RESEARCH: COVID-19
FOLDING PROJECT #17313 PROFILE
PROJECT TEAM
Manager(s): Ivy ZhangInstitution: Memorial Sloan Kettering Cancer Center
Project URL: View Project Website
WORK UNIT INFO
Atoms: 39,868Core: 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 simulating proteins involved in this process, with and without sugar molecules (glycosylation). They aim to understand how glycosylation affects protein shape and binding, potentially leading to new drug design strategies.
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.
RELATED TERMS GLOSSARY AI BETA
SARS-CoV-2
Severe Acute Respiratory Syndrome Coronavirus 2
SARS-CoV-2 is a virus that causes COVID-19. It's a type of coronavirus that was first identified in Wuhan, China in late 2019. The virus spreads through respiratory droplets and can cause a range of symptoms from mild to severe.
receptor binding domain (RBD)
Receptor Binding Domain
The receptor binding domain (RBD) is a specific part of the SARS-CoV-2 spike protein that binds to the ACE2 receptor on human cells. This binding allows the virus to enter and infect cells.
ACE2
Angiotensin-converting enzyme 2
ACE2 is a protein found on the surface of many human cells. It plays a role in regulating blood pressure and other bodily functions. The SARS-CoV-2 virus uses ACE2 as a receptor to enter and infect cells.
glycosylation
The process of attaching sugar molecules to proteins or lipids.
Glycosylation is a common modification that affects the function and structure of many proteins. In the case of SARS-CoV-2, glycosylation can impact how the virus binds to human cells and evades the immune system.
Markov State Models
Mathematical models used to simulate the dynamic behavior of molecules.
Markov State Models are used to understand how proteins change shape and interact with other molecules over time. In this case, they will be used to study how glycosylation affects the binding between SARS-CoV-2 RBD and ACE2.
metastable states
States that are relatively stable but can transition to other states.
Metastable states represent temporary configurations that molecules can occupy. Understanding these states is important for understanding how proteins function and interact.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:40:20|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce GTX 1070 Mobile GP104M [GeForce GTX 1070 Mobile] |
Nvidia | GP104M | 810,739 | 30,761 | 26.36 | 0 hrs 55 mins |
| 2 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 609,873 | 27,588 | 22.11 | 1 hrs 5 mins |
| 3 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 527,669 | 26,619 | 19.82 | 1 hrs 13 mins |
| 4 | GeForce GTX 780 GK110 [GeForce GTX 780] 3977 |
Nvidia | GK110 | 303,961 | 19,929 | 15.25 | 1 hrs 34 mins |
| 5 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 287,252 | 21,748 | 13.21 | 1 hrs 49 mins |
| 6 | GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile] |
Nvidia | GP107M | 259,810 | 21,049 | 12.34 | 1 hrs 57 mins |
| 7 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 226,637 | 20,146 | 11.25 | 2 hrs 8 mins |
| 8 | Quadro M2200 GM206 [Quadro M2200] |
Nvidia | GM206 | 224,981 | 20,141 | 11.17 | 2 hrs 9 mins |
| 9 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 201,769 | 18,930 | 10.66 | 2 hrs 15 mins |
| 10 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 140,701 | 17,127 | 8.22 | 2 hrs 55 mins |
| 11 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 136,132 | 16,913 | 8.05 | 2 hrs 59 mins |
| 12 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 122,185 | 16,340 | 7.48 | 3 hrs 13 mins |
| 13 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 122,169 | 16,357 | 7.47 | 3 hrs 13 mins |
| 14 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 101,498 | 15,252 | 6.65 | 3 hrs 36 mins |
| 15 | GeForce GTX 750 GM107 [GeForce GTX 750] 1111 |
Nvidia | GM107 | 95,572 | 15,135 | 6.31 | 3 hrs 48 mins |
| 16 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 88,361 | 14,726 | 6.00 | 3 hrs 60 mins |
| 17 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 85,165 | 14,483 | 5.88 | 4 hrs 5 mins |
| 18 | Quadro K620 GM107GL [Quadro K620] |
Nvidia | GM107GL | 56,453 | 12,628 | 4.47 | 5 hrs 22 mins |
| 19 | GeForce GTX 560 Ti GF114 [GeForce GTX 560 Ti] |
Nvidia | GF114 | 41,288 | 11,435 | 3.61 | 6 hrs 39 mins |
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| 20 | GeForce GTX 460 v2 GF114 [GeForce GTX 460 v2] 1045.6 |
Nvidia | GF114 | 27,382 | 9,653 | 2.84 | 8 hrs 28 mins |
| 21 | GeForce GT 710 GK208B [GeForce GT 710] 366 |
Nvidia | GK208B | 12,200 | 7,617 | 1.60 | 14 hrs 59 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:40:20|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|