RESEARCH: INFLUENZA
FOLDING PROJECT #12454 PROFILE
PROJECT TEAM
Manager(s): Dylan NovackInstitution: Temple University
Project URL: View Project Website
WORK UNIT INFO
Atoms: 90,406Core: 0x23
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Miniprotein drugs are being developed to fight flu by blocking a viral protein called hemagglutinin. Scientists want to understand how these miniproteins work so they can design even better ones. They'll use computer simulations to see how the miniproteins bind and unbind from hemagglutinin, giving us a clearer picture of the process.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Designed miniprotein therapeutics occupy the middle ground between small molecule drugs and monoclonal antibody treatments for infectious disease.
Hemagglutinin is a viral fusion protein that allows H1 influenza A (HA) to bind sialic acid on cell surfaces, as well as being involved in the post-endocytosis mechanism of cellular infection.; The Baker lab at University of Washington has developed de novo designed miniproteins that bind hemagglutinin, and developed ways to improve their binding through affinity maturation.
Many of the mutations seen in affinity-matured sequences are not directly in the binding interface, and it is unclear how these changes lead to higher affinity.
Understanding this mechanism may help us better computationally design better binders.
We aim to use molecular dynamics simulations to examine ab initio binding pathways for these miniprotein binders, and use enhanced sampling methods to study the unbinding reaction.
Pairing these methods together will provide a robust description of the complete binding reaction for this system.
RELATED TERMS GLOSSARY AI BETA
miniprotein
A small protein with therapeutic potential.
Miniproteins are tiny proteins designed for specific medical purposes. They're smaller than traditional antibodies but still effective at targeting diseases. Researchers are exploring their use in treating infections and other conditions.
monoclonal antibody
A laboratory-produced antibody that recognizes a specific antigen.
Monoclonal antibodies are lab-made immune system proteins that target specific molecules (antigens) on cells. They're used to treat various diseases by blocking harmful signals or triggering an immune response against cancer cells.
infectious disease
A disease caused by a pathogen.
Infectious diseases are illnesses caused by microorganisms like bacteria, viruses, fungi, or parasites. They can spread from person to person or through contaminated environments.
hemagglutinin
A viral protein that allows viruses to attach to host cells.
Hemagglutinin is a key protein found on the surface of many viruses. It helps the virus latch onto and enter human cells, enabling infection.
H1 influenza A
Influenza A subtype H1.
H1N1 is a type of influenza virus that can cause seasonal flu. It's characterized by its hemagglutinin protein (H1) and neuraminidase protein (N1). Vaccinations are available to help prevent infection.
sialic acid
A type of sugar found on cell surfaces.
Sialic acid is a common sugar molecule found attached to the surface of many cells. It plays a role in various biological processes, including cell signaling and recognition.
post-endocytosis mechanism
The process that occurs after a cell has engulfed a particle.
Post-endocytosis refers to the events that happen inside a cell after it has taken in a substance through endocytosis. This can include breaking down the engulfed material or using it for other cellular functions.
affinity maturation
The process of improving the binding strength of an antibody.
Affinity maturation is a natural process by which the immune system refines antibodies to make them bind more strongly to their target antigens. This enhances the effectiveness of the immune response.
molecular dynamics simulations
Computer models that simulate the movement of molecules over time.
Molecular dynamics simulations use computer algorithms to track the interactions between atoms and molecules. This allows scientists to study how proteins fold, how drugs bind to targets, and other biological processes at the atomic level.
enhanced sampling methods
Techniques used to speed up molecular dynamics simulations.
Enhanced sampling methods are designed to overcome the limitations of standard molecular dynamics simulations by exploring a wider range of possible conformations. This helps researchers study rare events and more complex systems.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:34:25|
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 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 9,049,387 | 97,384 | 92.92 | 0 hrs 15 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 9,045,206 | 256,310 | 35.29 | 0 hrs 41 mins |
| 3 | RTX A6000 GA102GL [RTX A6000] |
Nvidia | GA102GL | 8,761,935 | 36,715 | 238.65 | 0 hrs 6 mins |
| 4 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 8,473,121 | 233,163 | 36.34 | 0 hrs 40 mins |
| 5 | GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB] |
Nvidia | GA102 | 7,565,426 | 245,955 | 30.76 | 0 hrs 47 mins |
| 6 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 6,749,164 | 232,494 | 29.03 | 0 hrs 50 mins |
| 7 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,733,210 | 107,641 | 53.26 | 0 hrs 27 mins |
| 8 | Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE] |
AMD | Navi 31 | 5,603,179 | 192,734 | 29.07 | 0 hrs 50 mins |
| 9 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,557,370 | 219,593 | 25.31 | 0 hrs 57 mins |
| 10 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 5,546,804 | 223,290 | 24.84 | 0 hrs 58 mins |
| 11 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,458,972 | 220,356 | 24.77 | 0 hrs 58 mins |
| 12 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,962,691 | 214,333 | 23.15 | 1 hrs 2 mins |
| 13 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 4,582,424 | 209,042 | 21.92 | 1 hrs 6 mins |
| 14 | TITAN V GV100 [TITAN V] M 12288 |
Nvidia | GV100 | 4,008,106 | 200,107 | 20.03 | 1 hrs 12 mins |
| 15 | RTX A4000 GA104GL [RTX A4000] |
Nvidia | GA104GL | 3,826,028 | 196,260 | 19.49 | 1 hrs 14 mins |
| 16 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,759,320 | 192,547 | 19.52 | 1 hrs 14 mins |
| 17 | Radeon RX 7700XT/7800XT Navi 32 [Radeon RX 7700XT/7800XT] |
AMD | Navi 32 | 3,634,546 | 131,071 | 27.73 | 0 hrs 52 mins |
| 18 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,438,431 | 189,588 | 18.14 | 1 hrs 19 mins |
| 19 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,361,821 | 186,477 | 18.03 | 1 hrs 20 mins |
|
|
|||||||
| 20 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 3,309,989 | 155,170 | 21.33 | 1 hrs 8 mins |
| 21 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 3,198,212 | 111,684 | 28.64 | 0 hrs 50 mins |
| 22 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 3,055,755 | 177,189 | 17.25 | 1 hrs 23 mins |
| 23 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 Super] |
Nvidia | TU104 | 3,012,921 | 77,938 | 38.66 | 0 hrs 37 mins |
| 24 | GeForce RTX 4050 Max-Q / Mobile AD107M [GeForce RTX 4050 Max-Q / Mobile] |
Nvidia | AD107M | 2,891,523 | 180,348 | 16.03 | 1 hrs 30 mins |
| 25 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,865,053 | 162,278 | 17.66 | 1 hrs 22 mins |
| 26 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,842,576 | 177,949 | 15.97 | 1 hrs 30 mins |
| 27 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,578,345 | 163,951 | 15.73 | 1 hrs 32 mins |
| 28 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 2,576,729 | 172,747 | 14.92 | 1 hrs 37 mins |
| 29 | GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB] |
Nvidia | TU106 | 2,568,958 | 172,228 | 14.92 | 1 hrs 37 mins |
| 30 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,415,347 | 168,912 | 14.30 | 1 hrs 41 mins |
| 31 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,376,009 | 168,102 | 14.13 | 1 hrs 42 mins |
| 32 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 2,363,633 | 167,171 | 14.14 | 1 hrs 42 mins |
| 33 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,233,744 | 162,686 | 13.73 | 1 hrs 45 mins |
| 34 | GeForce RTX 2070 Mobile / Max-Q Refresh TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh] |
Nvidia | TU106M | 2,076,461 | 159,298 | 13.04 | 1 hrs 50 mins |
| 35 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,914,966 | 146,339 | 13.09 | 1 hrs 50 mins |
| 36 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,729,388 | 149,591 | 11.56 | 2 hrs 5 mins |
| 37 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 1,666,405 | 148,952 | 11.19 | 2 hrs 9 mins |
| 38 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,539,992 | 145,160 | 10.61 | 2 hrs 16 mins |
| 39 | GeForce RTX 4060 Max-Q / Mobile AD107M [GeForce RTX 4060 Max-Q / Mobile] |
Nvidia | AD107M | 1,528,252 | 109,343 | 13.98 | 1 hrs 43 mins |
|
|
|||||||
| 40 | GeForce RTX 3050 8GB GA107 [GeForce RTX 3050 8GB] |
Nvidia | GA107 | 1,495,121 | 142,668 | 10.48 | 2 hrs 17 mins |
| 41 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,409,376 | 141,374 | 9.97 | 2 hrs 24 mins |
| 42 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,373,574 | 139,594 | 9.84 | 2 hrs 26 mins |
| 43 | Radeon RX 6600/6600 XT/6600M Navi 23 XT-XL [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 XT-XL | 1,360,330 | 138,478 | 9.82 | 2 hrs 27 mins |
| 44 | RTX A2000 12GB GA106 [RTX A2000 12GB] |
Nvidia | GA106 | 1,329,518 | 138,247 | 9.62 | 2 hrs 30 mins |
| 45 | GeForce RTX 2070 Mobile TU106M [GeForce RTX 2070 Mobile] |
Nvidia | TU106M | 1,326,686 | 137,782 | 9.63 | 2 hrs 30 mins |
| 46 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,294,463 | 136,386 | 9.49 | 2 hrs 32 mins |
| 47 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,290,054 | 136,717 | 9.44 | 2 hrs 33 mins |
| 48 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,212,195 | 100,003 | 12.12 | 1 hrs 59 mins |
| 49 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 1,155,592 | 110,769 | 10.43 | 2 hrs 18 mins |
| 50 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 1,053,497 | 97,227 | 10.84 | 2 hrs 13 mins |
| 51 | GeForce RTX 3050 6GB GA107 [GeForce RTX 3050 6GB] |
Nvidia | GA107 | 1,040,415 | 36,715 | 28.34 | 0 hrs 51 mins |
| 52 | GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile] |
Nvidia | TU116M | 1,034,766 | 95,307 | 10.86 | 2 hrs 13 mins |
| 53 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 848,498 | 116,184 | 7.30 | 3 hrs 17 mins |
| 54 | Quadro P3200 Mobile GP104GLM [Quadro P3200 Mobile] |
Nvidia | GP104GLM | 803,145 | 116,730 | 6.88 | 3 hrs 29 mins |
| 55 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 742,857 | 36,715 | 20.23 | 1 hrs 11 mins |
| 56 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 684,023 | 112,633 | 6.07 | 3 hrs 57 mins |
| 57 | GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile] |
Nvidia | GP106M | 681,691 | 109,890 | 6.20 | 3 hrs 52 mins |
| 58 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 651,618 | 108,012 | 6.03 | 3 hrs 59 mins |
| 59 | GeForce GTX 1650 Ti Mobile TU117M [GeForce GTX 1650 Ti Mobile] |
Nvidia | TU117M | 599,393 | 106,382 | 5.63 | 4 hrs 16 mins |
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|
|||||||
| 60 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 3091 |
Nvidia | TU116 | 579,800 | 105,866 | 5.48 | 4 hrs 23 mins |
| 61 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 566,928 | 36,715 | 15.44 | 1 hrs 33 mins |
| 62 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 538,517 | 47,069 | 11.44 | 2 hrs 6 mins |
| 63 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 474,081 | 76,212 | 6.22 | 3 hrs 51 mins |
| 64 | RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590] |
AMD | Ellesmere XT | 442,530 | 56,972 | 7.77 | 3 hrs 5 mins |
| 65 | Radeon RX 7700S/7600S Navi 33 [Radeon RX 7700S/7600S] |
AMD | Navi 33 | 399,473 | 36,715 | 10.88 | 2 hrs 12 mins |
| 66 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 379,126 | 94,109 | 4.03 | 5 hrs 57 mins |
| 67 | RX 5500/5500M/Pro 5500M Navi 14 [RX 5500/5500M/Pro 5500M] |
AMD | Navi 14 | 351,662 | 89,123 | 3.95 | 6 hrs 5 mins |
| 68 | Quadro M4000 GM204GL [Quadro M4000] |
Nvidia | GM204GL | 328,850 | 88,192 | 3.73 | 6 hrs 26 mins |
| 69 | GeForce GTX 1050 3 GB Max-Q GP107M [GeForce GTX 1050 3 GB Max-Q] |
Nvidia | GP107M | 324,125 | 86,202 | 3.76 | 6 hrs 23 mins |
| 70 | GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile] |
Nvidia | GP107M | 309,843 | 85,244 | 3.63 | 6 hrs 36 mins |
| 71 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 268,943 | 80,078 | 3.36 | 7 hrs 9 mins |
| 72 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 205,955 | 74,453 | 2.77 | 8 hrs 41 mins |
| 73 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 89,226 | 60,531 | 1.47 | 16 hrs 17 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:34:25|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|