RESEARCH: COVID-19
FOLDING PROJECT #13434 PROFILE
PROJECT TEAM
Manager(s): Prof. John ChoderaInstitution: Memorial Sloan Kettering Cancer Center
Project URL: View Project Website
WORK UNIT INFO
Atoms: 89,709Core: OPENMM_22
Status: Beta
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project uses computer simulations to study how potential drugs might work against the main enzyme of the SARS-CoV-2 virus. The goal is to help researchers quickly identify promising drug candidates for testing. You can even support this open science project by donating!
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
https://www.youtube.com/watch?v=VnyaAmM1nhE
These projects are to assist rapid sprints of relative alchemical free energy calculations for prioritizing compound designs from chemists from the COVID Moonshot for synthesis.
This series of projects simulates the SARS-CoV-2 main viral protease.
These projects collectively cover the entire set of X-ray structures collected by the COVID Moonshot, and more RUNs will be added as new structures are collected.
To learn more about what the Moonshot is and how it came about, you can read our blog post or watch this video.
In addition to helping us prioritize compounds, you can help us purchase more compounds for synthesis at cost from Enamine by sponsoring our GoFundMe page for patent-free open science COVID-19 drug discovery! This is a radical new approach to drug discovery that aims to rapidly produce inexpensive new therapies.
SARS-CoV-2 main viral potease (Mpro) with ligand bound, from the RCSB.
RELATED TERMS GLOSSARY AI BETA
alchemical free energy calculations
Calculations that estimate the energy changes associated with chemical reactions.
Alchemical free energy calculations are a type of computer simulation used in drug discovery to predict how well a molecule will bind to a target protein. This information can be used to prioritize compounds for further testing.
compound design
The process of creating new molecules with desired biological activity.
Compound design is a crucial step in drug discovery, where chemists use their knowledge of molecular structures and biological targets to create new molecules that can interact with specific proteins or pathways in the body. This involves designing compounds that have the right shape, charge, and functional groups to bind effectively to their target.
SARS-CoV-2
The virus that causes COVID-19.
SARS-CoV-2 is a type of coronavirus that emerged in late 2019 and rapidly spread worldwide, causing the COVID-19 pandemic. This virus primarily infects the respiratory system and can lead to severe illness, pneumonia, and death.
viral protease
An enzyme produced by viruses that cleaves viral proteins to enable replication.
Viral proteases are essential enzymes for the life cycle of many viruses, including SARS-CoV-2. They cleave (cut) specific viral proteins, which allows the virus to assemble new viral particles and spread infection.
X-ray structures
3D representations of molecules obtained using X-ray crystallography.
X-ray structures are detailed 3D models of molecules determined by shining X-rays through crystallized samples. These structures reveal the arrangement of atoms within a molecule, providing crucial insights into its function and interactions with other molecules.
Mpro
Main protease of SARS-CoV-2.
Mpro, also known as 3CL protease, is a key enzyme produced by the SARS-CoV-2 virus. It plays a crucial role in viral replication by cleaving viral proteins, which are necessary for assembling new viral particles and spreading infection.
RCSB
Research Collaboratory for Structural Bioinformatics.
The RCSB Protein Data Bank (PDB) is a comprehensive global database of experimentally determined 3D structures of proteins and nucleic acids. It provides researchers with access to a vast collection of structural data, which is essential for understanding the function and interactions of biomolecules.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:33:40|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 7,196,163 | 622,276 | 11.56 | 2 hrs 5 mins |
| 2 | GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB] |
Nvidia | GA102 | 5,645,228 | 571,572 | 9.88 | 2 hrs 26 mins |
| 3 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,877,724 | 553,592 | 8.81 | 2 hrs 43 mins |
| 4 | TITAN RTX TU102 [TITAN RTX] 16310 |
Nvidia | TU102 | 4,686,149 | 548,727 | 8.54 | 2 hrs 49 mins |
| 5 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 3,971,076 | 541,848 | 7.33 | 3 hrs 16 mins |
| 6 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,682,156 | 504,182 | 7.30 | 3 hrs 17 mins |
| 7 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 3,666,017 | 496,140 | 7.39 | 3 hrs 15 mins |
| 8 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,472,117 | 490,678 | 7.08 | 3 hrs 24 mins |
| 9 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 3,188,280 | 481,818 | 6.62 | 3 hrs 38 mins |
| 10 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 3,140,740 | 479,835 | 6.55 | 3 hrs 40 mins |
| 11 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,113,806 | 475,145 | 6.55 | 3 hrs 40 mins |
| 12 | GeForce RTX 2080 SUPER Mobile / Max-Q TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q] |
Nvidia | TU104M | 3,104,944 | 477,678 | 6.50 | 3 hrs 42 mins |
| 13 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,998,902 | 469,465 | 6.39 | 3 hrs 45 mins |
| 14 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,855,995 | 463,601 | 6.16 | 3 hrs 54 mins |
| 15 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,787,056 | 456,645 | 6.10 | 3 hrs 56 mins |
| 16 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465 |
Nvidia | TU106 | 2,669,015 | 453,966 | 5.88 | 4 hrs 5 mins |
| 17 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,430,439 | 436,449 | 5.57 | 4 hrs 19 mins |
| 18 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 2,375,165 | 431,618 | 5.50 | 4 hrs 22 mins |
| 19 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,212,877 | 422,399 | 5.24 | 4 hrs 35 mins |
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|
|||||||
| 20 | Radeon VII Vega 20 [Radeon VII] 13,284 |
AMD | Vega 20 | 2,083,866 | 404,657 | 5.15 | 4 hrs 40 mins |
| 21 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,863,706 | 403,345 | 4.62 | 5 hrs 12 mins |
| 22 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,718,116 | 384,899 | 4.46 | 5 hrs 23 mins |
| 23 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,673,725 | 382,230 | 4.38 | 5 hrs 29 mins |
| 24 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,567,507 | 378,189 | 4.14 | 5 hrs 47 mins |
| 25 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,520,985 | 375,078 | 4.06 | 5 hrs 55 mins |
| 26 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,482,321 | 362,583 | 4.09 | 5 hrs 52 mins |
| 27 | GeForce GTX Titan X GM200 [GeForce GTX Titan X] 6144 |
Nvidia | GM200 | 1,445,256 | 370,510 | 3.90 | 6 hrs 9 mins |
| 28 | Radeon RX 5600/5600 XT - 5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT / 5700/5700 XT] |
AMD | Navi 10 | 1,407,840 | 351,685 | 4.00 | 5 hrs 60 mins |
| 29 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,389,522 | 349,982 | 3.97 | 6 hrs 3 mins |
| 30 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,287,493 | 356,229 | 3.61 | 6 hrs 38 mins |
| 31 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,267,509 | 353,941 | 3.58 | 6 hrs 42 mins |
| 32 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,229,100 | 347,042 | 3.54 | 6 hrs 47 mins |
| 33 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 1,039,162 | 330,024 | 3.15 | 7 hrs 37 mins |
| 34 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 981,594 | 318,494 | 3.08 | 7 hrs 47 mins |
| 35 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 943,633 | 318,314 | 2.96 | 8 hrs 6 mins |
| 36 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 934,692 | 315,074 | 2.97 | 8 hrs 5 mins |
| 37 | GeForce GTX 1650 Ti Mobile TU116M [GeForce GTX 1650 Ti Mobile] |
Nvidia | TU116M | 874,539 | 311,313 | 2.81 | 8 hrs 33 mins |
| 38 | GeForce GTX 1070 GP104 [GeForce GTX 1070] |
Nvidia | GP104 | 786,640 | 302,176 | 2.60 | 9 hrs 13 mins |
| 39 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 718,449 | 290,417 | 2.47 | 9 hrs 42 mins |
|
|
|||||||
| 40 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 715,624 | 292,925 | 2.44 | 9 hrs 49 mins |
| 41 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 574,519 | 272,684 | 2.11 | 11 hrs 23 mins |
| 42 | Radeon R9 Fury X Fiji XT [Radeon R9 Fury X] |
AMD | Fiji XT | 547,224 | 219,143 | 2.50 | 9 hrs 37 mins |
| 43 | Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series] |
AMD | Hawaii | 487,787 | 257,857 | 1.89 | 12 hrs 41 mins |
| 44 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 484,475 | 256,745 | 1.89 | 12 hrs 43 mins |
| 45 | Radeon R9 200/300 Series Hawaii [Radeon R9 200/300 Series] |
AMD | Hawaii | 461,085 | 241,072 | 1.91 | 12 hrs 33 mins |
| 46 | Quadro T2000 Mobile / Max-Q TU117GLM [Quadro T2000 Mobile / Max-Q] |
Nvidia | TU117GLM | 413,272 | 201,071 | 2.06 | 11 hrs 41 mins |
| 47 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 397,636 | 241,039 | 1.65 | 14 hrs 33 mins |
| 48 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 289,122 | 217,239 | 1.33 | 18 hrs 2 mins |
| 49 | Radeon R9 280/HD 7900/8950 Tahiti PRO [Radeon R9 280/HD 7900/8950] |
AMD | Tahiti PRO | 288,836 | 216,449 | 1.33 | 17 hrs 59 mins |
| 50 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 274,259 | 212,896 | 1.29 | 18 hrs 38 mins |
| 51 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 257,694 | 200,262 | 1.29 | 18 hrs 39 mins |
| 52 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 236,598 | 194,272 | 1.22 | 19 hrs 42 mins |
| 53 | Radeon HD 7800 Pitcairn [Radeon HD 7800] |
AMD | Pitcairn | 185,325 | 186,849 | 0.99 | 24 hrs 12 mins |
| 54 | Radeon RX Vega M XL [Radeon RX Vega M XL] |
AMD | Vega | 175,795 | 165,630 | 1.06 | 22 hrs 37 mins |
| 55 | Radeon R7 250/HD 7700 R575A [Radeon R7 250/HD 7700] |
AMD | R575A | 48,715 | 125,550 | 0.39 | 61 hrs 51 mins |
| 56 | Ryzen 4900HS mobile Renoir [Ryzen 4900HS mobile] |
AMD | Renoir | 33,148 | 125,550 | 0.26 | 90 hrs 54 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:33:40|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|