-CR, please cite the tools as shown:
APE-Gen2.0
R. Fasoulis, M. M. Rigo, G. Lizée, D. A. Antunes, and L. E. Kavraki, “APE-Gen2.0: Expanding Rapid Class I Peptide-Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide Geometries,” Journal of Chemical Information and Modeling, vol. 64, no. 5, pp. 1730–1750, Mar. 2024.
J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations,” Molecules, vol. 24, no. 5, p. 881, 2019. PMID: 30832312, PMCID: PMC6429480
3pHLA
A. Conev, D. Devaurs, M. M. Rigo, D. A. Antunes, and L. E. Kavraki, “3pHLA-score improves structure-based peptide-HLA binding affinity prediction,” Scientific Reports, vol. 12, no. 1, Jun. 2022.
HLA-Arena
D. A. Antunes, J. R. Abella, S. Hall-Swan, D. Devaurs, A. Conev, M. Moll, G. Lizée, and L. E. Kavraki, “HLA-Arena: a customizable environment for the structural modeling and analysis of peptide-HLA complexes for cancer immunotherapy,” JCO Clinical Cancer Informatics, vol. 4, pp. 623–636, Jul. 2020. PMID: 32667823, PMCID: 7397777
PepSim
S. Hall-Swan, J. Slone, M. M. Rigo, D. A. Antunes, G. Lizée, and L. E. Kavraki, “PepSim: T-cell cross-reactivity prediction via comparison of peptide sequence and peptide-HLA structure,” Frontiers in Immunology, vol. 14, 2023.
EnGens
A. Conev, M. M. Rigo, D. Devaurs, A. F. Fonseca, H. Kalavadwala, M. V. de Freitas, C. Clementi, G. Zanatta, D. A. Antunes, and L. E. Kavraki, “EnGens: a computational framework for generation and analysis of representative protein conformational ensembles,” Briefings in Bioinformatics, p. bbad242, Jul. 2023.
DINC-Ensemble
D. Devaurs, D. A. Antunes, S. Hall-Swan, N. Mitchell, M. Moll, G. Lizée, and L. E. Kavraki, “Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins”, BMC Molecular and Cell Biology, vol. 20, no. 1, p. 42, 2019.
D. A. Antunes, M. Moll, D. Devaurs, K. R. Jackson, G. Lizée, and L. E. Kavraki, “DINC 2.0: a new protein-peptide docking webserver using an incremental approach”, Cancer Research, vol. 77, no. 21, pp. e55–57, 2017.
A. Dhanik, J. McMurray, and L. E. Kavraki, “DINC: A new AutoDock-based protocol for docking large ligands,” BMC Structural Biology, vol. 13, no. Suppl 1, p. S11, 2013.
D. A. Antunes, D. Devaurs, and L. E. Kavraki, “Understanding the challenges of protein flexibility in drug design,” Expert Opinion on Drug Discovery, vol. 10, no. 12, pp. 1301–1313, 2015.
DINC-Covid
S. Hall-Swan, D. Devaurs, M. M. Rigo, D. A. Antunes, L. E. Kavraki, and G. Zanatta, “DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins,” Computers in Biology and Medicine, vol. 139, p. 104943, 2021.
D. A. Antunes, M. Moll, D. Devaurs, K. R. Jackson, G. Lizée, and L. E. Kavraki, “DINC 2.0: a new protein-peptide docking webserver using an incremental approach”, Cancer Research, vol. 77, no. 21, pp. e55–57, 2017.
D. A. Antunes, D. Devaurs, and L. E. Kavraki, “Understanding the challenges of protein flexibility in drug design,” Expert Opinion on Drug Discovery, vol. 10, no. 12, pp. 1301–1313, 2015.