title: Computational protein engineering: bridging the gap between rational design and laboratory evolution.
abstract: Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation "hotspots" with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.
authors.affiliation: Department of Cell and Molecular Biology, Uppsala Biomedical Center (BMC), Uppsala University, Box 596, S-751 24 Uppsala, Sweden. kamerlin@icm.uu.se.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Barrozo
authors.forename: Rok
authors.initials: R
authors.lastname: Borstnar
authors.forename: Gaël
authors.initials: G
authors.lastname: Marloie
authors.forename: Shina Caroline Lynn
authors.initials: SC
authors.lastname: Kamerlin
mesh_terms: D020134:Catalytic Domain; D019295:Computational Biology; D019020:Directed Molecular Evolution; D004798:Enzymes / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D007700:Kinetics; D056004:Molecular Dynamics Simulation; D015202:Protein Engineering; D011789:Quantum Theory
chemical_list: D004798:Enzymes