Dr. Ana María Fernández Escamilla

Department: Instituto de Investigación, Desarrollo e Innovación en Biotecnología Sanitaria de Elche (IDiBE) /

Protein Architecture Group

Phone: +34 965 222 088

Email: ana.fernandeze@umh.es

Current Position: Associate  Professor, Biochemistry and Molecular Biology Department, Universidad Miguel Hernández.

Research Fields

  • Protein engineering. Combination of computational and experimental approaches. 

  • Protein-ligand binding interactions and protein-protein interaction. o Biochemical, biophysical and structural characterization of proteins. o Development of natural-molecule/peptides inhibitors against  Zika/Dengue virus.

  • New amyloids: exploitation in biomedicine, food security (food allergy) and sustainable agriculture. 

  • Bacterial biosensor development for detection of toxic and antimicrobial compounds. 

  • Characterization of the molecular mechanisms involved in microorganism-environment interaction. 

Representative Publications

  • Molina-Henares MA, Ramos-González MI, Daddaoua A, Fernández-Escamilla AM, Espinosa-Urgel M. FleQ of Pseudomonas putida KT2440 is a multimeric cyclic diguanylate binding protein that differentially regulates expression of biofilm matrix components. Res Microbiol. 2017 Jan;168(1):36-45. doi: 10.1016/j.resmic.2016.07.005. Epub 2016 Aug 5.

  • Espinosa-Urgel M, Serrano L, Ramos JL, Fernández-Escamilla AM. Engineering Biological Approaches for Detection of Toxic Compounds: A New Microbial Biosensor Based on the Pseudomonas putida TtgR Repressor. Mol Biotechnol. 2015 Jun;57(6):558-64. doi: 10.1007/s12033-015-9849-2. 

  • Espinosa-Urgel M, Serrano L, Ramos JL, Fernández-Escamilla AM. Engineering Biological Approaches for Detection of Toxic Compounds: A New Microbial Biosensor Based on the Pseudomonas putida TtgR Repressor. Mol Biotechnol. 2015 Jun;57(6):558-64. doi: 10.1007/s12033-015-9849-2.

  • Fernandez-Escamilla A. M., Cheung, M. S., Vega, M. C., Wilmanns, M., Onuchic, J. N., Serrano, L. Solvation in protein folding analysis, combination of theoretical and experimental approaches. Proceedings of the National Academy of Science of the United States of America: PNAS (2004), 101, 2834-2839. 

  • Fernandez-Escamilla A. M., Rosseau, F., Schymkowitz, J. & Serrano, L. Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nature Biotechnology (2004), 22, 1302-1306.

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Patents and Available Technologies

  • TANGO. A computer algorithm designed to predict aggregation-nucleating regions in proteins as well, the effect of mutations and environmental conditions on the aggregation propensity of these regions. We derived a statistical mechanics algorithm, TANGO, based on simple physico-chemical principles of secondary structure formation extended by the assumption that the core regions of an aggregate are fully buried. TANGO was benchmarked against 175 peptides of over 20 proteins and was able to predict the sequences experimentally observed to contribute to the aggregation of these proteins. Further TANGO correctly predicts the aggregation propensities of several disease-related mutations in the Alzheimer’s b-peptide. Our algorithm, therefore, opens the possibility to screen large databases for potentially disease-related aggregation motifs as well as to optimize recombinant protein yields by rationally out-designing protein aggregation.

Company Agreements

  • Detection of toxic compounds by the bacterial biosensor based on the TtgR repressor of Pseudomonas putida DOT -T1E. Financial Entities: GRONTAL Biotechnological Solutions S.L. and Spanish National Research Council (CSIC). Principal Investigator: Ana María Fernández Escamilla.