Design and Optimization of New Phosphine Oxazoline Ligands via High-Throughput Catalyst Screening

1998 ◽  
Vol 120 (36) ◽  
pp. 9180-9187 ◽  
Author(s):  
Alexander M. Porte ◽  
Joe Reibenspies ◽  
Kevin Burgess
Keyword(s):  
High Throughput ◽  
Design And Optimization ◽  
Catalyst Screening ◽  
Oxazoline Ligands

scholarly journals Genetically encoded biosensors for lignocellulose valorization

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Guadalupe Alvarez-Gonzalez ◽  
Neil Dixon
Keyword(s):  
High Throughput ◽  
Critical Factor ◽  
Modern Society ◽  
Low Carbon ◽  
Design And Optimization ◽  
Oil Reserves ◽  
Cell Factories ◽  
Major Bottleneck ◽  
Fuels And Chemicals ◽  
Pathway Regulation

Abstract Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery.

Discovery and evaluation of highly active imidotitanium ethylene polymerisation catalysts using high throughput catalyst screening

2004 ◽  
pp. 434-435 ◽  
Author(s):  
Nico Adams ◽  
Henricus J. Arts ◽  
Paul D. Bolton ◽  
Dan Cowell ◽  
Stuart R. Dubberley ◽  
...  
Keyword(s):  
High Throughput ◽  
Highly Active ◽  
Catalyst Screening ◽  
Ethylene Polymerisation

New Catalysts and Conditions for a CH Insertion Reaction Identified by High Throughput Catalyst Screening

1996 ◽  
Vol 35 (2) ◽  
pp. 220-222 ◽  
Author(s):  
Kevin Burgess ◽  
Hee-Jong Lim ◽  
Alexander M. Porte ◽  
Gary A. Sulikowski
Keyword(s):  
High Throughput ◽  
Insertion Reaction ◽  
Catalyst Screening

A Phage-Assisted Continuous Selection Approach for Deep Mutational Scanning of Protein-Protein Interactions

2019 ◽  
Author(s):  
Julia Zinkus-Boltz ◽  
Craig Devalk ◽  
Bryan Dickinson
Keyword(s):  
High Throughput ◽  
Protein Interactions ◽  
High Throughput Sequencing ◽  
Continuous Selection ◽  
Protein Protein Interactions ◽  
Design And Optimization ◽  
Molecular Determinants ◽  
A Cell ◽  
Key Drivers ◽  
Key Residues

Protein-protein interactions (PPIs) are critical for organizing molecules in a cell and mediating signaling pathways. Dysregulation of PPIs are often key drivers of disease. To better understand the biophysical basis of such disease processes – and to potentially target them - it is critical to understand the molecular determinants of PPIs. Deep mutational scanning (DMS) facilitates the acquisition of large amounts of biochemical data by coupling selection with high throughput sequencing (HTS). The challenging and labor-intensive design and optimization of a relevant selection platform for DMS, however, limits the use of powerful directed evolution and selection approaches. To address this limitation, we designed a versatile new phage assisted continuous selection (PACS) system using our proximity-dependent split RNA polymerase (RNAP) biosensors with the aim of greatly simplifying and streamlining the design of a new selection platform for PPIs. After characterization and validation using the model KRAS/RAF PPI, we generated a library of RAF variants and subjected them to PACS and DMS. Our HTS data revealed that amino acid (aa) positions 66, 84, and 89 on RAF, key residues in the KRAS/RAF PPI, are intolerant to mutations. We also identified a subset of residues with broad aa substitution tolerance, aa positions 52, 55, 76, and 79. Due to the plug and play nature of RNAP biosensors, this method can easily be extended to other PPIs. More broadly, this, and other methods under development, supports the application of evolutionary and high-throughput approaches to bear on biochemical problems, moving towards a more comprehensive understanding of sequence-function relationships in proteins.

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