Brianda Lopez Santini
PhD candidateAcademic education
| Since Dec 2019 |
PhD candidate at Max Planck School Matter to Life
Research performed at Technical University of Munich, Supervisor Martin Zacharias |
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| Aug 2016 - Jun 2018 | Master of Science in Nanoscience, Center for Nanosciences and Nanotechnology, Universidad Nacional Autónoma de México (UNAM) |
| Aug 2011 - Jun 2016 | Bachelor of Engineering in Nanotechnology, Universidad Autónoma de Baja California (UABC) |
Research experience
| Since Dec 2019 | PhD Thesis: Molecular modelling of the structure, function, and dynamics of biomolecules for therapeutical applications, Physics Department, TUM |
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| Aug 2016 - Jun 2019 | Master Thesis: Single stranded DNA computational drug design for cancer therapy applications, CNyN, UNAM |
| Aug 2014 - Aug 2016 | Student Researcher: Computational Drug Discovery, CNyN, UNAM |
Publications
Abdel-Rahman, S., Santini, B.L., Calvo-Barreiro, L., Zacharias, M., and Gabr, M., Design of cyclic peptides as novel inhibitors of ICOS/ICOSL interaction, Bioorg Med Chem Lett 1:99:129599, 2024. https://doi.org/10.1016/j.bmcl.2024.129599
Santini, B.L., Zacharias, M., Rapid Rational Design of Cyclic Peptides Mimicking Protein–Protein Interfaces. In: Simonson, T. (eds) Computational Peptide Science. Methods in Molecular Biology, vol 2405. Humana, New York, NY, 2022. https://doi.org/10.1007/978-1-0716-1855-4_12
Santini, B.L. and Zacharias, M., Rapid in silico Design of Potential Cyclic Peptide Binders Targeting Protein-Protein Interfaces Front. Chem. 8: 573259, 2020. https://doi.org/10.3389/fchem.2020.573259
Santini, B.L., Zúñiga-Bustos M., Vidal-Limón A., Alderete J.B., Águila S., and Jiménez V.A., In Silico Design of Novel Mutant Anti-MUC1 Aptamers for Targeted Cancer Therapy J. Chem. Inf. Model., 2020. https://doi.org/10.1021/acs.jcim.9b00756
Vidal-Limón A., Tafoya P., Santini B.L., Contreras O. and Águila S., Electron transfer pathways analysis of oxygen tolerant [NiFe] -hydrogenases for hydrogen production: A quantum mechanics / molecular mechanics - statistical coupled analysis. International Journal of Hydrogen Energy, 2017. https://doi.org/10.1016/j.ijhydene.2017.07.019