RESEARCH: CANCER
FOLDING PROJECT #17737 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 51,029
Core: OPENMM_22
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project explores how proteins use ion power to move molecules across cell membranes. These 'secondary active transporters' are important for many bodily functions and are targets for treating diseases like cancer and diabetes. By studying them, we can learn about how different types of proteins work together.

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

OFFICAL PROJECT DESCRIPTION

Projects 17711-17724 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 disease like cancer, diabetes, and neurological disorders.

These simulations 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: Biotechnology
Biochemistry / Membrane Transport

Secondary active transporters are crucial proteins found in all living organisms. They work by using an existing ion gradient to power the movement of other molecules across cell membranes. These transporters are involved in various essential cellular processes and are also important drug targets for treating diseases like cancer, diabetes, and neurological disorders.


Ion Gradient

A difference in ion concentration across a cell membrane.

Scientific: Pharmaceutical Research
Biochemistry / Membrane Transport

An ion gradient refers to the unequal distribution of ions, such as sodium or potassium, on either side of a cell membrane. This difference in concentration creates an electrochemical potential that drives various cellular processes, including nerve impulse transmission and nutrient uptake.


Drug Targets

Molecules or pathways that are potential therapeutic targets for drug development.

Technical: Pharmaceutical Industry
Pharmacology / Drug Discovery

Drug targets are specific molecules or cellular pathways involved in disease processes. By inhibiting or modulating these targets, drugs can exert their therapeutic effects. Identifying and targeting appropriate drug targets is a crucial step in the drug discovery process.


Simulations

Computer-based models that mimic biological processes.

Technical: Biotechnology
Bioinformatics / Computational Modeling

Simulations are powerful tools used in bioinformatics to study complex biological systems. By creating computer models that mimic real-world processes, researchers can explore various scenarios and gain insights into how biological systems function.


Proteins

Large biomolecules essential for various cellular functions.

Scientific: Life Sciences
Biochemistry / Molecular Biology

Proteins are the workhorses of cells, performing a wide range of functions such as catalyzing biochemical reactions, transporting molecules, providing structural support, and regulating cellular processes. Their diverse structures and functions make them vital components of all living organisms.


Cancer

A group of diseases characterized by abnormal cell growth.

Clinical: Healthcare
Oncology / Pathology

Cancer is a complex group of diseases where cells grow uncontrollably and spread to other parts of the body. This uncontrolled growth can result from genetic mutations or environmental factors, leading to various forms of cancer affecting different organs and tissues.


Diabetes

A group of metabolic disorders characterized by high blood sugar levels.

Clinical: Healthcare
Endocrinology / Metabolic Disorders

Diabetes is a chronic condition where the body struggles to regulate blood sugar levels. There are different types of diabetes, including type 1 and type 2. In type 1 diabetes, the immune system attacks insulin-producing cells, while in type 2 diabetes, the body becomes resistant to insulin or doesn't produce enough. High blood sugar can lead to various complications affecting the heart, kidneys, eyes, and nerves.


Neurological Disorders

Conditions that affect the nervous system.

Clinical: Healthcare
Neurology / Brain Diseases

Neurological disorders encompass a wide range of conditions affecting the brain, spinal cord, and nerves. These disorders can cause various symptoms, including seizures, paralysis, memory problems, and cognitive decline. Examples include Alzheimer's disease, Parkinson's disease, stroke, and multiple sclerosis.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:36:17
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 6,133,718 85,191 72.00 0 hrs 20 mins
2 GeForce RTX 3080 10GB / 20GB
GA102 [GeForce RTX 3080 10GB / 20GB]
Nvidia GA102 4,987,276 80,610 61.87 0 hrs 23 mins
3 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,738,350 79,223 59.81 0 hrs 24 mins
4 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 4,030,821 74,644 54.00 0 hrs 27 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,755,017 73,883 50.82 0 hrs 28 mins
6 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,060,763 68,699 44.55 0 hrs 32 mins
7 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 3,010,220 68,270 44.09 0 hrs 33 mins
8 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 2,836,885 66,815 42.46 0 hrs 34 mins
9 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,797,173 67,101 41.69 0 hrs 35 mins
10 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,699,771 65,899 40.97 0 hrs 35 mins
11 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,378,138 62,993 37.75 0 hrs 38 mins
12 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,357,623 63,442 37.16 0 hrs 39 mins
13 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,314,290 62,254 37.17 0 hrs 39 mins
14 GeForce RTX 2080 SUPER Mobile / Max-Q
TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q]
Nvidia TU104M 2,235,569 62,099 36.00 0 hrs 40 mins
15 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 2,070,378 60,578 34.18 0 hrs 42 mins
16 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,009,020 59,728 33.64 0 hrs 43 mins
17 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,759,058 57,227 30.74 0 hrs 47 mins
18 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,699,896 56,585 30.04 0 hrs 48 mins
19 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,461,737 54,157 26.99 0 hrs 53 mins
20 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,321,992 52,022 25.41 0 hrs 57 mins
21 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,173,748 50,136 23.41 1 hrs 2 mins
22 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,166,796 50,538 23.09 1 hrs 2 mins
23 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,106,311 49,189 22.49 1 hrs 4 mins
24 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,087,326 41,087 26.46 0 hrs 54 mins
25 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile] 4608
Nvidia TU106M 1,076,482 48,553 22.17 1 hrs 5 mins
26 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 964,331 46,931 20.55 1 hrs 10 mins
27 P104-100
GP104 [P104-100]
Nvidia GP104 697,091 42,219 16.51 1 hrs 27 mins
28 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 661,280 41,528 15.92 1 hrs 30 mins
29 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 513,164 38,087 13.47 1 hrs 47 mins
30 P106-100
GP106 [P106-100]
Nvidia GP106 451,975 36,352 12.43 1 hrs 56 mins
31 GeForce GTX 1650
TU116 [GeForce GTX 1650] 2984
Nvidia TU116 411,861 35,268 11.68 2 hrs 3 mins
32 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 308,073 32,145 9.58 2 hrs 30 mins
33 P106-090
GP106 [P106-090]
Nvidia GP106 212,321 28,512 7.45 3 hrs 13 mins
34 GeForce GTX 1050 Ti Mobile
GP107M [GeForce GTX 1050 Ti Mobile]
Nvidia GP107M 210,391 28,429 7.40 3 hrs 15 mins
35 GeForce GTX 660 Ti
GK104 [GeForce GTX 660 Ti] 2634
Nvidia GK104 135,349 21,775 6.22 3 hrs 52 mins
36 Quadro K2200
GM107GL [Quadro K2200]
Nvidia GM107GL 109,321 22,859 4.78 5 hrs 1 mins
37 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 95,790 19,843 4.83 4 hrs 58 mins
38 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 88,678 21,310 4.16 5 hrs 46 mins
39 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 74,041 20,071 3.69 6 hrs 30 mins
40 GeForce GT 710
GK208B [GeForce GT 710] 366
Nvidia GK208B 8,666 9,743 0.89 26 hrs 59 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:36:17
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make