Help Cure Muscular Dystrophy Explained

Help Cure Muscular Dystrophy is a volunteer computing project that runs on the BOINC platform.

It is a joint effort of the French muscular dystrophy charity, L'Association française contre les myopathies;^[1] and L'Institut de biologie moléculaire et cellulaire (Molecular and Cellular Biology Institute).

Project purpose

Help Cure Muscular Dystrophy studies the function of various proteins that are produced by the two hundred genes known to be involved in the production of neuromuscular proteins by modelling the protein-protein interactions of the forty thousand relevant proteins that are listed in the Protein Data Bank. More specifically, it models how a protein would be affected when another protein or a ligand docks with it.^[2]

Scientific publications

• Decrypting protein surfaces by combining evolution, geometry, and molecular docking. Proteins: Structure, Function, and Bioinformatics (2019). ^[3]
• Hidden partners: Using cross-docking calculations to predict binding sites for proteins with multiple interactions. Proteins: Structure, Function, and Bioinformatics (2018).^[4]
• Protein social behavior makes a stronger signal for partner identification than surface geometry. Proteins: Structure, Function, and Bioinformatics (2017).^[5]
• Great interactions: How binding incorrect partners can teach us about protein recognition and function. Proteins: Structure, Function, and Bioinformatics (2016).^[6]
• Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information. PLOS Computational Biology (2013).^[7]
• From Dedicated Grid to Volunteer Grid: Large Scale Execution of a Bioinformatics Application. Journal of Grid Computing (2009).^[8]
• Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling. PLOS Computational Biology (2009).^[9]
• Identification of Protein Interaction Partners and Protein–Protein Interaction Sites. Journal of Molecular Biology (2008).^[10]

See also

• BOINC
• List of volunteer computing projects
• Muscular dystrophy
• World Community Grid

External links

• Help Cure Muscular Dystrophy

Notes and References

1. Web site: French Muscular Dystrophy Association . 2009-10-30 . https://web.archive.org/web/20091201174933/http://www.afm-france.org/afm-english_version/ . 2009-12-01 . dead .
2. Web site: Help Cure Muscular Dystrophy - Phase 2 Research World Community Grid . 2022-09-10 . www.worldcommunitygrid.org.
3. Dequeker . Chloé . Laine . Elodie . Carbone . Alessandra . November 2019 . Decrypting protein surfaces by combining evolution, geometry, and molecular docking . Proteins: Structure, Function, and Bioinformatics . en . 87 . 11 . 952–965 . 10.1002/prot.25757 . 31199528 . 6852240 . 0887-3585.
4. Lagarde . Nathalie . Carbone . Alessandra . Sacquin-Mora . Sophie . July 2018 . Hidden partners: Using cross-docking calculations to predict binding sites for proteins with multiple interactions . Proteins: Structure, Function, and Bioinformatics . en . 86 . 7 . 723–737 . 10.1002/prot.25506. 29664226 . 4900895 .
5. Laine . Elodie . Carbone . Alessandra . January 2017 . Protein social behavior makes a stronger signal for partner identification than surface geometry: Protein Social Behavior . Proteins: Structure, Function, and Bioinformatics . en . 85 . 1 . 137–154 . 10.1002/prot.25206. 27802579 . 5242317 .
6. Vamparys . Lydie . Laurent . Benoist . Carbone . Alessandra . Sacquin‐Mora . Sophie . October 2016 . Great interactions: How binding incorrect partners can teach us about protein recognition and function . Proteins: Structure, Function, and Bioinformatics . en . 84 . 10 . 1408–1421 . 10.1002/prot.25086 . 27287388 . 5516155 . 0887-3585.
7. Lopes . Anne . Sacquin-Mora . Sophie . Dimitrova . Viktoriya . Laine . Elodie . Ponty . Yann . Carbone . Alessandra . 2013-12-05 . Kann . Maricel . Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information . PLOS Computational Biology . en . 9 . 12 . e1003369 . 10.1371/journal.pcbi.1003369 . 24339765 . 3854762 . 2013PLSCB...9E3369L . 5880229 . 1553-7358 . free .
8. Bertis . Viktors . Bolze . Raphaël . Desprez . Frédéric . Reed . Kevin . December 2009 . From Dedicated Grid to Volunteer Grid: Large Scale Execution of a Bioinformatics Application . Journal of Grid Computing . en . 7 . 4 . 463–478 . 10.1007/s10723-009-9130-7 . 22791104 . 1570-7873.
9. Engelen . Stefan . Trojan . Ladislas A. . Sacquin-Mora . Sophie . Lavery . Richard . Carbone . Alessandra . 2009-01-23 . Levitt . Michael . Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling . PLOS Computational Biology . en . 5 . 1 . e1000267 . 10.1371/journal.pcbi.1000267 . 19165315 . 2613531 . 2009PLSCB...5E0267E . 12292219 . 1553-7358 . free .
10. Sacquin-Mora . Sophie . Carbone . Alessandra . Lavery . Richard . October 2008 . Identification of Protein Interaction Partners and Protein–Protein Interaction Sites . Journal of Molecular Biology . en . 382 . 5 . 1276–1289 . 10.1016/j.jmb.2008.08.002. 18708070 .