RESEARCH: CANCER
FOLDING PROJECT #17745 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 85,312Core: OPENMM_22
Status: Beta
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at how proteins move stuff across cell walls using electricity. These proteins are found everywhere and help move important molecules. Understanding them could lead to new treatments for diseases like cancer and diabetes.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Projects 17745-17750 Molecular basis of secondary active transporters. Secondary active membrane transporters are proteins that utilize ions to transport an assortment of molecules across cell membranes.
These proteins are found in all domains in life and surprisingly, despite vastly different structures, operate under the same mechanism by using an ion gradient to assist in small molecule transport.
Furthermore, many of these secondary active transporters are drug targets to treat diseases like cancer, diabetes, and neurological disorders.
The simulations in this project will allow us to understand a universal role of ion-coupling across different families of proteins.
RELATED TERMS GLOSSARY AI BETA
Secondary active transporters
Proteins that use ions to transport molecules across cell membranes.
Secondary active transporters are essential proteins found in all living organisms. They use the energy stored in an ion gradient to move various molecules across cell membranes. This process is crucial for many biological functions, including nutrient uptake, waste removal, and signal transduction. These transporters are also important drug targets for treating diseases like cancer, diabetes, and neurological disorders.
Ion gradient
A difference in concentration of ions across a cell membrane.
An ion gradient refers to the unequal distribution of charged particles (ions) across a cell membrane. This difference in concentration is maintained by specialized proteins called pumps and channels. The energy stored in the ion gradient can be used to drive other cellular processes, such as the transport of molecules across the membrane.
Proteins
Large, complex molecules essential for all living organisms.
Proteins are the building blocks of life. They perform a wide variety of functions in cells, including catalyzing biochemical reactions, transporting molecules, providing structural support, and regulating gene expression. Proteins are composed of chains of amino acids, which fold into specific three-dimensional shapes that determine their function.
Cell membrane
A thin barrier that surrounds each cell.
The cell membrane is a selectively permeable barrier that separates the internal environment of a cell from its surroundings. It regulates the passage of molecules into and out of the cell, maintaining cellular homeostasis. The cell membrane is composed primarily of lipids and proteins.
Simulations
Computer models used to study complex systems.
Simulations are powerful tools for studying biological systems. By creating computer models of cells, tissues, or organisms, researchers can explore how different factors influence their behavior. Simulations can be used to test hypotheses, predict outcomes, and gain insights into the complexities of life.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:36:10|
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 | 6,859,029 | 87,686 | 78.22 | 0 hrs 18 mins |
| 2 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 2,714,233 | 64,408 | 42.14 | 0 hrs 34 mins |
| 3 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 1,904,685 | 57,317 | 33.23 | 0 hrs 43 mins |
| 4 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 875,704 | 44,379 | 19.73 | 1 hrs 13 mins |
| 5 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 38,546 | 15,655 | 2.46 | 9 hrs 45 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:36:10|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
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