Folding project #17730, CANCER research

Research section Research projects and references

Project #17730 overview

Project Summary AI Beta

This project studies how proteins use ion gradients to move molecules across cell membranes. These proteins are important for many bodily functions and are targets for drugs treating diseases like cancer and diabetes. By studying them, we can learn more about how these proteins work across different types of organisms.

Automated summary; simplified and may not be fully accurate.

Project team

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

Work unit

Atoms: 118,949
Core: OPENMM_22
Status: Public

Source material

Official 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.

Reading reference

Related Terms Glossary AI Beta

Automated high-level definitions; simplified and may not be fully accurate.

Secondary active transporters

Proteins that use ions to transport molecules across cell membranes.

Scientific: BiotechnologyMembrane Transport / Cellular Processes

Secondary active transporters are crucial proteins found in all living organisms. They utilize an existing ion gradient to power the movement of various molecules across cell membranes. This process is essential for many cellular functions and makes these transporters important targets for treating diseases like cancer, diabetes, and neurological disorders.

Ion gradient

A difference in ion concentration across a cell membrane.

Scientific: BiotechnologyMembrane Transport / Cellular Processes

An ion gradient refers to an uneven distribution of charged particles (ions) on either side of a cell membrane. This imbalance in charge is essential for various cellular processes, including nerve impulse transmission and nutrient uptake. Secondary active transporters exploit this gradient to facilitate the movement of molecules across the membrane.

Drug targets

Molecules or cellular processes that are targeted by drugs.

Scientific: BiotechnologyPharmacology / Disease Treatment

Drug targets are specific molecules or cellular pathways that are involved in the development or progression of a disease. By targeting these molecules, drugs can aim to either block their function or enhance their activity, leading to therapeutic effects.

Simulations

Computer models used to represent and study complex systems.

Scientific: BiotechnologyBiotechnology Research / Computational Biology

Simulations are powerful tools in biotechnology research that allow scientists to create virtual representations of biological processes. These models can be used to test hypotheses, explore different scenarios, and gain insights into the behavior of complex systems like proteins or entire cells.

Cancer

A group of diseases characterized by uncontrolled cell growth.

Medical: BiotechnologyDisease / Oncology

Cancer is a broad term encompassing various diseases characterized by the uncontrolled growth and spread of abnormal cells. These cells can invade surrounding tissues and organs, leading to life-threatening complications.

Diabetes

A metabolic disorder characterized by high blood sugar levels.

Medical: BiotechnologyDisease / Endocrinology

Diabetes is a chronic disease affecting how the body regulates blood sugar (glucose). In type 1 diabetes, the immune system destroys insulin-producing cells. In type 2 diabetes, the body becomes resistant to insulin or doesn't produce enough. Both types lead to high blood sugar levels, which can damage various organs over time.

Neurological disorders

Conditions affecting the nervous system.

Medical: BiotechnologyDisease / Neuroscience

Neurological disorders encompass a wide range of conditions impacting the brain, spinal cord, and nerves. These disorders can affect various aspects of neurological function, including movement, sensation, cognition, and emotions.

GPU PPD Averages

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	7,160,294	129,255	55.40	0 ^hrs 26 ^mins
2	GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB]	Nvidia	GA102	5,591,201	120,765	46.30	0 ^hrs 31 ^mins
3	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	5,004,065	115,922	43.17	0 ^hrs 33 ^mins
4	Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000]	Nvidia	TU102GL	4,311,914	109,794	39.27	0 ^hrs 37 ^mins
5	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	4,138,082	109,898	37.65	0 ^hrs 38 ^mins
6	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	3,204,411	100,376	31.92	0 ^hrs 45 ^mins
7	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	3,066,160	98,216	31.22	0 ^hrs 46 ^mins
8	GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti]	Nvidia	GA104	2,881,548	96,763	29.78	0 ^hrs 48 ^mins
9	GeForce RTX 2080 TU104 [GeForce RTX 2080]	Nvidia	TU104	2,798,254	95,877	29.19	0 ^hrs 49 ^mins
10	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER]	Nvidia	TU104	2,643,452	93,916	28.15	0 ^hrs 51 ^mins
11	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	2,404,592	87,952	27.34	0 ^hrs 53 ^mins
12	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465	Nvidia	TU106	2,357,931	91,031	25.90	0 ^hrs 56 ^mins
13	GeForce RTX 2080 SUPER Mobile / Max-Q TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q]	Nvidia	TU104M	2,290,922	90,152	25.41	0 ^hrs 57 ^mins
14	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	2,154,545	87,669	24.58	0 ^hrs 59 ^mins
15	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	2,105,051	87,497	24.06	0 ^hrs 60 ^mins
16	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	1,923,340	81,757	23.53	1 ^hrs 1 ^mins
17	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	1,859,122	84,184	22.08	1 ^hrs 5 ^mins
18	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	1,792,865	83,017	21.60	1 ^hrs 7 ^mins
19	Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]	AMD	Navi 21	1,542,723	77,828	19.82	1 ^hrs 13 ^mins

20	GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile]	Nvidia	TU106M	1,390,629	76,695	18.13	1 ^hrs 19 ^mins
21	GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186	Nvidia	GP104	1,262,451	74,658	16.91	1 ^hrs 25 ^mins
22	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	1,166,126	72,335	16.12	1 ^hrs 29 ^mins
23	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	1,058,855	69,641	15.20	1 ^hrs 35 ^mins
24	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,022,180	65,016	15.72	1 ^hrs 32 ^mins
25	GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti]	Nvidia	TU116	927,531	67,063	13.83	1 ^hrs 44 ^mins
26	P104-100 GP104 [P104-100]	Nvidia	GP104	830,282	64,372	12.90	1 ^hrs 52 ^mins
27	GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER]	Nvidia	TU116	790,682	63,204	12.51	1 ^hrs 55 ^mins
28	GeForce GTX 970 GM204 [GeForce GTX 970] 3494	Nvidia	GM204	556,015	56,353	9.87	2 ^hrs 26 ^mins
29	Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]	AMD	Navi 10	534,453	53,035	10.08	2 ^hrs 23 ^mins
30	P106-100 GP106 [P106-100]	Nvidia	GP106	522,764	55,179	9.47	2 ^hrs 32 ^mins
31	GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q]	Nvidia	TU117M	511,068	55,131	9.27	2 ^hrs 35 ^mins
32	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	500,290	52,484	9.53	2 ^hrs 31 ^mins
33	Radeon R9 200/300 Series Hawaii [Radeon R9 200/300 Series]	AMD	Hawaii	448,834	52,690	8.52	2 ^hrs 49 ^mins
34	GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984	Nvidia	TU116	376,609	49,448	7.62	3 ^hrs 9 ^mins
35	Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series]	AMD	Hawaii	349,744	48,303	7.24	3 ^hrs 19 ^mins
36	Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590]	AMD	Ellesmere XT	330,236	45,440	7.27	3 ^hrs 18 ^mins
37	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	322,125	47,126	6.84	3 ^hrs 31 ^mins
38	Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64]	AMD	Vega 10 XL/XT	309,799	40,959	7.56	3 ^hrs 10 ^mins
39	Quadro M4000 GM204GL [Quadro M4000]	Nvidia	GM204GL	275,981	44,957	6.14	3 ^hrs 55 ^mins

40	P106-090 GP106 [P106-090]	Nvidia	GP106	228,771	41,834	5.47	4 ^hrs 23 ^mins
41	Radeon R9 280/HD 7900/8950 Tahiti PRO [Radeon R9 280/HD 7900/8950]	AMD	Tahiti PRO	220,257	41,009	5.37	4 ^hrs 28 ^mins
42	GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile]	Nvidia	GP107M	206,803	40,668	5.09	4 ^hrs 43 ^mins
43	GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634	Nvidia	GK104	146,901	33,384	4.40	5 ^hrs 27 ^mins
44	Radeon HD 7800 Pitcairn [Radeon HD 7800]	AMD	Pitcairn	116,599	33,586	3.47	6 ^hrs 55 ^mins
45	Radeon RX Vega M XL [Radeon RX Vega M XL]	AMD	Vega	116,134	33,530	3.46	6 ^hrs 56 ^mins
46	Quadro P620 GP107GL [Quadro P620]	Nvidia	GP107GL	114,867	33,419	3.44	6 ^hrs 59 ^mins
47	Quadro K2200 GM107GL [Quadro K2200]	Nvidia	GM107GL	111,532	33,106	3.37	7 ^hrs 7 ^mins
48	GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389	Nvidia	GM107	110,772	32,807	3.38	7 ^hrs 6 ^mins
49	GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935	Nvidia	GP106	108,814	32,241	3.38	7 ^hrs 7 ^mins
50	GeForce GTX 760 GK104 [GeForce GTX 760] 2258	Nvidia	GK104	105,849	31,587	3.35	7 ^hrs 10 ^mins
51	GeForce GTX 960M GM107 [GeForce GTX 960M] 1439	Nvidia	GM107	101,981	31,008	3.29	7 ^hrs 18 ^mins
52	Radeon RX 460 Baffin XT [Radeon RX 460]	AMD	Baffin XT	99,932	31,972	3.13	7 ^hrs 41 ^mins
53	GeForce GT 1030 GP108 [GeForce GT 1030] 1127	Nvidia	GP108	87,671	30,472	2.88	8 ^hrs 21 ^mins
54	GTX 650 Ti Boost GK106 [GTX 650 Ti Boost]	Nvidia	GK106	78,261	29,490	2.65	9 ^hrs 3 ^mins
55	Quadro K1200 GM107GL [Quadro K1200]	Nvidia	GM107GL	75,522	29,065	2.60	9 ^hrs 14 ^mins
56	Radeon R7/R6 360 Series Bonaire [Radeon R7/R6 360 Series]	AMD	Bonaire	48,070	22,588	2.13	11 ^hrs 17 ^mins
57	Radeon R7 250/HD 7700 R575A [Radeon R7 250/HD 7700]	AMD	R575A	31,029	21,655	1.43	16 ^hrs 45 ^mins

Research: CANCER Folding Project #17730

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 17730

GPU PPD Averages

Research: CANCER Folding Project #17730

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages