RESEARCH: MG2-ION-BINDING
FOLDING PROJECT #19301 PROFILE
PROJECT TEAM
Manager(s): Rabindranath PaulInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 200,176Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how Rubisco activase (Rca), a protein that uses energy to help plants grow, binds to molecules like ADP and ATP. By using computer simulations, researchers hope to understand the details of this binding process and identify important parts of the Rca protein involved.
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 that perform diverse cellular functions.
AAA+ proteins are a large group of proteins found in all living organisms. They play important roles in many cellular processes, such as DNA replication, protein folding, and cell division. These proteins use energy from ATP to carry out their functions.
ATPase
An enzyme that catalyzes the hydrolysis of ATP.
ATPases are enzymes that break down a molecule called ATP. ATP is the main energy source for cells. ATPases play important roles in many cellular processes, such as muscle contraction, nerve impulse transmission, and protein synthesis.
ATP
Adenosine triphosphate, the primary energy currency of cells.
ATP stands for adenosine triphosphate. It's a molecule that stores and releases energy in cells. When cells need energy to do work, they break down ATP into ADP (adenosine diphosphate) and release energy.
ADP
Adenosine diphosphate, a molecule produced when ATP is hydrolyzed.
ADP stands for adenosine diphosphate. It's formed when ATP loses one phosphate group. Cells can convert ADP back into ATP to store energy again.
Mg2+
Magnesium ion, often involved in enzyme catalysis.
Mg2+ is a magnesium ion. It's important for many biological processes, including helping enzymes work correctly.
Rubisco activase (Rca)
An enzyme that activates Rubisco, a key enzyme in photosynthesis.
Rubisco activase is an important protein found in plants. It helps activate Rubisco, which is the enzyme that captures carbon dioxide during photosynthesis. This process is essential for making food and releasing oxygen.
Simulations
Computer models used to study biological systems.
Simulations are computer programs that mimic how real-world systems work. In biology, simulations can be used to understand complex processes like protein folding or drug interactions.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:25:29|
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 | 7,463,005 | 255,043 | 29.26 | 0 hrs 49 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,183,167 | 240,224 | 25.74 | 0 hrs 56 mins |
| 3 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,285,281 | 228,618 | 23.12 | 1 hrs 2 mins |
| 4 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,228,619 | 228,390 | 22.89 | 1 hrs 3 mins |
| 5 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,156,812 | 225,795 | 22.84 | 1 hrs 3 mins |
| 6 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,568,035 | 218,128 | 20.94 | 1 hrs 9 mins |
| 7 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,279,480 | 214,363 | 19.96 | 1 hrs 12 mins |
| 8 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,982,444 | 208,507 | 19.10 | 1 hrs 15 mins |
| 9 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,165,724 | 192,734 | 16.43 | 1 hrs 28 mins |
| 10 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,076,286 | 191,775 | 16.04 | 1 hrs 30 mins |
| 11 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,425,511 | 176,293 | 13.76 | 1 hrs 45 mins |
| 12 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,194,980 | 169,617 | 12.94 | 1 hrs 51 mins |
| 13 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 2,055,827 | 166,454 | 12.35 | 1 hrs 57 mins |
| 14 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 1,572,645 | 153,432 | 10.25 | 2 hrs 20 mins |
| 15 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,393,298 | 146,864 | 9.49 | 2 hrs 32 mins |
| 16 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,372,519 | 146,999 | 9.34 | 2 hrs 34 mins |
| 17 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,338,924 | 141,560 | 9.46 | 2 hrs 32 mins |
| 18 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,178,770 | 139,166 | 8.47 | 2 hrs 50 mins |
| 19 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 1,160,055 | 137,484 | 8.44 | 2 hrs 51 mins |
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|||||||
| 20 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,131,782 | 136,467 | 8.29 | 2 hrs 54 mins |
| 21 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 961,960 | 129,100 | 7.45 | 3 hrs 13 mins |
| 22 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 885,332 | 127,004 | 6.97 | 3 hrs 27 mins |
| 23 | Radeon RX 6600/6600 XT/6600M Navi 23 [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 | 294,505 | 85,192 | 3.46 | 6 hrs 57 mins |
| 24 | Radeon RX Vega 7 Lucienne [Radeon RX Vega 7] |
AMD | Lucienne | 43,326 | 41,898 | 1.03 | 23 hrs 13 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:25:29|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|