Engineering proteinase K using machine learning and synthetic genes.

ABSTRACT:

Background

Altering a protein's function by changing its sequence allows natural proteins to be converted into useful molecular tools. Current protein engineering methods are limited by a lack of high throughput physical or computational tests that can accurately predict protein activity under conditions relevant to its final application. Here we describe a new synthetic biology approach to protein engineering that avoids these limitations by combining high throughput gene synthesis with machine learning-based design algorithms.

Results

We selected 24 amino acid substitutions to make in proteinase K from alignments of homologous sequences. We then designed and synthesized 59 specific proteinase K variants containing different combinations of the selected substitutions. The 5

SUBMITTER: Liao J 

PROVIDER: S-EPMC1847811 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature