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  • 1
    Publication Date: 2008-03-08
    Description: The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431203/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431203/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Jiang, Lin -- Althoff, Eric A -- Clemente, Fernando R -- Doyle, Lindsey -- Rothlisberger, Daniela -- Zanghellini, Alexandre -- Gallaher, Jasmine L -- Betker, Jamie L -- Tanaka, Fujie -- Barbas, Carlos F 3rd -- Hilvert, Donald -- Houk, Kendall N -- Stoddard, Barry L -- Baker, David -- R01 CA097328/CA/NCI NIH HHS/ -- R01 GM049857/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2008 Mar 7;319(5868):1387-91. doi: 10.1126/science.1152692.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/18323453" target="_blank"〉PubMed〈/a〉
    Keywords: Aldehyde-Lyases/*chemistry/metabolism ; *Algorithms ; Binding Sites ; Catalysis ; Catalytic Domain ; Computer Simulation ; Crystallography, X-Ray ; Hydrogen Bonding ; Hydrophobic and Hydrophilic Interactions ; Kinetics ; Models, Molecular ; Protein Conformation ; Protein Engineering
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2008-03-21
    Description: The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination-a model reaction for proton transfer from carbon-with measured rate enhancements of up to 10(5) and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a 〉200-fold increase in k(cat)/K(m) (k(cat)/K(m) of 2,600 M(-1)s(-1) and k(cat)/k(uncat) of 〉10(6)). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Rothlisberger, Daniela -- Khersonsky, Olga -- Wollacott, Andrew M -- Jiang, Lin -- DeChancie, Jason -- Betker, Jamie -- Gallaher, Jasmine L -- Althoff, Eric A -- Zanghellini, Alexandre -- Dym, Orly -- Albeck, Shira -- Houk, Kendall N -- Tawfik, Dan S -- Baker, David -- Howard Hughes Medical Institute/ -- England -- Nature. 2008 May 8;453(7192):190-5. doi: 10.1038/nature06879. Epub 2008 Mar 19.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/18354394" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Amino Acid Motifs ; Binding Sites/genetics ; Catalysis ; Computational Biology ; *Computer Simulation ; Crystallography, X-Ray ; Directed Molecular Evolution/*methods ; Drug Design ; Drug Evaluation, Preclinical ; Enzymes/*chemistry/genetics/*metabolism ; Kinetics ; Models, Chemical ; Models, Molecular ; Protein Engineering/*methods ; Quantum Theory ; Sensitivity and Specificity
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2014-01-28
    Description: Environmental Science & Technology DOI: 10.1021/es4043098
    Print ISSN: 0013-936X
    Electronic ISSN: 1520-5851
    Topics: Chemistry and Pharmacology , Energy, Environment Protection, Nuclear Power Engineering
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  • 4
    Publication Date: 2012-06-27
    Description: Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (kcat/Km values of ≤ 5 × 104 M-1s-1). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by kcat/Km, and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59’s evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to 〉 2,000-fold increase in catalytic efficiency, mainly via higher kcat values. The best KE59 variants exhibited kcat/Km values up to 0.6 × 106 M-1s-1, and kcat/kuncat values of ≤ 107 almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 5
    Publication Date: 2008-03-07
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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