RESEARCH: CANCER
FOLDING PROJECT #17794 PROFILE

PROJECT TEAM

Manager(s): Matthew Chan
Institution: University of Illinois Urbana-Champaign

WORK UNIT INFO

Atoms: 65,610
Core: OPENMM_22
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project explores how proteins use ion gradients to move molecules across cell membranes. These 'secondary active transporters' are found everywhere and help with many important processes, including drug delivery. By studying them, we can learn more about how cells work and develop new treatments for diseases like cancer and diabetes.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

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

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

Secondary active transporters

Proteins that use ion gradients to transport molecules across cell membranes.

Scientific: Biotechnology
Cellular Transport / Membrane Proteins

Secondary active transporters are crucial proteins found in all living organisms. They help move various molecules across cell membranes by utilizing the energy stored in an existing ion gradient. This process is essential for numerous cellular functions, including nutrient uptake, waste removal, and signal transduction. Dysfunctional secondary active transporters are implicated in various diseases, making them attractive drug targets.


Ion gradient

A difference in ion concentration across a membrane.

Scientific: Biotechnology
Cellular Transport / Membrane Proteins

An ion gradient is a difference in the concentration of electrically charged atoms (ions) across a cell membrane. This difference in concentration creates an electrochemical potential that can be harnessed to power cellular processes. For example, ion gradients are essential for maintaining cell volume, transmitting nerve impulses, and transporting molecules across membranes.


Drug targets

Molecules or pathways that are targeted by drugs to treat diseases.

Technical: Pharmaceuticals
Pharmaceutical Research / Disease Therapy

Drug targets are specific molecules or biological processes that are involved in the development or progression of a disease. Pharmaceuticals aim to develop drugs that interact with these targets to either block their activity, enhance their function, or modulate their signaling pathways. Targeting these specific molecules can help alleviate symptoms, slow disease progression, or even cure certain diseases.


Cancer

A group of diseases characterized by uncontrolled cell growth.

Pathological: Healthcare
Medicine / Oncology

Cancer is a broad term encompassing a variety of diseases characterized by the abnormal and uncontrolled growth of cells. These cancerous cells can invade surrounding tissues, spread to other parts of the body (metastasis), and disrupt normal bodily functions. Cancer arises from mutations in DNA that regulate cell growth and division, leading to uncontrolled proliferation and tumor formation.


Diabetes

A metabolic disorder characterized by high blood sugar levels.

Pathological: Healthcare
Medicine / Endocrinology

Diabetes is a chronic condition affecting how the body regulates blood sugar (glucose). In type 1 diabetes, the immune system attacks insulin-producing cells in the pancreas. In type 2 diabetes, the body becomes resistant to insulin or doesn't produce enough. This leads to elevated blood sugar levels, which can damage various organs and tissues over time.


Neurological disorders

Conditions affecting the nervous system.

Pathological: Healthcare
Medicine / Neuroscience

Neurological disorders encompass a wide range of conditions that affect the brain, spinal cord, and peripheral nerves. These disorders can manifest in various ways, including cognitive impairment, movement problems, sensory disturbances, and emotional changes. Examples include Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:35:06
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 6,613,301 164,107 40.30 0 hrs 36 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,369,002 155,353 34.56 0 hrs 42 mins
3 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,716,658 147,396 32.00 0 hrs 45 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,370,482 142,159 30.74 0 hrs 47 mins
5 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 3,955,507 139,132 28.43 0 hrs 51 mins
6 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,373,393 132,749 25.41 0 hrs 57 mins
7 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,606,424 145,167 17.95 1 hrs 20 mins
8 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,104,258 113,234 18.58 1 hrs 17 mins
9 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,250,461 94,792 13.19 1 hrs 49 mins
10 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 873,106 79,341 11.00 2 hrs 11 mins
11 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 510,784 70,854 7.21 3 hrs 20 mins
12 P106-090
GP106 [P106-090]
Nvidia GP106 314,651 59,967 5.25 4 hrs 34 mins
13 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 133,839 45,068 2.97 8 hrs 5 mins
14 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 112,307 42,800 2.62 9 hrs 9 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:35:06
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make