The Rosetta Molecular Modeling Suite, originally developed in the Baker Laboratory at the University of Washington, is a powerful software package widely used for protein structure prediction and protein design. Since its inception in the late 1990s, Rosetta has transformed into a versatile cornerstone of structural biology, with ongoing development efforts spanning numerous academic labs worldwide. Its latest iterations showcase Rosetta’s enduring spirit of innovation, leveraging cutting-edge artificial intelligence to pioneer novel approaches to de novo protein engineering.

Origins and Early Development (Late 1990s - Early 2000s):

  • The development of Rosetta began in the late 1990s under the leadership of Dr. David Baker at the University of Washington.
    • The first publication: K T Simons 1, C Kooperberg, E Huang, D Baker. Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J Mol Biol. 1997 Apr 25;268(1):209-25.
  • The initial focus of Rosetta was on ab initio protein structure prediction, aiming to predict protein structures from amino acid sequences alone.
  • In the early 2000s, the Baker laboratory made significant advancements in protein structure prediction using Rosetta, including the successful prediction of the structures of small proteins.

Expansion into Protein Design and Modeling Versatility (Mid-2000s - Early 2010s):

  • Building upon its success in protein structure prediction, Rosetta expanded its capabilities to include protein design and protein-protein docking.
  • With multiple academic labs specializing in Rosetta’s development for broad applications, its modeling protocols have become increasingly versatile, facilitating the optimization, scoring, and design of various biomolecular structures such as enzymes, antibodies, membrane proteins, and custom conformations.

Widespread Adoption and Community Contributions (2010s - Present):

  • Throughout the 2010s, Rosetta gained widespread adoption in both academic and industrial settings, becoming a standard tool in structural biology and drug discovery.
  • The RosettaCommons, an international consortium of researchers, was established to foster collaboration and community-driven development of Rosetta.
  • Rosetta continued to evolve, with new modules and algorithms developed for a wide range of applications, including antibody design, enzyme design, and small molecule docking.
  • In 2020, DeepMind’s AlphaFold, a deep learning-based method for protein structure prediction, gained widespread attention for its remarkable accuracy. The Rosetta community learned from its AI architecture and improved upon it with RosettaFold which can now do structure prediction with non-protein atoms such as nucleotides, metals, and small molecules.

Current and Future Directions:

  • In 2024, The RosettaCommons created Levitate Bio, which provides easy-to-use, automated Rosetta protocols available on a subscription basis and offers custom modeling or software development. Levitate is the for-profit arm of the non-profit organization and will help fund continued development of modeling software and support the Rosetta community.
  • Rosetta continues to be actively developed and maintained by the Baker laboratory and the broader RosettaCommons community.
  • Ongoing research efforts focus on improving the accuracy and efficiency of protein structure prediction, expanding the scope of protein design with artificial intelligence, and advancing our understanding of protein function and interaction.

As the field of structural biology continues to evolve, Rosetta is poised to play a central role in addressing key challenges and unlocking new opportunities in drug discovery, biotechnology, and basic science. The RosettaCommons is committed to scientific excellence, supporting the hundreds of active researchers, and providing fundamental tools for thousands of software users.