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\n  \n 2017\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Extending Chemical Perturbations Of The Ubiquitin Fitness Landscape In A Classroom Setting.\n \n \n \n \n\n\n \n Mavor, D.; Barlow, K.; Asarnow, D.; Birman, Y.; Britain, D.; Chen, W.; Green, E. M.; Kenner, L. R.; Mensa, B.; Morinishi, L. S.; Nelson, C. A.; Poss, E. M.; Suresh, P.; Tian, R.; Arhar, T.; Ary, B. E.; Bauer, D. P.; Bergman, I. D.; Brunetti, R. M.; Chio, C. M.; Dai, S. A.; Dickinson, M. S.; Elledge, S.; Hendel, N. L.; Helsell, C. V. M.; Kang, E.; Kern, N.; Khoroshkin, M. S.; Kirkemo, L. L.; Lewis, G. R.; Lou, K.; Marin, W. M.; Maxwell, A. M.; McTigue, P. F.; Meyers-Turnbull, D.; Nagy, T. L.; Natale, A. M.; Oltion, K.; Pourmal, S.; Reder, G. K.; Rettko, N. J.; Rohweder, P. J.; Schwarz, D. M. C.; Tan, S. K.; Thomas, P. V.; Tibble, R. W.; Tsai, M. K.; Town, J. P.; Ugur, F. S.; Wassarman, D. R.; Wolff, A. M.; Wu, T. S.; Bogdanoff, D.; Li, J.; Thorn, K. S.; O'Conchúir, S. T.; Swaney, D. L.; Chow, E. D.; Madhani, H. D.; Redding, S.; Bolon, D. N. A.; Kortemme, T.; DeRisi, J. L.; Kampmann, M.; and Fraser, J. S.\n\n\n \n\n\n\n bioRxiv. May 2017.\n \n\n\n\n
\n\n\n\n \n \n \"ExtendingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{mavor_extending_2017,\n\ttitle = {Extending {Chemical} {Perturbations} {Of} {The} {Ubiquitin} {Fitness} {Landscape} {In} {A} {Classroom} {Setting}},\n\turl = {http://biorxiv.org/content/early/2017/05/17/139352.abstract},\n\tdoi = {10.1101/139352},\n\tabstract = {Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary time scales. Building on our previous work (Mavor et al. 2016), we used deep mutational scanning to determine how twelve new chemicals reveal novel mutational sensitivities of ubiquitin residues. We found sensitization of Lys63 in eight new conditions. In total, our experiments have uncovered a highly sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the Ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales.},\n\tjournal = {bioRxiv},\n\tauthor = {Mavor, David and Barlow, Kyle and Asarnow, Daniel and Birman, Yuliya and Britain, Derek and Chen, Weilin and Green, Evan M. and Kenner, Lillian R. and Mensa, Bruk and Morinishi, Leanna S. and Nelson, Charlotte A. and Poss, Erin M. and Suresh, Pooja and Tian, Ruilin and Arhar, Taylor and Ary, Beatrice E. and Bauer, David P. and Bergman, Ian D. and Brunetti, Rachel M. and Chio, Cynthia M. and Dai, Shizhong A. and Dickinson, Miles S. and Elledge, Susanna and Hendel, Nathan L. and Helsell, Cole V. M. and Kang, Emily and Kern, Nadja and Khoroshkin, Matvei S. and Kirkemo, Lisa L. and Lewis, Greyson R. and Lou, Kevin and Marin, Wesley M. and Maxwell, Alison M. and McTigue, Peter F. and Meyers-Turnbull, Douglas and Nagy, Tamas L. and Natale, Andrew M. and Oltion, Keely and Pourmal, Sergei and Reder, Gabriel K. and Rettko, Nicholas J. and Rohweder, Peter J. and Schwarz, Daniel M. C. and Tan, Sophia K. and Thomas, Paul V. and Tibble, Ryan W. and Tsai, Mary K. and Town, Jason P. and Ugur, Fatima S. and Wassarman, Douglas R. and Wolff, Alexander M. and Wu, Taia S. and Bogdanoff, Derek and Li, Jennifer and Thorn, Kurt S. and O'Conchúir, Shane Thomas and Swaney, Danielle L. and Chow, Eric D. and Madhani, Hiten D. and Redding, Sy and Bolon, Daniel N. A. and Kortemme, Tanja and DeRisi, Joseph L. and Kampmann, Martin and Fraser, James S.},\n\tmonth = may,\n\tyear = {2017},\n}\n\n
\n
\n\n\n
\n Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary time scales. Building on our previous work (Mavor et al. 2016), we used deep mutational scanning to determine how twelve new chemicals reveal novel mutational sensitivities of ubiquitin residues. We found sensitization of Lys63 in eight new conditions. In total, our experiments have uncovered a highly sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the Ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales.\n
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\n  \n 2016\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Design of Light-Controlled Protein Conformations and Functions.\n \n \n \n \n\n\n \n Ritterson, R.; Hoersch, D.; Barlow, K.; and Kortemme, T.\n\n\n \n\n\n\n In Stoddard, B. L., editor(s), Computational Design of Ligand Binding Proteins, of Methods in Molecular Biology, pages 197–211. Springer New York, January 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DesignPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@incollection{stoddard_design_2016,\n\tseries = {Methods in {Molecular} {Biology}},\n\ttitle = {Design of {Light}-{Controlled} {Protein} {Conformations} and {Functions}},\n\tcopyright = {©2016 Springer Science+Business Media New York},\n\tisbn = {978-1-4939-3567-3},\n\turl = {http://dx.doi.org/10.1007/978-1-4939-3569-7_12},\n\tabstract = {In recent years, interest in controlling protein function with light has increased. Light offers a number of unique advantages over other methods, including spatial and temporal control and high selectivity. Here, we describe a general protocol for engineering a protein to be controllable with light via reaction with an exogenously introduced photoisomerizable small molecule and illustrate our protocol with two examples from the literature: the engineering of the calcium affinity of the cell–cell adhesion protein cadherin, which is an example of a protein that switches from a native to a disrupted state (Ritterson et al. J Am Chem Soc (2013) 135:12516–12519), and the engineering of the opening and closing of the chaperonin Mm-cpn, an example of a switch between two functional states (Hoersch et al.: Nat Nanotechn (2013) 8:928–932). This protocol guides the user from considering which proteins may be most amenable to this type of engineering, to considerations of how and where to make the desired changes, to the assays required to test for functionality.},\n\tlanguage = {English},\n\tnumber = {1414},\n\turldate = {2016-10-20},\n\tbooktitle = {Computational {Design} of {Ligand} {Binding} {Proteins}},\n\tpublisher = {Springer New York},\n\tauthor = {Ritterson, RyanS. and Hoersch, Daniel and Barlow, KyleA. and Kortemme, Tanja},\n\teditor = {Stoddard, Barry L.},\n\tmonth = jan,\n\tyear = {2016},\n\tdoi = {10.1007/978-1-4939-3569-7_12},\n\tkeywords = {Light-modulatable proteins, Photoswitches, computational protein design, protein engineering},\n\tpages = {197--211},\n}\n\n
\n
\n\n\n
\n In recent years, interest in controlling protein function with light has increased. Light offers a number of unique advantages over other methods, including spatial and temporal control and high selectivity. Here, we describe a general protocol for engineering a protein to be controllable with light via reaction with an exogenously introduced photoisomerizable small molecule and illustrate our protocol with two examples from the literature: the engineering of the calcium affinity of the cell–cell adhesion protein cadherin, which is an example of a protein that switches from a native to a disrupted state (Ritterson et al. J Am Chem Soc (2013) 135:12516–12519), and the engineering of the opening and closing of the chaperonin Mm-cpn, an example of a switch between two functional states (Hoersch et al.: Nat Nanotechn (2013) 8:928–932). This protocol guides the user from considering which proteins may be most amenable to this type of engineering, to considerations of how and where to make the desired changes, to the assays required to test for functionality.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting.\n \n \n \n \n\n\n \n Mavor, D.; Barlow, K.; Thompson, S.; Barad, B. A.; Bonny, A. R.; Cario, C. L.; Gaskins, G.; Liu, Z.; Deming, L.; Axen, S. D.; Caceres, E.; Chen, W.; Cuesta, A.; Gate, R.; Green, E. M.; Hulce, K. R.; Ji, W.; Kenner, L. R.; Mensa, B.; Morinishi, L. S.; Moss, S. M.; Mravic, M.; Muir, R. K.; Niekamp, S.; Nnadi, C. I.; Palovcak, E.; Poss, E. M.; Ross, T. D.; Salcedo, E. C.; See, S.; Subramaniam, M.; Wong, A. W.; Li, J.; Thorn, K. S.; Conchúir, S. T. Ó; Roscoe, B. P.; Chow, E. D.; DeRisi, J. L.; Kortemme, T.; Bolon, D. N.; and Fraser, J. S.\n\n\n \n\n\n\n eLife, 5: e15802. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DeterminationPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{mavor_determination_2016,\n\ttitle = {Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting},\n\tvolume = {5},\n\tcopyright = {© 2016, Mavor et al. This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.},\n\tissn = {2050-084X},\n\turl = {http://elifesciences.org/content/5/e15802v1},\n\tdoi = {10.7554/eLife.15802},\n\tabstract = {{\\textless}meta name="DC.Rights" content="© 2016, Mavor et al. 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\n  \n 2015\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n A Web Resource for Standardized Benchmark Datasets, Metrics, and Rosetta Protocols for Macromolecular Modeling and Design.\n \n \n \n \n\n\n \n Conchúir, S. Ó; Barlow, K. A.; Pache, R. A.; Ollikainen, N.; Kundert, K.; O'Meara, M. J.; Smith, C. A.; and Kortemme, T.\n\n\n \n\n\n\n PLOS ONE, 10(9): e0130433. September 2015.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{conchuir_web_2015,\n\ttitle = {A {Web} {Resource} for {Standardized} {Benchmark} {Datasets}, {Metrics}, and {Rosetta} {Protocols} for {Macromolecular} {Modeling} and {Design}},\n\tvolume = {10},\n\tissn = {1932-6203},\n\turl = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130433},\n\tdoi = {10.1371/journal.pone.0130433},\n\tabstract = {The development and validation of computational macromolecular modeling and design methods depend on suitable benchmark datasets and informative metrics for comparing protocols. In addition, if a method is intended to be adopted broadly in diverse biological applications, there needs to be information on appropriate parameters for each protocol, as well as metrics describing the expected accuracy compared to experimental data. In certain disciplines, there exist established benchmarks and public resources where experts in a particular methodology are encouraged to supply their most efficient implementation of each particular benchmark. We aim to provide such a resource for protocols in macromolecular modeling and design. We present a freely accessible web resource ( https://kortemmelab.ucsf.edu/benchmarks ) to guide the development of protocols for protein modeling and design. The site provides benchmark datasets and metrics to compare the performance of a variety of modeling protocols using different computational sampling methods and energy functions, providing a “best practice” set of parameters for each method. Each benchmark has an associated downloadable benchmark capture archive containing the input files, analysis scripts, and tutorials for running the benchmark. The captures may be run with any suitable modeling method; we supply command lines for running the benchmarks using the Rosetta software suite. We have compiled initial benchmarks for the resource spanning three key areas: prediction of energetic effects of mutations, protein design, and protein structure prediction, each with associated state-of-the-art modeling protocols. With the help of the wider macromolecular modeling community, we hope to expand the variety of benchmarks included on the website and continue to evaluate new iterations of current methods as they become available.},\n\tnumber = {9},\n\turldate = {2016-04-06},\n\tjournal = {PLOS ONE},\n\tauthor = {Conchúir, Shane Ó and Barlow, Kyle A. and Pache, Roland A. and Ollikainen, Noah and Kundert, Kale and O'Meara, Matthew J. and Smith, Colin A. and Kortemme, Tanja},\n\tmonth = sep,\n\tyear = {2015},\n\tkeywords = {Alanine, Crystal structure, Macromolecular design, Multiple alignment calculation, Protein sequencing, Protein structure, Protein structure prediction, point mutation},\n\tpages = {e0130433},\n}\n\n
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\n The development and validation of computational macromolecular modeling and design methods depend on suitable benchmark datasets and informative metrics for comparing protocols. In addition, if a method is intended to be adopted broadly in diverse biological applications, there needs to be information on appropriate parameters for each protocol, as well as metrics describing the expected accuracy compared to experimental data. In certain disciplines, there exist established benchmarks and public resources where experts in a particular methodology are encouraged to supply their most efficient implementation of each particular benchmark. We aim to provide such a resource for protocols in macromolecular modeling and design. We present a freely accessible web resource ( https://kortemmelab.ucsf.edu/benchmarks ) to guide the development of protocols for protein modeling and design. The site provides benchmark datasets and metrics to compare the performance of a variety of modeling protocols using different computational sampling methods and energy functions, providing a “best practice” set of parameters for each method. Each benchmark has an associated downloadable benchmark capture archive containing the input files, analysis scripts, and tutorials for running the benchmark. The captures may be run with any suitable modeling method; we supply command lines for running the benchmarks using the Rosetta software suite. We have compiled initial benchmarks for the resource spanning three key areas: prediction of energetic effects of mutations, protein design, and protein structure prediction, each with associated state-of-the-art modeling protocols. With the help of the wider macromolecular modeling community, we hope to expand the variety of benchmarks included on the website and continue to evaluate new iterations of current methods as they become available.\n
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\n \n\n \n \n \n \n \n \n Improved specificity of TALE-based genome editing using an expanded RVD repertoire.\n \n \n \n \n\n\n \n Miller, J. C.; Zhang, L.; Xia, D. F.; Campo, J. J.; Ankoudinova, I. V.; Guschin, D. Y.; Babiarz, J. E.; Meng, X.; Hinkley, S. J.; Lam, S. C.; Paschon, D. E.; Vincent, A. I.; Dulay, G. P.; Barlow, K. A.; Shivak, D. A.; Leung, E.; Kim, J. D.; Amora, R.; Urnov, F. D.; Gregory, P. D.; and Rebar, E. J.\n\n\n \n\n\n\n Nature Methods, 12(5): 465–471. May 2015.\n \n\n\n\n
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@article{miller_improved_2015,\n\ttitle = {Improved specificity of {TALE}-based genome editing using an expanded {RVD} repertoire},\n\tvolume = {12},\n\tcopyright = {© 2015 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},\n\tissn = {1548-7091},\n\turl = {http://www.nature.com/nmeth/journal/v12/n5/full/nmeth.3330.html},\n\tdoi = {10.1038/nmeth.3330},\n\tabstract = {Transcription activator–like effector (TALE) proteins have gained broad appeal as a platform for targeted DNA recognition, largely owing to their simple rules for design. These rules relate the base specified by a single TALE repeat to the identity of two key residues (the repeat variable diresidue, or RVD) and enable design for new sequence targets via modular shuffling of these units. A key limitation of these rules is that their simplicity precludes options for improving designs that are insufficiently active or specific. Here we address this limitation by developing an expanded set of RVDs and applying them to improve the performance of previously described TALEs. As an extreme example, total conversion of a TALE nuclease to new RVDs substantially reduced off-target cleavage in cellular studies. By providing new RVDs and design strategies, these studies establish options for developing improved TALEs for broader application across medicine and biotechnology.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2016-04-06},\n\tjournal = {Nature Methods},\n\tauthor = {Miller, Jeffrey C. and Zhang, Lei and Xia, Danny F. and Campo, John J. and Ankoudinova, Irina V. and Guschin, Dmitry Y. and Babiarz, Joshua E. and Meng, Xiangdong and Hinkley, Sarah J. and Lam, Stephen C. and Paschon, David E. and Vincent, Anna I. and Dulay, Gladys P. and Barlow, Kyle A. and Shivak, David A. and Leung, Elo and Kim, Jinwon D. and Amora, Rainier and Urnov, Fyodor D. and Gregory, Philip D. and Rebar, Edward J.},\n\tmonth = may,\n\tyear = {2015},\n\tkeywords = {Biotechnology, Genetic engineering},\n\tpages = {465--471},\n}\n
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\n Transcription activator–like effector (TALE) proteins have gained broad appeal as a platform for targeted DNA recognition, largely owing to their simple rules for design. These rules relate the base specified by a single TALE repeat to the identity of two key residues (the repeat variable diresidue, or RVD) and enable design for new sequence targets via modular shuffling of these units. A key limitation of these rules is that their simplicity precludes options for improving designs that are insufficiently active or specific. Here we address this limitation by developing an expanded set of RVDs and applying them to improve the performance of previously described TALEs. As an extreme example, total conversion of a TALE nuclease to new RVDs substantially reduced off-target cleavage in cellular studies. By providing new RVDs and design strategies, these studies establish options for developing improved TALEs for broader application across medicine and biotechnology.\n
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\n  \n 2011\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n A TALE nuclease architecture for efficient genome editing.\n \n \n \n \n\n\n \n Miller, J. C.; Tan, S.; Qiao, G.; Barlow, K. A.; Wang, J.; Xia, D. F.; Meng, X.; Paschon, D. E.; Leung, E.; Hinkley, S. J.; Dulay, G. P.; Hua, K. L.; Ankoudinova, I.; Cost, G. J.; Urnov, F. D.; Zhang, H. S.; Holmes, M. C.; Zhang, L.; Gregory, P. D.; and Rebar, E. J.\n\n\n \n\n\n\n Nature Biotechnology, 29(2): 143–148. February 2011.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@article{miller_tale_2011,\n\ttitle = {A {TALE} nuclease architecture for efficient genome editing},\n\tvolume = {29},\n\tcopyright = {© 2010 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},\n\tissn = {1087-0156},\n\turl = {http://www.nature.com/nbt/journal/v29/n2/full/nbt.1755.html},\n\tdoi = {10.1038/nbt.1755},\n\tabstract = {Nucleases that cleave unique genomic sequences in living cells can be used for targeted gene editing and mutagenesis. Here we develop a strategy for generating such reagents based on transcription activator–like effector (TALE) proteins from Xanthomonas. We identify TALE truncation variants that efficiently cleave DNA when linked to the catalytic domain of FokI and use these nucleases to generate discrete edits or small deletions within endogenous human NTF3 and CCR5 genes at efficiencies of up to 25\\%. We further show that designed TALEs can regulate endogenous mammalian genes. These studies demonstrate the effective application of designed TALE transcription factors and nucleases for the targeted regulation and modification of endogenous genes.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2016-04-06},\n\tjournal = {Nature Biotechnology},\n\tauthor = {Miller, Jeffrey C. and Tan, Siyuan and Qiao, Guijuan and Barlow, Kyle A. and Wang, Jianbin and Xia, Danny F. and Meng, Xiangdong and Paschon, David E. and Leung, Elo and Hinkley, Sarah J. and Dulay, Gladys P. and Hua, Kevin L. and Ankoudinova, Irina and Cost, Gregory J. and Urnov, Fyodor D. and Zhang, H. Steve and Holmes, Michael C. and Zhang, Lei and Gregory, Philip D. and Rebar, Edward J.},\n\tmonth = feb,\n\tyear = {2011},\n\tkeywords = {Gene regulation, Genetic engineering, Molecular engineering},\n\tpages = {143--148},\n}\n\n
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\n Nucleases that cleave unique genomic sequences in living cells can be used for targeted gene editing and mutagenesis. Here we develop a strategy for generating such reagents based on transcription activator–like effector (TALE) proteins from Xanthomonas. We identify TALE truncation variants that efficiently cleave DNA when linked to the catalytic domain of FokI and use these nucleases to generate discrete edits or small deletions within endogenous human NTF3 and CCR5 genes at efficiencies of up to 25%. We further show that designed TALEs can regulate endogenous mammalian genes. These studies demonstrate the effective application of designed TALE transcription factors and nucleases for the targeted regulation and modification of endogenous genes.\n
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