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Your search keyword '"Joseph H Lubin"' showing total 3 results
Start Over Author "Joseph H Lubin" Topic 0303 health sciences
3 results on '"Joseph H Lubin"'

1. Virtual Boot Camp: <scp>COVID</scp> ‐19 evolution and structural biology

Author

Christine Zardecki, Paul Craig, Sagar D. Khare, Jennifer Jiang, Siobain Duffy, Stephen K. Burley, Jitendra Singh, Yana Bromberg, Julia R. Koeppe, Jay A. Tischfield, Stephen A. Mills, Shuchismita Dutta, Rebecca Roberts, Bonnie L. Hall, Vidur Sarma, Lingjun Xie, Brian P. Hudson, Michael J. Pikaart, and Joseph H Lubin

Subjects
2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Biology, Biochemistry, Education, Distance, Evolution, Molecular, 03 medical and health sciences, Pandemic, Humans, Pandemics, Molecular Biology, Coronavirus 3C Proteases, 030304 developmental biology, Covid‐19, Boot camp, 0303 health sciences, SARS-CoV-2, Extramural, 05 social sciences, COVID-19, Computational Biology, 050301 education, Virology, Structural biology, Curriculum, 0503 education
Published
2020
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2. Novel sampling strategies and a coarse-grained score function for docking homomers, flexible heteromers, and oligosaccharides using Rosetta in CAPRI Rounds 37–45

Author

Shourya S. Roy Burman, Morgan L. Nance, Jeliazko R. Jeliazkov, Jason W. Labonte, Jeffrey J. Gray, Joseph H. Lubin, and Naireeta Biswas

Subjects
Protein Conformation, alpha-Helical, Computer science, Oligosaccharides, Score, Ligands, Biochemistry, Article, 03 medical and health sciences, Critical Assessment of Prediction of Interactions, Structural Biology, Protein Interaction Mapping, Humans, Macromolecular docking, Protein Interaction Domains and Motifs, Amino Acid Sequence, Molecular Biology, Conformational isomerism, 030304 developmental biology, 0303 health sciences, Binding Sites, 030302 biochemistry & molecular biology, Scoring methods, Proteins, Molecular Docking Simulation, Research Design, Structural Homology, Protein, Docking (molecular), Protein Conformation, beta-Strand, Protein Multimerization, Peptides, Algorithm, Software, Protein Binding, Macromolecule
Abstract

Critical Assessment of PRediction of Interactions (CAPRI) rounds 37 through 45 introduced larger complexes, new macromolecules, and multistage assemblies. For these rounds, we used and expanded docking methods in Rosetta to model 23 target complexes. We successfully predicted 14 target complexes and recognized and refined near-native models generated by other groups for two further targets. Notably, for targets T110 and T136, we achieved the closest prediction of any CAPRI participant. We created several innovative approaches during these rounds. Since round 39 (target 122), we have used the new RosettaDock 4.0, which has a revamped coarse-grained energy function and the ability to perform conformer selection during docking with hundreds of pregenerated protein backbones. Ten of the complexes had some degree of symmetry in their interactions, so we tested Rosetta SymDock, realized its shortcomings, and developed the next-generation symmetric docking protocol, SymDock2, which includes docking of multiple backbones and induced-fit refinement. Since the last CAPRI assessment, we also developed methods for modeling and designing carbohydrates in Rosetta, and we used them to successfully model oligosaccharide-protein complexes in round 41. Although the results were broadly encouraging, they also highlighted the pressing need to invest in (a) flexible docking algorithms with the ability to model loop and linker motions and in (b) new sampling and scoring methods for oligosaccharide-protein interactions.

Published
2019
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3. Macromolecular modeling and design in Rosetta: recent methods and frameworks

Author

Jack Maguire, Ragul Gowthaman, Marion F. Sauer, Georg Kuenze, Tanja Kortemme, Benjamin Basanta, Indigo Chris King, Jens Meiler, Rhiju Das, Ora Schueler-Furman, Nicholas A. Marze, Brandon Frenz, Christoffer Norn, Julia Koehler Leman, Jason W. Labonte, Kala Bharath Pilla, Lei Shi, Sergey Lyskov, Brian D. Weitzner, Nir London, Karen R. Khar, Jaume Bonet, Nawsad Alam, Andreas Scheck, Alexander M. Sevy, Lars Malmström, Thomas Huber, Christopher Bystroff, Lior Zimmerman, Lorna Dsilva, Bruno E. Correia, Roland L. Dunbrack, Sergey Ovchinnikov, Rocco Moretti, Scott Horowitz, Phil Bradley, Frank DiMaio, Noah Ollikainen, Brian Kuhlman, Jeffrey J. Gray, Melanie L. Aprahamian, Andrew Leaver-Fay, Santrupti Nerli, Brian Koepnick, Xingjie Pan, Manasi A. Pethe, Andrew M. Watkins, Summer B. Thyme, Enrique Marcos, Vikram Khipple Mulligan, Hahnbeom Park, Po-Ssu Huang, David K. Johnson, Daniel-Adriano Silva, Patrick Barth, Shannon Smith, Caleb Geniesse, Jason K. Lai, Patrick Conway, Amelie Stein, Jeliazko R. Jeliazkov, David Baker, Dominik Gront, Kalli Kappel, Firas Khatib, Robert Kleffner, Brian J. Bender, Richard Bonneau, Kyle A. Barlow, Joseph H. Lubin, Shourya S. Roy Burman, Nikolaos G. Sgourakis, Yuval Sedan, Ryan E. Pavlovicz, Kristin Blacklock, Seth Cooper, Barak Raveh, Alisa Khramushin, John Karanicolas, Justin B. Siegel, Sharon L. Guffy, Brian G. Pierce, Alex Ford, Darwin Y. Fu, Orly Marcu, Gideon Lapidoth, Brian Coventry, René M. de Jong, Shane O’Conchúir, Thomas W. Linsky, William R. Schief, Rebecca F. Alford, Scott E. Boyken, Sagar D. Khare, Maria Szegedy, Ray Yu-Ruei Wang, Steven M. Lewis, Hamed Khakzad, Timothy M. Jacobs, Frank D. Teets, Lukasz Goldschmidt, Daisuke Kuroda, Steffen Lindert, P. Douglas Renfrew, Yifan Song, Jared Adolf-Bryfogle, Michael S. Pacella, and Aliza B. Rubenstein

Subjects
atomic-accuracy, Models, Molecular, Computer science, Macromolecular Substances, Protein Conformation, Interoperability, computational design, Score, antibody structures, Biochemistry, Article, homing endonuclease specificity, 03 medical and health sciences, Software, Molecular Biology, 030304 developmental biology, 0303 health sciences, business.industry, Proteins, Usability, fold determination, Cell Biology, Molecular Docking Simulation, variable region, Docking (molecular), protein-structure prediction, small-molecule docking, Modeling and design, Peptidomimetics, User interface, Software engineering, business, de-novo design, sparse nmr data, Biotechnology
Abstract

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at ., This Perspective reviews tools developed over the past five years in the macromolecular modeling, docking and design software Rosetta.

Published
2019

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