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RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite

Author

Listed:
  • Sarel J Fleishman
  • Andrew Leaver-Fay
  • Jacob E Corn
  • Eva-Maria Strauch
  • Sagar D Khare
  • Nobuyasu Koga
  • Justin Ashworth
  • Paul Murphy
  • Florian Richter
  • Gordon Lemmon
  • Jens Meiler
  • David Baker

Abstract

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.

Suggested Citation

  • Sarel J Fleishman & Andrew Leaver-Fay & Jacob E Corn & Eva-Maria Strauch & Sagar D Khare & Nobuyasu Koga & Justin Ashworth & Paul Murphy & Florian Richter & Gordon Lemmon & Jens Meiler & David Baker, 2011. "RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-10, June.
    • Handle: RePEc:plo:pone00:0020161
    DOI: 10.1371/journal.pone.0020161
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    References listed on IDEAS

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    1. Summer B. Thyme & Jordan Jarjour & Ryo Takeuchi & James J. Havranek & Justin Ashworth & Andrew M. Scharenberg & Barry L. Stoddard & David Baker, 2009. "Exploitation of binding energy for catalysis and design," Nature, Nature, vol. 461(7268), pages 1300-1304, October.
    2. Justin Ashworth & James J. Havranek & Carlos M. Duarte & Django Sussman & Raymond J. Monnat & Barry L. Stoddard & David Baker, 2006. "Computational redesign of endonuclease DNA binding and cleavage specificity," Nature, Nature, vol. 441(7093), pages 656-659, June.
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    1. Jared Adolf-Bryfogle & Oleks Kalyuzhniy & Michael Kubitz & Brian D Weitzner & Xiaozhen Hu & Yumiko Adachi & William R Schief & Roland L Dunbrack Jr., 2018. "RosettaAntibodyDesign (RAbD): A general framework for computational antibody design," PLOS Computational Biology, Public Library of Science, vol. 14(4), pages 1-38, April.
    2. Daniel Ellis & Julia Lederhofer & Oliver J. Acton & Yaroslav Tsybovsky & Sally Kephart & Christina Yap & Rebecca A. Gillespie & Adrian Creanga & Audrey Olshefsky & Tyler Stephens & Deleah Pettie & Mic, 2022. "Structure-based design of stabilized recombinant influenza neuraminidase tetramers," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    3. Julia Skokowa & Birte Hernandez Alvarez & Murray Coles & Malte Ritter & Masoud Nasri & Jérémy Haaf & Narges Aghaallaei & Yun Xu & Perihan Mir & Ann-Christin Krahl & Katherine W. Rogers & Kateryna Maks, 2022. "A topological refactoring design strategy yields highly stable granulopoietic proteins," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    4. Vishruth Mullapudi & Jaime Vaquer-Alicea & Vaibhav Bommareddy & Anthony R. Vega & Bryan D. Ryder & Charles L. White & Marc. I. Diamond & Lukasz A. Joachimiak, 2023. "Network of hotspot interactions cluster tau amyloid folds," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    5. Thomas W. Linsky & Kyle Noble & Autumn R. Tobin & Rachel Crow & Lauren Carter & Jeffrey L. Urbauer & David Baker & Eva-Maria Strauch, 2022. "Sampling of structure and sequence space of small protein folds," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    6. Kristin J. Adolfsen & Isolde Callihan & Catherine E. Monahan & Per Jr. Greisen & James Spoonamore & Munira Momin & Lauren E. Fitch & Mary Joan Castillo & Lindong Weng & Lauren Renaud & Carl J. Weile &, 2021. "Improvement of a synthetic live bacterial therapeutic for phenylketonuria with biosensor-enabled enzyme engineering," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    7. Zachary R. Crook & Gregory P. Sevilla & Pamela Young & Emily J. Girard & Tinh-Doan Phi & Monique L. Howard & Jason Price & James M. Olson & Natalie W. Nairn, 2024. "CYpHER: catalytic extracellular targeted protein degradation with high potency and durable effect," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    8. Karen J. Gonzalez & Jiachen Huang & Miria F. Criado & Avik Banerjee & Stephen M. Tompkins & Jarrod J. Mousa & Eva-Maria Strauch, 2024. "A general computational design strategy for stabilizing viral class I fusion proteins," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    9. Tamuka M. Chidyausiku & Soraia R. Mendes & Jason C. Klima & Marta Nadal & Ulrich Eckhard & Jorge Roel-Touris & Scott Houliston & Tibisay Guevara & Hugh K. Haddox & Adam Moyer & Cheryl H. Arrowsmith & , 2022. "De novo design of immunoglobulin-like domains," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    10. Jaume Bonet & Sarah Wehrle & Karen Schriever & Che Yang & Anne Billet & Fabian Sesterhenn & Andreas Scheck & Freyr Sverrisson & Barbora Veselkova & Sabrina Vollers & Roxanne Lourman & Mélanie Villard , 2018. "Rosetta FunFolDes – A general framework for the computational design of functional proteins," PLOS Computational Biology, Public Library of Science, vol. 14(11), pages 1-30, November.
    11. Jonathan Yaacov Weinstein & Carlos Martí-Gómez & Rosalie Lipsh-Sokolik & Shlomo Yakir Hoch & Demian Liebermann & Reinat Nevo & Haim Weissman & Ekaterina Petrovich-Kopitman & David Margulies & Dmitry I, 2023. "Designed active-site library reveals thousands of functional GFP variants," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    12. P. Konstantin Richter & Paula Blázquez-Sánchez & Ziyue Zhao & Felipe Engelberger & Christian Wiebeler & Georg Künze & Ronny Frank & Dana Krinke & Emanuele Frezzotti & Yuliia Lihanova & Patricia Falken, 2023. "Structure and function of the metagenomic plastic-degrading polyester hydrolase PHL7 bound to its product," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    13. Edward King & Sarah Maxel & Yulai Zhang & Karissa C. Kenney & Youtian Cui & Emma Luu & Justin B. Siegel & Gregory A. Weiss & Ray Luo & Han Li, 2022. "Orthogonal glycolytic pathway enables directed evolution of noncanonical cofactor oxidase," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    14. Xinlei Zhuang & Zhe Wang & Jiansheng Fan & Xuefei Bai & Yingchun Xu & James J. Chou & Tingjun Hou & Shuqing Chen & Liqiang Pan, 2022. "Structure-guided and phage-assisted evolution of a therapeutic anti-EGFR antibody to reverse acquired resistance," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    15. Diego del Alamo & Kevin L Jagessar & Jens Meiler & Hassane S Mchaourab, 2021. "Methodology for rigorous modeling of protein conformational changes by Rosetta using DEER Distance Restraints," PLOS Computational Biology, Public Library of Science, vol. 17(6), pages 1-18, June.
    16. Sowmiya Palani & Yuka Machida & Julia R. Alvey & Vandana Mishra & Allison L. Welter & Gaofeng Cui & Benoît Bragantini & Maria Victoria Botuyan & Anh T. Q. Cong & Georges Mer & Matthew J. Schellenberg , 2024. "Dimerization-dependent serine protease activity of FAM111A prevents replication fork stalling at topoisomerase 1 cleavage complexes," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    17. Jorge Roel-Touris & Marta Nadal & Enrique Marcos, 2023. "Single-chain dimers from de novo immunoglobulins as robust scaffolds for multiple binding loops," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    18. Alexander M Sevy & Tim M Jacobs & James E Crowe Jr. & Jens Meiler, 2015. "Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-23, July.

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