Protein Engineering & Computational Protein Design

We specialize in the development of novel proteins with useful properties for their application in chemistry and biology. In particular, we are interested in developing designer biocatalysts for chemical synthesis as well as genetically-encoded biosensors based on fluorescent proteins for in vivo imaging applications. To achieve these goals, we develop and exploit multistate computational protein design methods to predict mutations leading to the desired protein property. More information on our research projects can be found in the Research section.

Latest Results

Legault S et al. (2022) Chemical Science, 13, 1408-1418

Here, we use computational protein design to enhance red fluorescent protein brightness by optimizing packing of the chromophore, which we hypothesized would increase quantum yield by rigidifying it and reducing non-radiative decay. Residues surrounding the chromophore were simultaneously mutated in silico to various combinations of aliphatic amino acids. We experimentally characterized the top 10 designed sequences and identified mSandy1, a variant displaying an 11-fold enhancement to quantum yield relative to its parent RFP (absolute quantum yield increase of 0.24), a result that has previously only been achieved using multiple rounds of directed evolution with high-throughput screening of several thousand variants. To further improve brightness, we performed three rounds of directed evolution on mSandy1 and obtained mSandy2, the brightest Discosoma sp. derived monomeric RFP with an emission maximum >600 nm reported to date. Crystallographic analysis confirmed that the chromophore p-hydroxybenzylidene moiety of mSandy2 was rigidified due to tight packing by aliphatic residues, confirming our original hypothesis. Our results demonstrate the utility of computational protein design for increasing RFP quantum yield by enhancing chromophore packing, and generating novel templates for directed evolution of brighter variants

Quote: "While many RFPs are now available, novel variants displaying high brightness in the far-red or near-infrared optical window are still desired to enable various types of applications. In this context, the [computational protein design] approach for enhancing quantum yield described here can expedite the creation of novel bright RFP templates for further engineering."

Read more here.

Previous results can be found here.


Advanced Protein Engineering Training, Internships, Courses & Exhibition (APRENTICE) Program

Interested in pursuing graduate training in protein engineering? Find out more about the APRENTICE program by clicking on the image below.


Research Funding

We gratefully acknowledge support from the following agencies:



Protein Engineering, Computational Protein Design, Multistate Design, Enzymes, Biocatalysis, Fluorescent Proteins, Protein Dynamics, Molecular Modeling, Protein Science, Biological Chemistry


Contact info

Roberto Chica, Ph. D.
Department of Chemistry and Biomolecular Sciences
University of Ottawa
10 Marie Curie
Ottawa, ON K1N 6N5

(613) 562-5800 x 1988
rchica at uottawa dot ca