RESEARCH: COVID-19
FOLDING PROJECT #17330 PROFILE
PROJECT TEAM
Manager(s): Ivy ZhangInstitution: Memorial Sloan Kettering Cancer Center
Project URL: View Project Website
WORK UNIT INFO
Atoms: 257,386Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how the SARS-CoV-2 virus attaches to human cells. Researchers are using computer simulations to understand how the virus's protein (RBD) changes shape when it binds to a receptor on our cells (ACE2). They're also looking at how sugar molecules attached to these proteins affect their shape and binding. This knowledge will help scientists design better drugs to fight COVID-19.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
These projects involve the SARS-CoV-2 receptor binding domain (RBD) and its target receptor in humans, ACE2.
We are simulating these proteins alone and in complex with each other (and with and without glycosylation).
We will build Markov State Models using the Fah simulation data, which will help us identify the metastable states of each protein/protein complex.
Given these experiments, we hope to be able to explain the impact of glycosylation on RBD conformational dynamics as well as identify whether there are shifts in metastable states upon RBD:ACE2 binding.
Ultimately, the knowledge gained here will help infom drug design efforts. Note: 17313-6 replace 17307-9, as 17307-9 used a different, less stable integrator. 17329-331 replace 17316-8 (change from rectangular to truncated octahedron box) 17332-5 replace 17325-8 ((change from rectangular to truncated octahedron box).
RELATED TERMS GLOSSARY AI BETA
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
SARS-CoV-2 is the virus that causes COVID-19. It is a type of coronavirus that primarily affects the respiratory system. Understanding its structure and how it interacts with human cells is crucial for developing treatments and vaccines.
receptor binding domain (RBD)
Receptor Binding Domain
The RBD is a specific region on the surface of SARS-CoV-2 that binds to the ACE2 receptor on human cells, allowing the virus to enter and infect them. This interaction is essential for viral replication.
ACE2
Angiotensin-converting enzyme 2
ACE2 is a protein found on the surface of many human cells, including those in the lungs and heart. It plays a role in regulating blood pressure and fluid balance. SARS-CoV-2 uses ACE2 as its entry point into human cells.
glycosylation
The process of adding sugar molecules to proteins.
Glycosylation is a crucial process that modifies proteins and influences their function, stability, and interactions. In the context of SARS-CoV-2, glycosylation can affect how the virus binds to human cells and evade the immune system.
Markov State Models
Mathematical models used to simulate the behavior of complex systems over time.
Markov State Models are powerful tools for understanding protein dynamics and identifying stable states. By simulating the movements of atoms in proteins, researchers can gain insights into how they fold, interact with other molecules, and carry out their functions.
metastable states
Transient states that are relatively stable but can eventually transition to other states.
Metastable states represent different conformations or configurations of a protein. Understanding these states is crucial for comprehending how proteins function and respond to changes in their environment.
drug design
The process of identifying and developing new drugs to treat diseases.
Drug design involves a multidisciplinary approach that combines chemistry, biology, and computational modeling to create molecules with specific therapeutic effects. Understanding how viruses like SARS-CoV-2 interact with human cells is essential for designing effective antiviral drugs.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:39:53|
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 | 5,878,955 | 247,653 | 23.74 | 1 hrs 1 mins |
| 2 | GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB] |
Nvidia | GA102 | 5,486,995 | 244,083 | 22.48 | 1 hrs 4 mins |
| 3 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 4,465,614 | 228,598 | 19.53 | 1 hrs 14 mins |
| 4 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,363,901 | 226,040 | 19.31 | 1 hrs 15 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,078,239 | 221,771 | 18.39 | 1 hrs 18 mins |
| 6 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 3,797,702 | 213,043 | 17.83 | 1 hrs 21 mins |
| 7 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,895,549 | 197,587 | 14.65 | 1 hrs 38 mins |
| 8 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,818,442 | 196,269 | 14.36 | 1 hrs 40 mins |
| 9 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,646,894 | 191,339 | 13.83 | 1 hrs 44 mins |
| 10 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 2,609,492 | 190,685 | 13.68 | 1 hrs 45 mins |
| 11 | GeForce RTX 2080 TU104 [GeForce RTX 2080] |
Nvidia | TU104 | 2,590,588 | 190,848 | 13.57 | 1 hrs 46 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,443,779 | 186,969 | 13.07 | 1 hrs 50 mins |
| 13 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,073,237 | 175,793 | 11.79 | 2 hrs 2 mins |
| 14 | GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497 |
Nvidia | TU106 | 1,976,114 | 174,329 | 11.34 | 2 hrs 7 mins |
| 15 | GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q] |
Nvidia | GA104M | 1,848,570 | 171,130 | 10.80 | 2 hrs 13 mins |
| 16 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 1,743,284 | 165,467 | 10.54 | 2 hrs 17 mins |
| 17 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,583,069 | 161,638 | 9.79 | 2 hrs 27 mins |
| 18 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,578,332 | 161,558 | 9.77 | 2 hrs 27 mins |
| 19 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,472,064 | 149,037 | 9.88 | 2 hrs 26 mins |
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|
|||||||
| 20 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,442,942 | 146,374 | 9.86 | 2 hrs 26 mins |
| 21 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,345,321 | 151,932 | 8.85 | 2 hrs 43 mins |
| 22 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,242,367 | 146,983 | 8.45 | 2 hrs 50 mins |
| 23 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,200,475 | 148,579 | 8.08 | 2 hrs 58 mins |
| 24 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,118,707 | 139,878 | 8.00 | 3 hrs 0 mins |
| 25 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,102,209 | 140,246 | 7.86 | 3 hrs 3 mins |
| 26 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,087,391 | 143,276 | 7.59 | 3 hrs 10 mins |
| 27 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 1,086,938 | 141,988 | 7.66 | 3 hrs 8 mins |
| 28 | GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q] 4550 |
Nvidia | TU106M | 1,082,037 | 143,323 | 7.55 | 3 hrs 11 mins |
| 29 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 918,225 | 135,236 | 6.79 | 3 hrs 32 mins |
| 30 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 892,556 | 134,214 | 6.65 | 3 hrs 37 mins |
| 31 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 753,479 | 126,776 | 5.94 | 4 hrs 2 mins |
| 32 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 624,444 | 117,806 | 5.30 | 4 hrs 32 mins |
| 33 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 572,259 | 115,640 | 4.95 | 4 hrs 51 mins |
| 34 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 550,162 | 114,445 | 4.81 | 4 hrs 60 mins |
| 35 | Quadro T2000 Mobile / Max-Q TU117GLM [Quadro T2000 Mobile / Max-Q] |
Nvidia | TU117GLM | 451,529 | 107,423 | 4.20 | 5 hrs 43 mins |
| 36 | Radeon RX 5500/5500M / Pro 5500M Navi 14 [Radeon RX 5500/5500M / Pro 5500M] |
AMD | Navi 14 | 450,357 | 104,002 | 4.33 | 5 hrs 33 mins |
| 37 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984 |
Nvidia | TU116 | 445,731 | 106,147 | 4.20 | 5 hrs 43 mins |
| 38 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 442,621 | 106,215 | 4.17 | 5 hrs 46 mins |
| 39 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 287,164 | 91,672 | 3.13 | 7 hrs 40 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:39:53|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|