RESEARCH: AAA-PROTEIN-SUPERFAMILY
FOLDING PROJECT #19317 PROFILE
PROJECT TEAM
Manager(s): Rabindranath PaulInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 185,988Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how Rubisco activase (Rca), a protein important for plant growth, uses energy from ATP to change shape and perform its job. Scientists will use computer simulations to understand how Rca binds to ATP and ADP and identify key parts of the protein involved in this process.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Atomistic insights into AAA+ protein superfamily ATPases Associated with diverse cellular Activities (AAA+) comprise a superfamily of proteins that perform a large variety of functions essential to cell physiology, including control of protein homeostasis, DNA replication, recombination, chromatin remodeling, ribosomal RNA processing, molecular targeting, organelle biogenesis, and membrane fusion.
Members of this superfamily are defined by the presence of what is termed the AAA+ domain containing the canonical Walker A and B motifs required for ATP binding and hydrolysis.
Typically, genomes encode approximately ten to several hundred AAA+ family members, each of which is thought to be adapted to specific functional niches that necessitate precise mechanisms of substrate recognition and processing.
The striking adaptive radiation of AAA+ proteins to operate in diverse settings illustrates the versatile utility of the AAA+ domain.
AAA+ proteins typically form hexameric complexes and act as motors to remodel other proteins, DNA/RNA, or multicomponent complexes.
Indeed, many chaperones and ATP-dependent proteases are or have subunits that belong to this superfamily.
Rubisco activase (Rca) belongs to the AAA+ superfamily of proteins and it hydrolyzes ATP to ADP.
The complementarity of nucleotide-binding sites between AAA+ interfaces, the mechanism of ATP hydrolysis and the conformational changes activating or deactivating their ATP-binding pocket ensure a functional cycle that creates mechanical force to promote remodeling of substrates.
In this study, we will investigated the ADP/ATP and Mg2+ ion binding mechanism in Rca monomer and homodimers using extensive longtime scale simulations.
We will also try to find the binding pathway for ADP and ATP.
Simulations will also helps to predicts the crucial residues that involved in this binding process.
RELATED TERMS GLOSSARY AI BETA
AAA+
ATPases Associated with diverse cellular Activities
AAA+ proteins are a large family of enzymes that use energy from ATP to perform various cellular tasks, such as protein folding, DNA repair, and membrane fusion. They are essential for many biological processes and are found in all living organisms.
ATPase
An enzyme that hydrolyzes ATP to ADP, releasing energy.
ATPases are enzymes that break down adenosine triphosphate (ATP), a molecule that stores energy in cells. This process releases energy that can be used to power various cellular activities, such as muscle contraction, nerve impulse transmission, and protein synthesis.
Protein
A large biomolecule composed of amino acids linked together in a chain.
Proteins are essential building blocks of all living organisms. They perform a wide range of functions, including catalyzing biochemical reactions, transporting molecules, providing structural support, and regulating cellular processes.
DNA
Deoxyribonucleic acid
DNA is a molecule that carries genetic information. It is composed of two strands of nucleotides wound around each other in a double helix structure. DNA contains the instructions for building and maintaining an organism.
RNA
Ribonucleic acid
RNA is a molecule similar to DNA, but it is single-stranded and plays a role in protein synthesis. It carries genetic information from DNA to ribosomes, where proteins are made.
Simulations
Computer models used to study complex systems.
Simulations are computer programs that mimic real-world processes. In biotechnology, simulations are used to study the behavior of molecules, cells, and organisms.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:25:09|
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 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 15,598,884 | 276,650 | 56.38 | 0 hrs 26 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 13,602,638 | 269,146 | 50.54 | 0 hrs 28 mins |
| 3 | GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 8,803,519 | 231,970 | 37.95 | 0 hrs 38 mins |
| 4 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,979,301 | 212,957 | 32.77 | 0 hrs 44 mins |
| 5 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 6,586,630 | 209,783 | 31.40 | 0 hrs 46 mins |
| 6 | RTX A6000 GA102GL [RTX A6000] |
Nvidia | GA102GL | 6,260,680 | 205,311 | 30.49 | 0 hrs 47 mins |
| 7 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,793,389 | 201,977 | 28.68 | 0 hrs 50 mins |
| 8 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,089,766 | 188,405 | 27.02 | 0 hrs 53 mins |
| 9 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,063,559 | 194,008 | 26.10 | 0 hrs 55 mins |
| 10 | Radeon RX 7900XT/XTX Navi 31 [Radeon RX 7900XT/XTX] |
AMD | Navi 31 | 4,760,650 | 189,132 | 25.17 | 0 hrs 57 mins |
| 11 | GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB] |
Nvidia | GA102 | 4,653,467 | 148,429 | 31.35 | 0 hrs 46 mins |
| 12 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,554,265 | 185,422 | 24.56 | 0 hrs 59 mins |
| 13 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,193,582 | 181,611 | 23.09 | 1 hrs 2 mins |
| 14 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,879,830 | 178,080 | 21.79 | 1 hrs 6 mins |
| 15 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,764,984 | 174,907 | 21.53 | 1 hrs 7 mins |
| 16 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 3,388,118 | 168,067 | 20.16 | 1 hrs 11 mins |
| 17 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 3,379,632 | 168,377 | 20.07 | 1 hrs 12 mins |
| 18 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,342,972 | 166,553 | 20.07 | 1 hrs 12 mins |
| 19 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,985,418 | 162,599 | 18.36 | 1 hrs 18 mins |
|
|
|||||||
| 20 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,978,684 | 162,600 | 18.32 | 1 hrs 19 mins |
| 21 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 2,940,424 | 162,459 | 18.10 | 1 hrs 20 mins |
| 22 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,719,032 | 157,325 | 17.28 | 1 hrs 23 mins |
| 23 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,698,268 | 157,138 | 17.17 | 1 hrs 24 mins |
| 24 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,582,470 | 154,696 | 16.69 | 1 hrs 26 mins |
| 25 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,319,824 | 149,733 | 15.49 | 1 hrs 33 mins |
| 26 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,062,577 | 143,722 | 14.35 | 1 hrs 40 mins |
| 27 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 2,003,456 | 142,347 | 14.07 | 1 hrs 42 mins |
| 28 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,874,635 | 139,084 | 13.48 | 1 hrs 47 mins |
| 29 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,695,102 | 132,995 | 12.75 | 1 hrs 53 mins |
| 30 | GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB] |
Nvidia | TU106 | 1,575,772 | 132,591 | 11.88 | 2 hrs 1 mins |
| 31 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 1,541,092 | 129,966 | 11.86 | 2 hrs 1 mins |
| 32 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,525,978 | 145,781 | 10.47 | 2 hrs 18 mins |
| 33 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,182,705 | 118,321 | 10.00 | 2 hrs 24 mins |
| 34 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,179,617 | 118,008 | 10.00 | 2 hrs 24 mins |
| 35 | GeForce RTX 3050 Ti Mobile GA107M [GeForce RTX 3050 Ti Mobile] |
Nvidia | GA107M | 1,142,763 | 117,664 | 9.71 | 2 hrs 28 mins |
| 36 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 1,141,192 | 118,009 | 9.67 | 2 hrs 29 mins |
| 37 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,061,826 | 114,045 | 9.31 | 2 hrs 35 mins |
| 38 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,059,686 | 114,207 | 9.28 | 2 hrs 35 mins |
| 39 | Radeon RX 6600/6600 XT/6600M Navi 23 XT-XL [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 XT-XL | 1,032,982 | 114,661 | 9.01 | 2 hrs 40 mins |
|
|
|||||||
| 40 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 994,236 | 113,150 | 8.79 | 2 hrs 44 mins |
| 41 | Radeon Pro W5700 Navi 10 [Radeon Pro W5700] |
AMD | Navi 10 | 963,700 | 108,062 | 8.92 | 2 hrs 41 mins |
| 42 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 952,444 | 110,394 | 8.63 | 2 hrs 47 mins |
| 43 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 922,086 | 101,351 | 9.10 | 2 hrs 38 mins |
| 44 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 763,180 | 103,841 | 7.35 | 3 hrs 16 mins |
| 45 | RX 5600 OEM/5600XT/5700/5700XT Navi 10 [RX 5600 OEM/5600XT/5700/5700XT] |
AMD | Navi 10 | 748,618 | 103,063 | 7.26 | 3 hrs 18 mins |
| 46 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 702,853 | 99,998 | 7.03 | 3 hrs 25 mins |
| 47 | Tesla T4 TU104GL [Tesla T4] |
Nvidia | TU104GL | 691,437 | 100,417 | 6.89 | 3 hrs 29 mins |
| 48 | RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590] |
AMD | Ellesmere XT | 436,194 | 85,611 | 5.10 | 4 hrs 43 mins |
| 49 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 330,735 | 80,501 | 4.11 | 5 hrs 50 mins |
| 50 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 161,314 | 61,585 | 2.62 | 9 hrs 10 mins |
| 51 | Vega Mobile 5000 series APU Cezanne [Vega Mobile 5000 series APU] |
AMD | Cezanne | 51,640 | 46,509 | 1.11 | 21 hrs 37 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:25:09|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|