Toward New Nonnatural TIM-Barrel Enzymes Using Computational Design and Directed Evolution Approaches

2016 ◽  
pp. 561-611
Author(s):  
Mirja Krause ◽  
Rik Wierenga
Keyword(s):  
Directed Evolution ◽  
Computational Design ◽  
Tim Barrel

Artificial Enzymes bringing together Computational Design and Directed Evolution

2021 ◽  
Author(s):  
Beatriz de Pina Mariz ◽  
Sara S Carvalho ◽  
Iris Batalha ◽  
Ana Sofia Pina
Keyword(s):  
Directed Evolution ◽  
Chemical Reactions ◽  
Computational Design ◽  
Industrial Processes ◽  
Artificial Enzymes ◽  
Ancient Times

Enzymes are proteins that catalyse chemical reactions and, as such, have been widely used to facilitate a variety of natural and industrial processes, dating back to ancient times. In fact,...

scholarly journals Development of High Affinity and High Specificity Inhibitors of Matrix Metalloproteinase 14 through Computational Design and Directed Evolution

2017 ◽  
Vol 292 (8) ◽  
pp. 3481-3495 ◽  
Author(s):  
Valeria Arkadash ◽  
Gal Yosef ◽  
Jason Shirian ◽  
Itay Cohen ◽  
Yuval Horev ◽  
...  
Keyword(s):  
Directed Evolution ◽  
Surface Display ◽  
High Specificity ◽  
Computational Design ◽  
Computational Method ◽  
Yeast Surface Display ◽  
Mmp Inhibitor ◽  
Starting Point ◽  
Yeast Surface

Degradation of the extracellular matrices in the human body is controlled by matrix metalloproteinases (MMPs), a family of more than 20 homologous enzymes. Imbalance in MMP activity can result in many diseases, such as arthritis, cardiovascular diseases, neurological disorders, fibrosis, and cancers. Thus, MMPs present attractive targets for drug design and have been a focus for inhibitor design for as long as 3 decades. Yet, to date, all MMP inhibitors have failed in clinical trials because of their broad activity against numerous MMP family members and the serious side effects of the proposed treatment. In this study, we integrated a computational method and a yeast surface display technique to obtain highly specific inhibitors of MMP-14 by modifying the natural non-specific broad MMP inhibitor protein N-TIMP2 to interact optimally with MMP-14. We identified an N-TIMP2 mutant, with five mutations in its interface, that has an MMP-14 inhibition constant (Ki) of 0.9 pm, the strongest MMP-14 inhibitor reported so far. Compared with wild-type N-TIMP2, this variant displays ∼900-fold improved affinity toward MMP-14 and up to 16,000-fold greater specificity toward MMP-14 relative to other MMPs. In an in vitro and cell-based model of MMP-dependent breast cancer cellular invasiveness, this N-TIMP2 mutant acted as a functional inhibitor. Thus, our study demonstrates the enormous potential of a combined computational/directed evolution approach to protein engineering. Furthermore, it offers fundamental clues into the molecular basis of MMP regulation by N-TIMP2 and identifies a promising MMP-14 inhibitor as a starting point for the development of protein-based anticancer therapeutics.

scholarly journals A De Novo Protein Binding Pair By Computational Design and Directed Evolution

2011 ◽  
Vol 42 (2) ◽  
pp. 250-260 ◽  
Author(s):  
John Karanicolas ◽  
Jacob E. Corn ◽  
Irwin Chen ◽  
Lukasz A. Joachimiak ◽  
Orly Dym ◽  
...  
Keyword(s):  
Protein Binding ◽  
Directed Evolution ◽  
De Novo ◽  
Computational Design

scholarly journals Optimization of the In-Silico-Designed Kemp Eliminase KE70 by Computational Design and Directed Evolution

2011 ◽  
Vol 407 (3) ◽  
pp. 391-412 ◽  
Author(s):  
Olga Khersonsky ◽  
Daniela Röthlisberger ◽  
Andrew M. Wollacott ◽  
Paul Murphy ◽  
Orly Dym ◽  
...  
Keyword(s):  
Directed Evolution ◽  
In Silico ◽  
Computational Design

scholarly journals Towards conformational fidelity of a quaternary HIV-1 epitope: computational design and directed evolution of a minimal V1V2 antigen

2018 ◽  
Vol 31 (4) ◽  
pp. 121-133 ◽  
Author(s):  
Jennifer I Lai ◽  
Deeptak Verma ◽  
Chris Bailey-Kellogg ◽  
Margaret E Ackerman
Keyword(s):  
Directed Evolution ◽  
Computational Design ◽  
Hiv 1
Sign in / Sign up

Export Citation Format

Share Document