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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

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Macromolecular modeling and design in Rosetta: recent methods and frameworks.

Julia Koehler Leman^1,2, Brian D Weitzner^3,4,5,6, Steven M Lewis^7,8,9

¹Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA. Julia.koehler.leman@nyu.edu.

|June 3, 2020

Summary

Rosetta software, a powerful tool for macromolecular modeling, has been enhanced with over 80 new methods in the last five years. These updates improve its performance, usability, and interoperability for researchers worldwide.

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Area of Science:

Computational biology
Structural biology
Biochemistry

Background:

Rosetta software is a widely adopted platform for macromolecular modeling, docking, and design.
It has undergone continuous development and extension by a global community for two decades.
Key advantages include high performance and interoperability across diverse modeling tasks.

Purpose of the Study:

To review recent advancements in Rosetta software over the past five years.
To highlight new tools, methods, and improvements.
To provide an overview of the current capabilities and usability of Rosetta.

Main Methods:

Review of tools and methods developed within the last five years.
Analysis of improvements to the Rosetta score function.
Evaluation of enhancements in user interfaces and overall usability.

Main Results:

Over 80 new methods have been incorporated into Rosetta.
Significant improvements have been made to the score function, enhancing modeling accuracy.
User interfaces and usability have been refined for better accessibility and efficiency.

Conclusions:

Rosetta continues to evolve as a leading platform for macromolecular modeling.
Recent developments have expanded its capabilities and improved user experience.
The software remains a valuable and accessible resource for the scientific community.