Dataset Information

Directed polymerase evolution.

ABSTRACT: Polymerases evolved in nature to synthesize DNA and RNA, and they underlie the storage and flow of genetic information in all cells. The availability of these enzymes for use at the bench has driven a revolution in biotechnology and medicinal research; however, polymerases did not evolve to function efficiently under the conditions required for some applications and their high substrate fidelity precludes their use for most applications that involve modified substrates. To circumvent these limitations, researchers have turned to directed evolution to tailor the properties and/or substrate repertoire of polymerases for different applications, and several systems have been developed for this purpose. These systems draw on different methods of creating a pool of randomly mutated polymerases and are differentiated by the process used to isolate the most fit members. A variety of polymerases have been evolved, providing new or improved functionality, as well as interesting new insight into the factors governing activity.

SUBMITTER: Chen T

PROVIDER: S-EPMC3982152 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Directed polymerase evolution.

Chen Tingjian T Romesberg Floyd E FE

FEBS letters 20131105 2

Polymerases evolved in nature to synthesize DNA and RNA, and they underlie the storage and flow of genetic information in all cells. The availability of these enzymes for use at the bench has driven a revolution in biotechnology and medicinal research; however, polymerases did not evolve to function efficiently under the conditions required for some applications and their high substrate fidelity precludes their use for most applications that involve modified substrates. To circumvent these limit ...[more]

PMID: 24211837

Similar Datasets

Project description:Directed evolution is a powerful tool for improving existing properties and imparting completely new functionalities to proteins1-4. Nonetheless, its potential in even small proteins is inherently limited by the astronomical number of possible amino acid sequences. Sampling the complete sequence space of a 100-residue protein would require testing of 20100 combinations, which is beyond any existing experimental approach. In practice, selective modification of relatively few residues is sufficient for efficient improvement, functional enhancement and repurposing of existing proteins5. Moreover, computational methods have been developed to predict the locations and, in certain cases, identities of potentially productive mutations6-9. Importantly, all current approaches for prediction of hot spots and productive mutations rely heavily on structural information and/or bioinformatics, which is not always available for proteins of interest. Moreover, they offer a limited ability to identify beneficial mutations far from the active site, even though such changes may markedly improve the catalytic properties of an enzyme10. Machine learning methods have recently showed promise in predicting productive mutations11, but they frequently require large, high-quality training datasets, which are difficult to obtain in directed evolution experiments. Here we show that mutagenic hot spots in enzymes can be identified using NMR spectroscopy. In a proof-of-concept study, we converted myoglobin, a non-enzymatic oxygen storage protein, into a highly efficient Kemp eliminase using only three mutations. The observed levels of catalytic efficiency exceed those of proteins designed using current approaches and are similar with those of natural enzymes for the reactions that they are evolved to catalyse. Given the simplicity of this experimental approach, which requires no a priori structural or bioinformatic knowledge, we expect it to be widely applicable and to enable the full potential of directed enzyme evolution.

Dataset Information

Directed polymerase evolution.

Publications

Directed polymerase evolution.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets