RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17902 PROFILE
PROJECT TEAM
Manager(s): Austin WeigleInstitution: University of Illinois at Urbana-Champaign
Project URL: View Project Website
WORK UNIT INFO
Atoms: 179,595Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project relates to studying how adding a phosphate group (phosphorylation) to the end of a sugar transporter protein affects how it works and clumps together with other proteins. This is important because these changes can control how much sugar enters and leaves cells, which is crucial for things like metabolism.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Measuring the Effects of Post-translational Modification on Membrane Transporter Function and Oligomerization: Membrane transporters possess terminal tails which can variably regulate their substrate recognition, gating dynamics, and oligomerization (see https://royalsocietypublishing.org/doi/full/10.1098/rsob.190083 for a review).
To reflect physiological conditions and satisfy the instantaneous demands of cells, these termini are known to be post-translationally modified (PTM).
PTMs, like phosphorylation, have been shown to regulate transporter function through allostery or direct local interactions, thus blocking transmembrane substrate import and/or export. Simulations in this project will be focused on studying how C-terminal phosphorylation affects oligomerization dynamics of a sugar transporter.
While a basic protein folding problem, understanding how PTMs affect transporter oligomerization, and oligomer dynamics, is critical for understanding biological regulations for basal transport activity.
This study's ability to observe how terminal PTMs may influence sugar transport dynamics has implications for studying cells in altered metabolic states.
RELATED TERMS GLOSSARY AI BETA
Post-translational Modification
Alterations to a protein after its synthesis.
Post-translational modifications (PTMs) are chemical changes that happen to proteins *after* they've been made. These modifications can affect how proteins work, where they go in the cell, and how long they last. Examples include phosphorylation, glycosylation, and ubiquitination.
Membrane Transporter
A protein that moves molecules across cell membranes.
Membrane transporters are like tiny doors within cells that allow specific substances to enter or leave. These proteins play a crucial role in maintaining the balance of nutrients, ions, and waste products inside and outside the cell.
Oligomerization
The process of proteins coming together to form complexes.
Oligomerization is when multiple protein molecules join forces to create a larger, more complex structure. This can change how the proteins function and interact with other molecules.
Phosphorylation
The addition of a phosphate group to a molecule.
Phosphorylation is like attaching a tiny electrical switch to a protein. This can turn the protein 'on' or 'off', affecting its activity and interactions with other molecules.
Allostery
The regulation of a protein's activity by binding to a site other than the active site.
Allostery is like having a remote control for a protein. Binding to a specific site can change how the protein works, even if it's far from its main 'switch'.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:34:45|
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 | 9,902,935 | 358,453 | 27.63 | 0 hrs 52 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 8,670,907 | 341,330 | 25.40 | 0 hrs 57 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 8,326,574 | 338,741 | 24.58 | 0 hrs 59 mins |
| 4 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 5,412,067 | 293,575 | 18.44 | 1 hrs 18 mins |
| 5 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 5,349,686 | 291,013 | 18.38 | 1 hrs 18 mins |
| 6 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,958,327 | 283,675 | 17.48 | 1 hrs 22 mins |
| 7 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,856,241 | 281,032 | 17.28 | 1 hrs 23 mins |
| 8 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,563,649 | 276,390 | 16.51 | 1 hrs 27 mins |
| 9 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,713,907 | 259,324 | 14.32 | 1 hrs 41 mins |
| 10 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,669,773 | 233,023 | 11.46 | 2 hrs 6 mins |
| 11 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,629,755 | 230,475 | 11.41 | 2 hrs 6 mins |
| 12 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,300,329 | 220,884 | 10.41 | 2 hrs 18 mins |
| 13 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,242,798 | 218,102 | 10.28 | 2 hrs 20 mins |
| 14 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,560,102 | 194,561 | 8.02 | 2 hrs 60 mins |
| 15 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,452,214 | 150,595 | 9.64 | 2 hrs 29 mins |
| 16 | GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q] |
Nvidia | TU106M | 1,326,536 | 183,971 | 7.21 | 3 hrs 20 mins |
| 17 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 619,320 | 143,419 | 4.32 | 5 hrs 33 mins |
| 18 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 565,807 | 138,489 | 4.09 | 5 hrs 52 mins |
| 19 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 377,606 | 121,438 | 3.11 | 7 hrs 43 mins |
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| 20 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 326,046 | 115,458 | 2.82 | 8 hrs 30 mins |
| 21 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 298,799 | 112,527 | 2.66 | 9 hrs 2 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:34:45|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|