RESEARCH: CANCER
FOLDING PROJECT #17764 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 92,122
Core: OPENMM_22
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project looks at how proteins use energy from ions to move molecules across cell membranes. These proteins are found everywhere and are important for things like fighting cancer, diabetes, and brain disorders. By studying these proteins, we can learn how they work and maybe find new ways to treat diseases.

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

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

Secondary active transporters

Proteins that use ions to transport molecules across cell membranes.

Scientific: Medicine
Biotechnology / Cellular Transport

Secondary active transporters are essential proteins found in all living organisms. They work by utilizing an existing ion gradient to power the movement of other molecules across cell membranes. This process is crucial for various biological functions, including nutrient uptake, waste removal, and signal transduction. Many secondary active transporters are also drug targets for treating diseases like cancer, diabetes, and neurological disorders.


Membrane transporters

Proteins that move molecules across cell membranes.

Scientific: Medicine
Biotechnology / Cellular Transport

Membrane transporters are proteins embedded within the cell membrane that play a vital role in regulating the movement of substances into and out of the cell. They facilitate the transport of nutrients, ions, waste products, and signaling molecules across this selective barrier. Different types of membrane transporters exist, including passive transporters (which move substances down their concentration gradient) and active transporters (which require energy to move substances against their concentration gradient).


Ion gradient

A difference in ion concentration across a membrane.

Scientific: Medicine
Biotechnology / Cellular Transport

An ion gradient is a fundamental concept in cellular biology that describes the unequal distribution of charged particles (ions) across a cell membrane. This difference in concentration creates an electrochemical potential that can be harnessed by cells for various purposes, such as powering active transport processes, generating nerve impulses, and maintaining cellular pH balance.


Drug targets

Molecules or biological processes that are potential therapeutic targets.

Technical: Medicine
Biotechnology / Pharmacology

Drug targets are specific molecules or cellular pathways that pharmaceutical companies aim to modulate (activate, inhibit, or modify) in order to treat diseases. These targets can include proteins, enzymes, receptors, DNA sequences, or even entire signaling networks. Identifying and understanding drug targets is crucial for the development of new and effective medications.


Cancer

A disease characterized by uncontrolled cell growth and spread.

Pathology: Healthcare
Medicine / Oncology

Cancer is a group of diseases characterized by the abnormal growth and spread of cells. These cells divide uncontrollably and can invade surrounding tissues and organs. Cancer arises from mutations in DNA that disrupt normal cellular regulatory mechanisms, leading to unchecked proliferation and evasion of cell death. Various factors contribute to cancer development, including genetic predisposition, environmental exposures, and lifestyle choices.


Diabetes

A metabolic disorder characterized by high blood sugar levels.

Pathology: Healthcare
Medicine / Endocrinology

Diabetes is a chronic metabolic disorder characterized by elevated levels of glucose (sugar) in the bloodstream. This occurs when the body either does not produce enough insulin (Type 1 diabetes) or cannot effectively use the insulin it produces (Type 2 diabetes). Insulin is a hormone that regulates blood sugar by allowing glucose to enter cells for energy production. Without sufficient insulin, glucose builds up in the bloodstream, leading to various complications such as damage to blood vessels, nerves, and organs.


Neurological disorders

Conditions affecting the nervous system.

Pathology: Healthcare
Medicine / Neuroscience

Neurological disorders encompass a wide range of conditions that affect the brain, spinal cord, and peripheral nerves. These disorders can manifest as various symptoms, including impaired movement, sensation, cognition, and behavior. Some common neurological disorders include Alzheimer's disease, Parkinson's disease, stroke, epilepsy, multiple sclerosis, and autism spectrum disorder.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:35:53
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 8,172,780 160,528 50.91 0 hrs 28 mins
2 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 7,415,068 157,190 47.17 0 hrs 31 mins
3 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 7,216,091 153,845 46.90 0 hrs 31 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 5,482,261 142,647 38.43 0 hrs 37 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,739,967 135,196 35.06 0 hrs 41 mins
6 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 4,349,115 132,508 32.82 0 hrs 44 mins
7 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 4,324,601 132,583 32.62 0 hrs 44 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,926,997 127,085 30.90 0 hrs 47 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,376,562 121,150 27.87 0 hrs 52 mins
10 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,731,355 113,806 24.00 0 hrs 60 mins
11 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,713,256 108,417 25.03 0 hrs 58 mins
12 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,691,698 112,154 24.00 0 hrs 60 mins
13 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 2,279,217 117,813 19.35 1 hrs 14 mins
14 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 1,480,923 92,585 16.00 1 hrs 30 mins
15 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,367,708 90,231 15.16 1 hrs 35 mins
16 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,262,683 87,686 14.40 1 hrs 40 mins
17 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,248,564 84,171 14.83 1 hrs 37 mins
18 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 1,213,755 86,607 14.01 1 hrs 43 mins
19 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,194,560 85,710 13.94 1 hrs 43 mins
20 Radeon RX 6800/6800 XT / 6900 XT
Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]
AMD Navi 21 956,514 73,407 13.03 1 hrs 51 mins
21 Radeon Pro W5700
Navi 10 [Radeon Pro W5700]
AMD Navi 10 898,240 74,453 12.06 1 hrs 59 mins
22 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 880,958 77,491 11.37 2 hrs 7 mins
23 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 725,001 72,946 9.94 2 hrs 25 mins
24 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 551,206 66,158 8.33 2 hrs 53 mins
25 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 550,416 66,146 8.32 2 hrs 53 mins
26 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 546,232 66,382 8.23 2 hrs 55 mins
27 Radeon VII
Vega 20 [Radeon VII] 13,284
AMD Vega 20 544,146 66,253 8.21 2 hrs 55 mins
28 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 445,205 61,886 7.19 3 hrs 20 mins
29 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 312,328 54,313 5.75 4 hrs 10 mins
30 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 221,900 48,090 4.61 5 hrs 12 mins
31 Radeon HD 7800 Series
Pitcairn PRO [Radeon HD 7800 Series]
AMD Pitcairn PRO 101,225 37,725 2.68 8 hrs 57 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:35:53
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make