AIMC Topic: Directed Molecular Evolution
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PyPEF-An Integrated Framework for Data-Driven Protein Engineering.
Journal of chemical information and modeling
Jul 14, 2021
Data-driven strategies are gaining increased attention in protein engineering due to recent advances in access to large experimental databanks of proteins, next-generation sequencing (NGS), high-throughput screening (HTS) methods, and the development...
Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.
Cell
Dec 16, 2020
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...
Machine learning-assisted enzyme engineering.
Methods in enzymology
Jun 12, 2020
Directed evolution and rational design are powerful strategies in protein engineering to tailor enzyme properties to meet the demands in academia and industry. Traditional approaches for enzyme engineering and directed evolution are often experimenta...
One-shot optimization of multiple enzyme parameters: Tailoring glucose oxidase for pH and electron mediators.
Biotechnology and bioengineering
Oct 1, 2019
Enzymes are biological catalysts with many industrial applications, but natural enzymes are usually unsuitable for industrial processes because they are not optimized for the process conditions. The properties of enzymes can be improved by directed e...
Machine-learning-guided directed evolution for protein engineering.
Nature methods
Jul 15, 2019
Protein engineering through machine-learning-guided directed evolution enables the optimization of protein functions. Machine-learning approaches predict how sequence maps to function in a data-driven manner without requiring a detailed model of the ...
Machine learning-assisted directed protein evolution with combinatorial libraries.
Proceedings of the National Academy of Sciences of the United States of America
Apr 12, 2019
To reduce experimental effort associated with directed protein evolution and to explore the sequence space encoded by mutating multiple positions simultaneously, we incorporate machine learning into the directed evolution workflow. Combinatorial sequ...
A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.
Scientific reports
Nov 13, 2018
Directed evolution is an important research activity in synthetic biology and biotechnology. Numerous reports describe the application of tedious mutation/screening cycles for the improvement of proteins. Recently, knowledge-based approaches have fac...
Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins.
ACS synthetic biology
Aug 20, 2018
Molecular evolution based on mutagenesis is widely used in protein engineering. However, optimal proteins are often difficult to obtain due to a large sequence space. Here, we propose a novel approach that combines molecular evolution with machine le...
A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.
Nature chemical biology
Feb 26, 2018
We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing prote...
Development and characterization of an α-l-rhamnosidase mutant with improved thermostability and a higher efficiency for debittering orange juice.
Food chemistry
Nov 16, 2017
The glycoside hydrolase, α-l-rhamnosidase, could remove the bitter taste of naringin from citrus juices. However, most α-l-rhamnosidases are easily deactivated at high temperatures, limiting the practice in debittering citrus juices. The V529A mutant...
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