RESEARCH: CANCER
FOLDING PROJECT #17747 PROFILE
PROJECT TEAM
Manager(s): Matthew ChanInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 77,576Core: OPENMM_22
Status: Beta
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how proteins called secondary active transporters use ions to move molecules across cell membranes. These transporters are important for many things and are even drug targets for diseases like cancer and diabetes. By simulating these transporters, researchers hope to understand how they work across different types of proteins.
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 a type of protein found in all living organisms. They play a crucial role in moving molecules across cell membranes by using the energy stored in an ion gradient. This process is essential for many cellular functions, such as nutrient uptake and waste removal. These transporters are important drug targets for treating various diseases like cancer, diabetes, and neurological disorders.
Ion gradient
A difference in ion concentration across a cell membrane.
An ion gradient is a difference in the concentration of charged particles (ions) on either side of a cell membrane. This difference in concentration creates a potential energy that can be used to drive various cellular processes, such as the transport of molecules across the membrane. Secondary active transporters utilize this energy stored in the ion gradient to move other molecules against their concentration gradient.
Drug targets
Molecules or pathways that are involved in the development or progression of a disease and can be targeted by drugs.
Drug targets are specific molecules or biological pathways within cells that are implicated in the development or progression of diseases. Pharmaceutical companies identify these targets and develop drugs that aim to interfere with their function, ultimately treating the disease. Secondary active transporters are frequently drug targets for various conditions such as cancer, diabetes, and neurological disorders.
Simulations
Computer models used to mimic complex biological processes.
Simulations are computer programs that create virtual representations of biological systems. These models allow researchers to study complex processes like protein interactions and drug mechanisms in a controlled environment. By running simulations, scientists can gain insights into how molecules work and potentially discover new drugs or therapies.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:36:07|
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 | 6,744,886 | 77,176 | 87.40 | 0 hrs 16 mins |
| 2 | TITAN Xp GP102 [TITAN Xp] 12150 |
Nvidia | GP102 | 2,764,912 | 57,666 | 47.95 | 0 hrs 30 mins |
| 3 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 1,936,915 | 51,561 | 37.57 | 0 hrs 38 mins |
| 4 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,810,619 | 70,711 | 25.61 | 0 hrs 56 mins |
| 5 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 879,560 | 39,598 | 22.21 | 1 hrs 5 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:36:07|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
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