个人简介

Dr. Chica specializes in the development of novel proteins with useful properties for their application in chemistry. In particular, he is interested in developing new protein-based biocatalysts for the asymmetric synthesis of D-amino acids as well as red fluorescent proteins for their application in whole-body imaging. The methodology used by Dr. Chica involves using computational protein design algorithms to search through the vastness of sequence space to help predict protein sequences that are compatible with the desired protein fold and function. His multidisciplinary research program encompasses activities such as experimental protein chemistry, enzymology, biochemistry, molecular biology, and molecular modelling.

研究领域

The wide range of extraordinary properties displayed by proteins, such as specific ligand binding, high catalytic activity, and ligand-induced conformational changes, allows them to carry out complex molecular processes with extreme precision and efficiency. Because of these properties, many proteins are being exploited for a large number of applications in industry and research. Although various useful properties from natural proteins are being exploited, novel properties not found in nature are required to expand the applications possible for proteins in industry and research. To access these desired new properties, scientists use protein engineering and design techniques. Protein engineering and design have yielded many successes, yet the identification of protein sequences that will display the desired properties remains a formidable challenge due to the vastness of sequence space that one must sample to identify beneficial mutations. To help overcome the inherent difficulties of protein engineering, computational protein design (CPD) algorithms have been developed. The power of CPD results from its capability to perform virtual screening of sequence spaces astronomically larger (>10E80 sequences) than those that can be experimentally tested. Our research group exploits CPD algorithms to achieve three long-term aims, which are (1) to create new proteins for chemical and biological applications, (2) to develop new computational methods to more efficiently engineer proteins, and (3) to gain fundamental knowledge about the determinants of protein function using a design-based approach instead of the traditional perturbation-based approach.

The wide range of extraordinary properties displayed by proteins, such as specific ligand binding, high catalytic activity, and ligand-induced conformational changes, allows them to carry out complex molecular processes with extreme precision and efficiency. Because of these properties, many proteins are being exploited for a large number of applications in industry and research. Although various useful properties from natural proteins are being exploited, novel properties not found in nature are required to expand the applications possible for proteins in industry and research. To access these desired new properties, scientists use protein engineering and design techniques. Protein engineering and design have yielded many successes, yet the identification of protein sequences that will display the desired properties remains a formidable challenge due to the vastness of sequence space that one must sample to identify beneficial mutations. To help overcome the inherent difficulties of protein engineering, computational protein design (CPD) algorithms have been developed. The power of CPD results from its capability to perform virtual screening of sequence spaces astronomically larger (>10E80 sequences) than those that can be experimentally tested. Our research group exploits CPD algorithms to achieve three long-term aims, which are 1) to create new proteins for useful applications, 2) to develop new computational strategies to more efficiently engineer proteins, and 3) to gain fundamental knowledge about the determinants of protein function using a design-based approach instead of the traditional perturbation-based approach.

近期论文

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Davey JA, Damry AM, Goto NK* & Chica RA* (2017) Rational Design of Proteins that Exchange on Functional Timescales. Submitted. Preprint available on BioRxiv. St-Jacques AD, Gagnon O & Chica RA* (2017) Computational Enzyme Design: Successes, Challenges and Future Directions. In: Williams G & Hall M, editors. Modern Biocatalysis: Advances Towards Synthetic Biological Systems, Royal Society of Chemistry, in press. Eason MG, Damry AM & Chica RA* (2017) Structure-Guided Rational Design of Red Fluorescent Proteins: Towards Designer Genetically-Encoded Fluorophores. Current Opinion in Structural Biology 45, 91-99. Davey JA & Chica RA* (2017) Multistate Computational Protein Design with Backbone Ensembles. Methods in Molecular Biology 1529, 161-179. Davey JA & Chica RA* (2016) Turning a Negative into a Positive: Conversion of a Homodimer into a Heterodimer using Negative State Repertoires. Structure 24, 496-497. Invited commentary article. Pandelieva AT, Baran MJ, Calderini GF, McCann JL, Tremblay V, Sarvan S, Davey JA, Couture JF* & Chica RA* (2016) Brighter Red Fluorescent Proteins by Rational Design of Triple-Decker Motif. ACS Chemical Biology 11, 508-517. St-Jacques AD, Rachel NM, Curry DR, Gillet SMFG, Clouthier CM, Keillor JW, Pelletier JN & Chica RA* (2016) Specificity of Transglutaminase-Catalyzed Peptide Synthesis. Journal of Molecular Catalysis B: Enzymatic 123, 53-61. Davey JA, Damry AM, Euler CK, Goto NK & Chica RA* (2015) Prediction of Stable Globular Proteins using Negative Design With Non-Native Backbone Ensembles. Structure 23, 2011-2021. Chica RA* (2015) Protein Engineering in the 21st Century. Protein Science 24, 431-433. Commentary article. Davey JA & Chica RA* (2015) Optimization of Rotamers Prior to Template Minimization Improves Stability Predictions Made by Computational Protein Design. Protein Science 24, 545-560. Lanouette S, Davey JA, Elisma F, Ning Z, Figeys D, Chica RA* & Couture JF* (2015) Discovery of Substrates for a SET Domain Lysine Methyltransferase Predicted by Multistate Computational Protein Design. Structure 23, 206-215. Commentary on this article can be found here. Barber JEB, Damry AM, Calderini GF, Walton CJW & Chica RA* (2014) Continuous Colorimetric Screening Assay for Detection of D-Amino Acid Aminotransferase Mutants Displaying Altered Substrate Specificity. Analytical Biochemistry 463, 23-30. Davey JA & Chica RA* (2014) Improving the Accuracy of Protein Stability Predictions With Multistate Design Using a Variety of Backbone Ensembles. Proteins: Structure, Function and Bioinformatics 82, 771-784. Mironov GG, St.-Jacques AD, Mungham A, Eason MG, Chica RA* & Berezovski MV* (2013) Bioanalysis for Biocatalysis: Multiplexed Capillary Electrophoresis–Mass Spectrometry Assay for Aminotransferase Substrate Discovery and Specificity Profiling. Journal of the American Chemical Society 135, 13728-13736. Walton CJW & Chica RA* (2013) A High-Throughput Assay for Screening L- or D-amino Acid Specific Aminotransferase Mutant Libraries. Analytical Biochemistry 441, 190–198. Moore MM, Oteng-Pabi SK, Pandelieva AT, Mayo SL & Chica RA* (2012) Recovery of Red Fluorescent Protein Chromophore Maturation Deficiency through Rational Design. PLoS One 7: e52463. Davey JA & Chica RA* (2012) Multistate Approaches in Computational Protein Design. Protein Science 21, 1241-1252. Postdoctoral Research Privett HK, Kiss G, Lee TM, Blomberg R, Chica RA, Thomas LM, Hilvert D, Houk KN & Mayo SL (2012) Iterative Approach to Computational Enzyme Design. Proceedings of the National Academy of Science of the USA 109, 3790-3795. Hemmert AC, Otto TC, Chica RA, Wierdl M, Edwards JS, Lewis SL, Edwards CC, Tsurkan L, Cadieux CL, Kasten SA, Cashman JR, Mayo SL, Potter PM, Cerasoli DM & Redinbo MR (2011) Nerve Agent Hydrolysis Activity Designed into a Human Drug Metabolism Enzyme. PLoS One 6, e17441. Chica RA, Moore MM, Allen BD & Mayo SL (2010) Generation of Longer Emission Wavelength Red Fluorescent Proteins Using Computationally Designed Libraries. Proceedings of the National Academy of Science of the USA 107, 20257-20262. Faculty of 1000 review of this article can be found here.