RESEARCH: MG2-ION-BINDING
FOLDING PROJECT #19305 PROFILE
PROJECT TEAM
Manager(s): Rabindranath PaulInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 139,195Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project investigates how Rubisco activase (Rca), a protein that helps plants perform photosynthesis, binds to energy molecules like ATP. Using computer simulations, researchers will explore how Rca interacts with these molecules and identify key amino acids involved in the process. This understanding can lead to better ways to improve plant growth and efficiency.
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+ protein
A superfamily of proteins involved in various cellular functions.
AAA+ proteins are a large group of essential proteins found in cells. They use energy from ATP to carry out many important tasks like controlling protein production, DNA replication, and organizing cell structures.
ATP
Adenosine Triphosphate
ATP is the main energy currency of cells. It powers most cellular processes by releasing energy when its phosphate bonds are broken.
ADP
Adenosine Diphosphate
ADP is a molecule produced when ATP releases energy. It can be converted back into ATP by adding a phosphate group.
Mg2+
Magnesium ion
Mg2+ is a positively charged magnesium ion that plays many roles in cellular processes, including helping enzymes work properly.
Rubisco activase (Rca)
A protein that activates Rubisco enzyme in plants.
Rubisco activase is an important enzyme found in plants that helps activate Rubisco, the key enzyme responsible for carbon dioxide fixation during photosynthesis.
ATP hydrolysis
The process of ATP breaking down into ADP and releasing energy.
ATP hydrolysis is how cells release the energy stored in ATP. This energy powers many cellular processes.
chaperone
A protein that helps other proteins fold correctly.
Chaperones are like cellular helpers that ensure proteins fold into their correct shapes, which is essential for them to function properly.
protease
An enzyme that breaks down proteins.
Proteases are enzymes that cut proteins into smaller pieces. They play important roles in breaking down cellular waste and regulating protein levels.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:25:23|
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 | 7,856,181 | 164,967 | 47.62 | 0 hrs 30 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 7,067,474 | 166,350 | 42.49 | 0 hrs 34 mins |
| 3 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 6,501,401 | 184,311 | 35.27 | 0 hrs 41 mins |
| 4 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,618,053 | 146,539 | 38.34 | 0 hrs 38 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,448,316 | 146,573 | 37.17 | 0 hrs 39 mins |
| 6 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,839,464 | 141,057 | 34.31 | 0 hrs 42 mins |
| 7 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,937,341 | 151,356 | 26.01 | 0 hrs 55 mins |
| 8 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,917,220 | 129,119 | 30.34 | 0 hrs 47 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,856,544 | 130,687 | 29.51 | 0 hrs 49 mins |
| 10 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 3,807,678 | 129,050 | 29.51 | 0 hrs 49 mins |
| 11 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,289,546 | 109,674 | 20.88 | 1 hrs 9 mins |
| 12 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 2,242,201 | 110,700 | 20.25 | 1 hrs 11 mins |
| 13 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,220,276 | 115,349 | 19.25 | 1 hrs 15 mins |
| 14 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,805,165 | 101,170 | 17.84 | 1 hrs 21 mins |
| 15 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,629,053 | 117,783 | 13.83 | 1 hrs 44 mins |
| 16 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 1,624,192 | 116,613 | 13.93 | 1 hrs 43 mins |
| 17 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,238,331 | 88,284 | 14.03 | 1 hrs 43 mins |
| 18 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,227,678 | 89,146 | 13.77 | 1 hrs 45 mins |
| 19 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 978,017 | 80,680 | 12.12 | 1 hrs 59 mins |
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| 20 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 891,736 | 80,200 | 11.12 | 2 hrs 10 mins |
| 21 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 562,265 | 66,251 | 8.49 | 2 hrs 50 mins |
| 22 | GeForce GTX 650 Ti GK106 [GeForce GTX 650 Ti] |
Nvidia | GK106 | 30,624 | 26,020 | 1.18 | 20 hrs 24 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:25:23|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|