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{{Infobox software
| name                = Rosetta@home
| logo                = Rosettahome.png
| logo caption        = Rosetta@home logo
| screenshot          = Rosetta.gif
| caption              = Rosetta@home screensaver
| status              = Active
| category            = Bioinformatics, Protein structure prediction, Distributed computing
| compute              = CPU
| dependencies        = [[wikipedia:Berkeley Open Infrastructure for Network Computing|BOINC]]
| developer            = Baker Laboratory
| author              = [[wikipedia:David Baker (biochemist)|David Baker]] and collaborators
| sponsor              = [[wikipedia:University of Washington|University of Washington]]
| maintainer          = Baker Laboratory and RosettaCommons
| released            = {{Start date and age|2005|06|06}}
| repository          = https://github.com/RosettaCommons
| programming language = C++, C
| operating system    = Windows, Linux, macOS
| size                = Varies by work unit
| stats as of          = {{Start date and age|2026|05|22}}
| average performance  = Several PFLOPS distributed across volunteer hosts
| active users        = 25000
| total users          = 1000000
| active hosts        = 45000
| total hosts          = 3000000
| cpu performance      = Large-scale distributed CPU processing
| website              = https://boinc.bakerlab.org/rosetta/
| license              = Mixed proprietary and academic research licensing
}}
[[File:{{#setmainimage:Rosettahome.png}}|alt=Rosetta@home logo|center|frameless]]
[[File:{{#setmainimage:Rosettahome.png}}|alt=Rosetta@home logo|center|frameless]]


[https://boinc.bakerlab.org/rosetta/ '''''Rosetta@home'''''] is a '''''[[wikipedia:Volunteer computing|volunteer distributed computing]]''''' project that uses [https://boinc.berkeley.edu/ '''''BOINC'''''] to help researchers predict and design the three-dimensional structures of proteins. The project is operated by the [[wikipedia:David Baker (biochemist)|Baker Laboratory]] at the [[wikipedia:University of Washington|University of Washington]] and is one of the best known and most scientifically productive projects in the BOINC ecosystem.<ref>https://boinc.bakerlab.org/rosetta/</ref><ref>https://en.wikipedia.org/wiki/Rosetta@home</ref>
[https://boinc.bakerlab.org/rosetta/ '''''Rosetta@home'''''] is a '''[[wikipedia:Volunteer computing|volunteer distributed computing]]''' project that uses the [[wikipedia:Berkeley Open Infrastructure for Network Computing|BOINC]] platform to help researchers predict and design the three-dimensional structures of proteins. The project is operated by the [[wikipedia:David Baker (biochemist)|Baker Laboratory]] at the [[wikipedia:University of Washington|University of Washington]] in Seattle, Washington, and is considered one of the most scientifically successful and widely recognized BOINC projects.<ref>{{cite web|url=https://boinc.bakerlab.org/rosetta/|title=Rosetta@home}}</ref><ref>{{cite web|url=https://en.wikipedia.org/wiki/Rosetta@home|title=Rosetta@home}}</ref>
 
Rosetta@home officially launched in 2005 as a public volunteer computing extension of the Rosetta protein modeling software suite. Volunteers donate spare CPU resources from personal computers to perform large-scale molecular simulations involving protein folding, protein docking, and protein design.<ref>{{cite journal|last=Das|first=Rhiju|last2=Baker|first2=David|title=Macromolecular Modeling with Rosetta|journal=Annual Review of Biochemistry|year=2008|volume=77|pages=363–382|doi=10.1146/annurev.biochem.77.062906.171838}}</ref>
 
== Overview ==


[[File:Rosetta.gif|alt=Rosetta@home screensaver|Rosetta@home screensaver showing protein folding simulations]]
Proteins are biological macromolecules composed of amino acid chains that fold into highly complex three-dimensional structures. The function of a protein depends heavily on its final folded conformation. Predicting how proteins fold from their amino acid sequence remains one of the major challenges in computational biology and biochemistry.<ref>{{cite web|url=https://en.wikipedia.org/wiki/Protein_folding|title=Protein folding}}</ref>


Rosetta@home officially launched in 2005 as a successor to earlier distributed protein-folding experiments and quickly became one of the largest volunteer computing projects in the world. The project allows ordinary volunteers to donate spare CPU power from home computers in order to perform extremely large numbers of protein-folding calculations that would otherwise require enormous supercomputing resources.<ref>https://en.wikipedia.org/wiki/Rosetta@home</ref>
Rosetta@home enables volunteers around the world to contribute computing power toward:


== Why Rosetta@home? ==
* Protein structure prediction
* Protein docking
* Protein interface analysis
* Computational enzyme design
* Vaccine and therapeutic research
* Antiviral protein development
* Cancer-related protein research
* Research into neurodegenerative diseases


Proteins are essential biological molecules responsible for nearly every process inside living cells. Understanding how proteins fold into their complex three-dimensional structures is one of the central challenges of modern biology. Incorrectly folded proteins are associated with many diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, cystic fibrosis, and certain cancers.<ref>https://en.wikipedia.org/wiki/Protein_folding</ref>
Many diseases are associated with protein misfolding or protein interaction failures, including:
 
* [[wikipedia:Alzheimer's disease|Alzheimer's disease]]
* [[wikipedia:Parkinson's disease|Parkinson's disease]]
* [[wikipedia:Huntington's disease|Huntington's disease]]
* [[wikipedia:Cystic fibrosis|Cystic fibrosis]]
* Certain forms of cancer
 
== Scientific basis ==
 
Protein folding is governed by thermodynamics and molecular interactions. Rosetta software attempts to locate energetically favorable conformations by minimizing an approximate free-energy function.
 
The project commonly uses computational approaches including:
 
* Monte Carlo sampling
* Energy minimization
* Fragment assembly
* Comparative modeling
* Ab initio structure prediction
* Protein docking simulations
*Machine-learning-assisted scoring functions


Rosetta@home enables volunteers worldwide to contribute computing power toward:
The Rosetta energy function attempts to minimize the free energy of candidate structures:


* Predicting protein structures
<math>E_{total} = \sum_i w_iE_i</math>
* Designing entirely new proteins
* Developing vaccines
* Creating antiviral therapies
* Studying cancer-related proteins
* Research into Alzheimer's disease and other neurodegenerative disorders
* Understanding immune system interactions


[[File:Protein_structure_examples.png|thumb|Examples of protein structures from Wikipedia]]
where:


During the COVID-19 pandemic, Rosetta@home received worldwide attention for helping researchers design proteins capable of binding to the SARS-CoV-2 spike protein. Some designed proteins showed promise as antiviral therapeutics and diagnostic tools.<ref>https://www.ipd.uw.edu/covid-19/</ref><ref>https://www.nature.com/articles/s41586-021-03819-2</ref>
* <math>E_i</math> represents individual energy terms
* <math>w_i</math> represents weighting coefficients


== Goal ==
The project also uses stochastic Monte Carlo methods that accept or reject conformational changes according to probabilities derived from statistical thermodynamics:


The primary goal of Rosetta@home is to determine and design accurate three-dimensional protein structures using computational methods. Researchers use the Rosetta software suite to explore millions of possible protein conformations in search of the most energetically favorable structures.<ref>https://www.rosettacommons.org/</ref>
<math>P = e^{-\Delta E / kT}</math>


The project also aims to:
where:


* Design new proteins not found in nature
* <math>\Delta E</math> is the change in energy
* Improve understanding of protein folding
* <math>k</math> is the Boltzmann constant
* Develop new therapeutics and vaccines
* <math>T</math> is temperature
* Advance computational biology and bioinformatics
* Provide open scientific tools to the research community


[[File:Protein_folding.png|thumb|Illustration of protein folding pathways]]
[[File:Protein_structure_examples.png|thumb|Examples of protein structures]]


== History ==
== History ==


Rosetta@home was created by researchers from the Baker Laboratory led by Professor [[wikipedia:David Baker (biochemist)|David Baker]]. The project became publicly available through the BOINC platform in 2005 and rapidly attracted volunteers from around the world.<ref>https://en.wikipedia.org/wiki/Rosetta@home</ref>
The Rosetta software project originated during the late 1990s at the Baker Laboratory under the leadership of Professor [[wikipedia:David Baker (biochemist)|David Baker]]. Early Rosetta software focused on ab initio protein structure prediction and rapidly gained recognition within computational biology research communities.<ref>{{cite journal|last=Simons|first=K. T.|last2=Kooperberg|first2=C.|last3=Huang|first3=E.|last4=Baker|first4=D.|title=Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions|journal=Journal of Molecular Biology|year=1997|volume=268|issue=1|pages=209–225|doi=10.1006/jmbi.1997.0959}}</ref>


The Rosetta software itself dates back to the late 1990s and evolved into one of the world's leading protein modeling platforms. Rosetta has since been used by thousands of researchers and institutions globally.<ref>https://www.rosettacommons.org/about</ref>
Rosetta@home became publicly available through BOINC in 2005 and quickly attracted a large international volunteer community. The project became one of the flagship scientific applications of the BOINC ecosystem during the late 2000s and early 2010s.<ref>{{cite web|url=https://web.archive.org/web/*/https://boinc.bakerlab.org/rosetta/|title=Archived Rosetta@home pages}}</ref>


The project experienced major growth during:
Major growth periods occurred during:
* The CASP protein structure prediction competitions
 
* CASP protein structure prediction competitions
* Influenza and HIV research initiatives
* Influenza and HIV research initiatives
* Development of computational protein design methods
* The COVID-19 pandemic
* The COVID-19 pandemic
* Major breakthroughs in computational protein design


Discussion threads preserved on the [[wikipedia:Wayback Machine|Wayback Machine]] and historical BOINC forums show Rosetta@home becoming one of the flagship BOINC projects during the late 2000s and early 2010s, often competing near the top of global BOINC statistics rankings.<ref>https://web.archive.org/web/*/https://boinc.bakerlab.org/rosetta/</ref>
== CASP participation ==
 
Rosetta methods achieved significant success in the [[wikipedia:Critical Assessment of protein Structure Prediction|CASP]] competitions, which evaluate computational protein structure prediction methods using experimentally determined structures not yet publicly released.
 
Performance in CASP competitions helped establish Rosetta as one of the leading protein prediction frameworks in computational biology.<ref>{{cite journal|last=Moult|first=John|title=Critical assessment of methods of protein structure prediction (CASP): Round XIII|journal=Proteins|year=2019|volume=87|issue=12|pages=1011–1020|doi=10.1002/prot.25823}}</ref>


== Methods ==
== Methods ==


Rosetta@home distributes small computational tasks known as ''work units'' to volunteer computers. Each work unit explores different possible shapes or interactions for a protein molecule.
[[File:PDB 1p5t EBI.jpg|thumb|Protein docking simulation example]]
 
Rosetta@home distributes small computational tasks known as ''work units'' to volunteer computers through BOINC. Each work unit evaluates different possible conformations or molecular interactions involving proteins.
 
The Rosetta software suite includes multiple scientific modules:
 
=== Ab initio structure prediction ===
 
Ab initio methods attempt to predict protein structures directly from amino acid sequence without relying entirely on experimentally solved templates.


The Rosetta software applies:
=== Protein docking ===
* Monte Carlo sampling
 
* Energy minimization algorithms
Docking simulations attempt to determine how proteins interact with other proteins or molecules. RosettaDock is one major Rosetta subsystem dedicated to these calculations.<ref>{{cite journal|last=Gray|first=Jeffrey J.|title=Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations|journal=Journal of Molecular Biology|year=2003|volume=331|issue=1|pages=281–299|doi=10.1016/S0022-2836(03)00670-3}}</ref>
* Fragment assembly methods
 
* Comparative modeling
=== Protein design ===
* Protein docking simulations
* De novo protein design


[[File:PDB 1p5t EBI.jpg|thumb|Protein docking simulation example]]
RosettaDesign enables researchers to computationally create entirely new proteins not found in nature. These methods have been used to design enzymes, binders, and antiviral mini-proteins.<ref>{{cite journal|last=Kuhlman|first=Brian|title=Design of a novel globular protein fold with atomic-level accuracy|journal=Science|year=2003|volume=302|issue=5649|pages=1364–1368|doi=10.1126/science.1089427}}</ref>


Each volunteer computer independently calculates possible structures and returns the results to project servers, where researchers analyze the data and identify promising protein conformations.<ref>https://boinc.bakerlab.org/rosetta/rah_about.php</ref>
=== Fragment assembly ===


Unlike projects focused solely on raw computational throughput, Rosetta@home often performs highly complex scientific simulations requiring sophisticated modeling techniques and extensive statistical analysis.
Many Rosetta methods use libraries of known protein fragments to assemble candidate structures during conformational searches.


== COVID-19 research ==
== COVID-19 research ==


Rosetta@home became heavily involved in COVID-19 research beginning in early 2020. Volunteers worldwide donated massive amounts of computing power to support urgent pandemic-related research efforts.
[[File:Protein_folding.png|thumb|Illustration of protein folding pathways]]
 
Rosetta@home became heavily involved in COVID-19 research beginning in early 2020. Public awareness of the project increased dramatically during the pandemic as volunteers contributed substantial additional computing power to pandemic-related research.<ref>{{cite web|url=https://www.ipd.uw.edu/covid-19/|title=Institute for Protein Design COVID-19 research}}</ref>


Researchers used Rosetta to:
Researchers used Rosetta to:
* Design mini-proteins that bind the coronavirus spike protein
 
* Design mini-proteins that bind the SARS-CoV-2 spike protein
* Study viral protein structures
* Study viral protein structures
* Develop potential antiviral therapeutics
* Develop candidate antiviral therapeutics
* Assist vaccine-related research
* Assist vaccine-related molecular research
 
One major achievement involved the creation of synthetic mini-proteins capable of strongly binding to the SARS-CoV-2 spike protein in laboratory studies.<ref>{{cite journal|last=Cao|first=Longxing|title=De novo design of picomolar SARS-CoV-2 miniprotein inhibitors|journal=Nature|year=2021|volume=595|issue=7867|pages=551–556|doi=10.1038/s41586-021-03819-2}}</ref>
 
The project received significant international media coverage during this period, causing major increases in volunteer participation and BOINC activity.<ref>{{cite web|url=https://www.reddit.com/r/BOINC/|title=r/BOINC discussions}}</ref>
 
== RosettaCommons ==
 
[[File:SARS-CoV-2_without_background.png|thumb|Illustration of SARS-CoV-2]]
 
The broader Rosetta software ecosystem is maintained by [[wikipedia:RosettaCommons|RosettaCommons]], an international consortium of universities and research institutions collaborating on computational structural biology software development.<ref>{{cite web|url=https://www.rosettacommons.org/about|title=About RosettaCommons}}</ref>
 
RosettaCommons includes contributors from:
 
* Universities
* Medical research institutes
* National laboratories
* International research organizations
 
The collaboration supports development of:


[[File:SARS-CoV-2_without_background.png|thumb|SARS-CoV-2 illustration from Wikipedia]]
* Rosetta biomolecular modeling software
* Educational resources
* Scientific workshops
* Protein design tools
* Molecular simulation frameworks


One highly publicized achievement involved the creation of synthetic mini-proteins capable of neutralizing SARS-CoV-2 in laboratory experiments.<ref>https://www.nature.com/articles/s41586-021-03819-2</ref>
== Project team and sponsors ==


The project received substantial media coverage during this period, leading to large increases in volunteer participation from around the world.<ref>https://www.reddit.com/r/BOINC/</ref>
[[File:University of Washington Red Square golden hour Seattle Washington.jpg|thumb|University of Washington campus]]


== Project team / Sponsors ==
Rosetta@home is operated primarily by the [https://www.bakerlab.org/ Baker Laboratory] at the [[wikipedia:University of Washington|University of Washington]] in Seattle, Washington, United States.


Rosetta@home is operated by the [https://www.bakerlab.org/ Baker Laboratory] at the [[wikipedia:University of Washington|University of Washington]] in [[wikipedia:Seattle|Seattle]], [[wikipedia:Washington (state)|Washington]], USA.
Key researchers and contributors include:


Key figures associated with the project include:
* [[wikipedia:David Baker (biochemist)|David Baker]]
* [[wikipedia:David Baker (biochemist)|David Baker]]
* RosettaCommons collaborators
* RosettaCommons scientists
* Researchers from multiple international institutions
* Researchers from multiple international institutions


[[File:University of Washington Red Square golden hour Seattle Washington.jpg|thumb|University of Washington campus]]
The project has collaborated with numerous scientific organizations and research groups worldwide.
 
The broader Rosetta development community, known as RosettaCommons, includes scientists from universities and research institutes worldwide.<ref>https://www.rosettacommons.org/</ref>


== System requirements ==
== System requirements ==


Rosetta@home primarily supports:
Rosetta@home primarily supports:
* Windows
 
* Microsoft Windows
* Linux
* Linux
* macOS
* macOS


The project mainly uses CPU processing rather than GPU acceleration. Work units can be memory intensive and may run for several hours depending on system performance and user configuration.
The project mainly performs CPU-based scientific calculations rather than GPU acceleration.


BOINC allows volunteers to:
Typical work units may:
* Limit CPU usage
 
* Pause computing during active computer use
* Run for several hours
* Restrict network activity
* Use moderate to high amounts of system memory
* Control temperature and power settings
* Require stable internet access for uploading results
* Generate checkpoint files for interrupted computations
 
BOINC allows volunteers to configure:
 
* CPU utilization limits
* Temperature and power management
* Network transfer schedules
* Runtime limits
* Disk usage quotas


== Community ==
== Community ==


Rosetta@home has maintained a large and active volunteer community for many years. Volunteers participate through:
[[File:Rosetta.gif|alt=Rosetta@home screensaver|thumb|Rosetta@home screensaver showing protein folding simulations]]
 
Rosetta@home has maintained a large international volunteer community since its launch. Volunteers participate through:
 
* BOINC teams
* BOINC teams
* Project message boards
* Project message boards
* Reddit communities
* Reddit communities
* Distributed computing forums
* Distributed computing forums
* Statistics websites
* Statistics aggregation websites


[[File:BOINC Logo custom.png|thumb|BOINC logo]]
Popular community resources include:


Many volunteers join competitive BOINC teams that contribute large amounts of computing power and participate in distributed computing events and challenges.
The project is frequently discussed on:
* Reddit BOINC communities
* BOINCstats
* BOINCstats
* Free-DC
* Free-DC
* Team forums
* Team AnandTech
* Historical distributed computing communities archived online
* Reddit BOINC communities
* Historical BOINC forums


== Scientific results ==
The project regularly participates in distributed computing competitions and community events organized by BOINC teams.
 
== Scientific impact ==
 
Rosetta@home has contributed to numerous scientific advances involving:


Rosetta@home has contributed to numerous scientific breakthroughs in:
* Protein structure prediction
* Protein structure prediction
* Protein design
* Protein engineering
* Enzyme engineering
* Computational enzymology
* Vaccine development
* Antiviral therapeutic development
* Viral research
* Vaccine research
* Computational biology
* Structural bioinformatics


Notable accomplishments include:
Notable achievements include:
* Successful participation in CASP competitions
 
* Strong performance in CASP competitions
* Development of novel synthetic proteins
* Development of novel synthetic proteins
* COVID-19 antiviral protein design
* Advances in computational enzyme design
* Advances in computational enzyme design
* SARS-CoV-2 antiviral binder design
* Contributions to structural biology research


Scientific results:
Scientific publications related to Rosetta@home and Rosetta software are archived through BOINC and RosettaCommons publication databases.<ref>{{cite web|url=https://boinc.berkeley.edu/pubs.php#Rosetta@home|title=BOINC scientific publications}}</ref>
* https://boinc.berkeley.edu/pubs.php#Rosetta@home


[[File:Protein_structure.jpg|thumb|Rendered protein structure]]
[[File:Protein_structure.jpg|thumb|Rendered protein structure]]
Line 158: Line 266:
== Scientific publications ==
== Scientific publications ==


Rosetta-related research has produced hundreds of peer-reviewed scientific papers across major journals including ''Nature'', ''Science'', and ''PNAS''.
Rosetta-related research has produced hundreds of peer-reviewed scientific papers in journals including:
 
* ''Nature''
* ''Science''
* ''Proceedings of the National Academy of Sciences''
* ''Journal of Molecular Biology''
* ''Proteins''


Key publication areas include:
Selected publications include:
* Protein folding prediction
 
* Protein interface design
* {{cite journal|last=Simons|first=K. T.|title=Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions|journal=Journal of Molecular Biology|year=1997|doi=10.1006/jmbi.1997.0959}}
* Synthetic protein engineering
* {{cite journal|last=Kuhlman|first=Brian|title=Design of a novel globular protein fold with atomic-level accuracy|journal=Science|year=2003|doi=10.1126/science.1089427}}
* Antiviral therapeutics
* {{cite journal|last=Gray|first=Jeffrey J.|title=Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations|journal=Journal of Molecular Biology|year=2003|doi=10.1016/S0022-2836(03)00670-3}}
* Computational enzyme design
* {{cite journal|last=Das|first=Rhiju|title=Macromolecular Modeling with Rosetta|journal=Annual Review of Biochemistry|year=2008|doi=10.1146/annurev.biochem.77.062906.171838}}
* {{cite journal|last=Cao|first=Longxing|title=De novo design of picomolar SARS-CoV-2 miniprotein inhibitors|journal=Nature|year=2021|doi=10.1038/s41586-021-03819-2}}
 
Additional publication lists:


Scientific publications:
* https://boinc.berkeley.edu/pubs.php#Rosetta@home
* https://boinc.berkeley.edu/pubs.php#Rosetta@home
* https://www.rosettacommons.org/publications
* https://www.rosettacommons.org/publications
== See also ==
* [[wikipedia:BOINC|BOINC]]
* [[wikipedia:Protein folding|Protein folding]]
* [[wikipedia:RosettaCommons|RosettaCommons]]
* [[wikipedia:Distributed computing|Distributed computing]]
* [[wikipedia:Computational biology|Computational biology]]
* [[wikipedia:David Baker (biochemist)|David Baker]]


== External links ==
== External links ==
Line 179: Line 304:
* [https://boinc.berkeley.edu/ BOINC]
* [https://boinc.berkeley.edu/ BOINC]
* [https://boincstats.com/en/stats/145/project/detail BOINCstats project statistics]
* [https://boincstats.com/en/stats/145/project/detail BOINCstats project statistics]
* [https://boinc.berkeley.edu/pubs.php#Rosetta@home BOINC scientific publications]
[[File:BOINC Logo custom.png|BOINC logo|center|frameless|150x150px]]
== References ==
{{Reflist}}

Revision as of 01:30, 23 May 2026


Rosetta@home
Rosetta@home screensaver
Project
StatusActive
CategoryBioinformatics, Protein structure prediction, Distributed computing
ComputeCPU
RequiresBOINC
Development
DeveloperBaker Laboratory
AuthorDavid Baker and collaborators
SponsorUniversity of Washington
MaintainerBaker Laboratory and RosettaCommons
Initial releaseJune 6, 2005  (21 years ago)
Repositoryhttps://github.com/RosettaCommons
Software
Written inC++, C
Operating systemWindows, Linux, macOS
SizeVaries by work unit
BOINC statistics
Stats as ofMay 22, 2026  (0 years ago)
PerformanceSeveral PFLOPS distributed across volunteer hosts
Active users25,000
Total users1,000,000
Active hosts45,000
Total hosts3,000,000
Analytics
CPU performanceLarge-scale distributed CPU processing
Metadata
Websitehttps://boinc.bakerlab.org/rosetta/
LicenseMixed proprietary and academic research licensing

[[File:{{#setmainimage:Rosettahome.png}}|alt=Rosetta@home logo|center|frameless]]

Rosetta@home is a volunteer distributed computing project that uses the BOINC platform to help researchers predict and design the three-dimensional structures of proteins. The project is operated by the Baker Laboratory at the University of Washington in Seattle, Washington, and is considered one of the most scientifically successful and widely recognized BOINC projects.[1][2]

Rosetta@home officially launched in 2005 as a public volunteer computing extension of the Rosetta protein modeling software suite. Volunteers donate spare CPU resources from personal computers to perform large-scale molecular simulations involving protein folding, protein docking, and protein design.[3]

Overview

Proteins are biological macromolecules composed of amino acid chains that fold into highly complex three-dimensional structures. The function of a protein depends heavily on its final folded conformation. Predicting how proteins fold from their amino acid sequence remains one of the major challenges in computational biology and biochemistry.[4]

Rosetta@home enables volunteers around the world to contribute computing power toward:

  • Protein structure prediction
  • Protein docking
  • Protein interface analysis
  • Computational enzyme design
  • Vaccine and therapeutic research
  • Antiviral protein development
  • Cancer-related protein research
  • Research into neurodegenerative diseases

Many diseases are associated with protein misfolding or protein interaction failures, including:

Scientific basis

Protein folding is governed by thermodynamics and molecular interactions. Rosetta software attempts to locate energetically favorable conformations by minimizing an approximate free-energy function.

The project commonly uses computational approaches including:

  • Monte Carlo sampling
  • Energy minimization
  • Fragment assembly
  • Comparative modeling
  • Ab initio structure prediction
  • Protein docking simulations
  • Machine-learning-assisted scoring functions

The Rosetta energy function attempts to minimize the free energy of candidate structures:

Etotal=∑iwiEi

where:

  • Ei represents individual energy terms
  • wi represents weighting coefficients

The project also uses stochastic Monte Carlo methods that accept or reject conformational changes according to probabilities derived from statistical thermodynamics:

P=e−ΔE/kT

where:

  • ΔE is the change in energy
  • k is the Boltzmann constant
  • T is temperature
File:Protein structure examples.png
Examples of protein structures

History

The Rosetta software project originated during the late 1990s at the Baker Laboratory under the leadership of Professor David Baker. Early Rosetta software focused on ab initio protein structure prediction and rapidly gained recognition within computational biology research communities.[5]

Rosetta@home became publicly available through BOINC in 2005 and quickly attracted a large international volunteer community. The project became one of the flagship scientific applications of the BOINC ecosystem during the late 2000s and early 2010s.[6]

Major growth periods occurred during:

  • CASP protein structure prediction competitions
  • Influenza and HIV research initiatives
  • Development of computational protein design methods
  • The COVID-19 pandemic

CASP participation

Rosetta methods achieved significant success in the CASP competitions, which evaluate computational protein structure prediction methods using experimentally determined structures not yet publicly released.

Performance in CASP competitions helped establish Rosetta as one of the leading protein prediction frameworks in computational biology.[7]

Methods

File:PDB 1p5t EBI.jpg
Protein docking simulation example

Rosetta@home distributes small computational tasks known as work units to volunteer computers through BOINC. Each work unit evaluates different possible conformations or molecular interactions involving proteins.

The Rosetta software suite includes multiple scientific modules:

Ab initio structure prediction

Ab initio methods attempt to predict protein structures directly from amino acid sequence without relying entirely on experimentally solved templates.

Protein docking

Docking simulations attempt to determine how proteins interact with other proteins or molecules. RosettaDock is one major Rosetta subsystem dedicated to these calculations.[8]

Protein design

RosettaDesign enables researchers to computationally create entirely new proteins not found in nature. These methods have been used to design enzymes, binders, and antiviral mini-proteins.[9]

Fragment assembly

Many Rosetta methods use libraries of known protein fragments to assemble candidate structures during conformational searches.

COVID-19 research

File:Protein folding.png
Illustration of protein folding pathways

Rosetta@home became heavily involved in COVID-19 research beginning in early 2020. Public awareness of the project increased dramatically during the pandemic as volunteers contributed substantial additional computing power to pandemic-related research.[10]

Researchers used Rosetta to:

  • Design mini-proteins that bind the SARS-CoV-2 spike protein
  • Study viral protein structures
  • Develop candidate antiviral therapeutics
  • Assist vaccine-related molecular research

One major achievement involved the creation of synthetic mini-proteins capable of strongly binding to the SARS-CoV-2 spike protein in laboratory studies.[11]

The project received significant international media coverage during this period, causing major increases in volunteer participation and BOINC activity.[12]

RosettaCommons

File:SARS-CoV-2 without background.png
Illustration of SARS-CoV-2

The broader Rosetta software ecosystem is maintained by RosettaCommons, an international consortium of universities and research institutions collaborating on computational structural biology software development.[13]

RosettaCommons includes contributors from:

  • Universities
  • Medical research institutes
  • National laboratories
  • International research organizations

The collaboration supports development of:

  • Rosetta biomolecular modeling software
  • Educational resources
  • Scientific workshops
  • Protein design tools
  • Molecular simulation frameworks

Project team and sponsors

File:University of Washington Red Square golden hour Seattle Washington.jpg
University of Washington campus

Rosetta@home is operated primarily by the Baker Laboratory at the University of Washington in Seattle, Washington, United States.

Key researchers and contributors include:

  • David Baker
  • RosettaCommons scientists
  • Researchers from multiple international institutions

The project has collaborated with numerous scientific organizations and research groups worldwide.

System requirements

Rosetta@home primarily supports:

  • Microsoft Windows
  • Linux
  • macOS

The project mainly performs CPU-based scientific calculations rather than GPU acceleration.

Typical work units may:

  • Run for several hours
  • Use moderate to high amounts of system memory
  • Require stable internet access for uploading results
  • Generate checkpoint files for interrupted computations

BOINC allows volunteers to configure:

  • CPU utilization limits
  • Temperature and power management
  • Network transfer schedules
  • Runtime limits
  • Disk usage quotas

Community

Error creating thumbnail:
Rosetta@home screensaver showing protein folding simulations

Rosetta@home has maintained a large international volunteer community since its launch. Volunteers participate through:

  • BOINC teams
  • Project message boards
  • Reddit communities
  • Distributed computing forums
  • Statistics aggregation websites

Popular community resources include:

  • BOINCstats
  • Free-DC
  • Team AnandTech
  • Reddit BOINC communities
  • Historical BOINC forums

The project regularly participates in distributed computing competitions and community events organized by BOINC teams.

Scientific impact

Rosetta@home has contributed to numerous scientific advances involving:

  • Protein structure prediction
  • Protein engineering
  • Computational enzymology
  • Antiviral therapeutic development
  • Vaccine research
  • Structural bioinformatics

Notable achievements include:

  • Strong performance in CASP competitions
  • Development of novel synthetic proteins
  • Advances in computational enzyme design
  • SARS-CoV-2 antiviral binder design
  • Contributions to structural biology research

Scientific publications related to Rosetta@home and Rosetta software are archived through BOINC and RosettaCommons publication databases.[14]

File:Protein structure.jpg
Rendered protein structure

Scientific publications

Rosetta-related research has produced hundreds of peer-reviewed scientific papers in journals including:

  • Nature
  • Science
  • Proceedings of the National Academy of Sciences
  • Journal of Molecular Biology
  • Proteins

Selected publications include:

  • Simons, K. T..(1997}).Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. Journal of Molecular Biology. DOI: 10.1006/jmbi.1997.0959.
  • Kuhlman, Brian.(2003}).Design of a novel globular protein fold with atomic-level accuracy. Science. DOI: 10.1126/science.1089427.
  • Gray, Jeffrey J..(2003}).Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. Journal of Molecular Biology. DOI: 10.1016/S0022-2836(03)00670-3.
  • Das, Rhiju.(2008}).Macromolecular Modeling with Rosetta. Annual Review of Biochemistry. DOI: 10.1146/annurev.biochem.77.062906.171838.
  • Cao, Longxing.(2021}).De novo design of picomolar SARS-CoV-2 miniprotein inhibitors. Nature. DOI: 10.1038/s41586-021-03819-2.

Additional publication lists:

See also

External links

BOINC logo
BOINC logo

References

  1. ↑ Rosetta@home.
  2. ↑ Rosetta@home.
  3. ↑ Das, Rhiju.(2008}).Macromolecular Modeling with Rosetta. Annual Review of Biochemistry. pp. 363–382. DOI: 10.1146/annurev.biochem.77.062906.171838.
  4. ↑ Protein folding.
  5. ↑ Simons, K. T..(1997}).Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. Journal of Molecular Biology. pp. 209–225. DOI: 10.1006/jmbi.1997.0959.
  6. ↑ Archived Rosetta@home pages.
  7. ↑ Moult, John.(2019}).Critical assessment of methods of protein structure prediction (CASP): Round XIII. Proteins. pp. 1011–1020. DOI: 10.1002/prot.25823.
  8. ↑ Gray, Jeffrey J..(2003}).Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. Journal of Molecular Biology. pp. 281–299. DOI: 10.1016/S0022-2836(03)00670-3.
  9. ↑ Kuhlman, Brian.(2003}).Design of a novel globular protein fold with atomic-level accuracy. Science. pp. 1364–1368. DOI: 10.1126/science.1089427.
  10. ↑ Institute for Protein Design COVID-19 research.
  11. ↑ Cao, Longxing.(2021}).De novo design of picomolar SARS-CoV-2 miniprotein inhibitors. Nature. pp. 551–556. DOI: 10.1038/s41586-021-03819-2.
  12. ↑ r/BOINC discussions.
  13. ↑ About RosettaCommons.
  14. ↑ BOINC scientific publications.
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