RESEARCH: MEMBRANE TRANSPORT
FOLDING PROJECT #17902 PROFILE

PROJECT TEAM

Manager(s): Austin Weigle
Institution: University of Illinois at Urbana-Champaign
Project URL: View Project Website

WORK UNIT INFO

Atoms: 179,595
Core: 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

Note: Glossary items are a high level summary and may not be 100% accurate.

Post-translational Modification

Alterations to a protein after its synthesis.

Technical: Biotechnology
Biochemistry / Protein Modification

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.

Scientific: Biotechnology
Cell Biology / Transport

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.

Technical: Biotechnology
Biochemistry / Protein Structure

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.

Technical: Biotechnology
Biochemistry / Protein Modification

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.

Scientific: Biotechnology
Biochemistry / Protein Function

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
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