Folding project #17742, CANCER research

Research section Research projects and references

Project #17742 overview

Project Summary AI Beta

This project looks at how proteins use energy from ions to move other molecules across cell membranes. These proteins are important for many bodily functions and are even targets for medicines treating diseases like cancer and diabetes. By studying them, we can learn how different types of proteins work together.

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: 115,098
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 transporter

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

Scientific: Pharmaceuticals, BiotechnologyBiochemistry / Membrane Transport

Secondary active transporters are essential proteins found in all living organisms. They use the energy stored in an ion gradient to move other molecules across cell membranes. This process is crucial for many biological functions, including nutrient uptake, waste removal, and signaling. These transporters are often targets for drugs used to treat diseases like cancer, diabetes, and neurological disorders.

Membrane transporter

A protein that facilitates the movement of molecules across cell membranes.

Scientific: Pharmaceuticals, BiotechnologyBiochemistry / Cellular Transport

Membrane transporters are proteins embedded in cell membranes that play a vital role in regulating what enters and exits cells. They transport a wide variety of molecules, including nutrients, ions, and waste products. This process is essential for maintaining cellular homeostasis and carrying out various biological functions.

Ion gradient

A difference in the concentration of ions across a membrane.

Scientific: Pharmaceuticals, BiotechnologyBiochemistry / Membrane Transport

An ion gradient refers to an uneven distribution of charged particles (ions) across a cell membrane. This gradient is often established by active transport processes that move ions against their concentration gradient, requiring energy. The resulting electrochemical potential difference drives various cellular functions, including nerve impulse transmission and nutrient uptake.

Drug targets

Molecules or cellular processes that are targeted by drugs to treat diseases.

Technical: PharmaceuticalsPharmacology / Disease Treatment

Drug targets are specific molecules or biological pathways involved in disease development. Pharmaceutical companies aim to develop drugs that interact with these targets and modulate their activity to alleviate symptoms or cure diseases. Examples include enzymes, receptors, and ion channels.

Simulations

Computer-based models that mimic biological processes.

Scientific: Pharmaceuticals, BiotechnologyBioinformatics / Molecular Modeling

Simulations are powerful tools used in bioinformatics to study complex biological systems. By creating computer models of molecules, cells, or even entire organisms, researchers can explore various scenarios and gain insights into their behavior. Simulations are widely employed in drug discovery, disease modeling, and understanding fundamental biological mechanisms.

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	7,724,987	128,110	60.30	0 ^hrs 24 ^mins
2	GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB]	Nvidia	GA102	5,911,447	117,654	50.24	0 ^hrs 29 ^mins
3	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	5,073,108	111,965	45.31	0 ^hrs 32 ^mins
4	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	4,665,183	107,990	43.20	0 ^hrs 33 ^mins
5	Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000]	Nvidia	TU102GL	4,332,844	105,312	41.14	0 ^hrs 35 ^mins
6	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	3,247,852	96,634	33.61	0 ^hrs 43 ^mins
7	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	3,101,908	94,906	32.68	0 ^hrs 44 ^mins
8	GeForce RTX 2080 TU104 [GeForce RTX 2080]	Nvidia	TU104	3,002,877	94,654	31.72	0 ^hrs 45 ^mins
9	GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti]	Nvidia	GA104	2,896,633	92,749	31.23	0 ^hrs 46 ^mins
10	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER]	Nvidia	TU104	2,821,008	92,055	30.64	0 ^hrs 47 ^mins
11	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	2,376,186	86,568	27.45	0 ^hrs 52 ^mins
12	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465	Nvidia	TU106	2,365,288	87,398	27.06	0 ^hrs 53 ^mins
13	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,339,922	86,961	26.91	0 ^hrs 54 ^mins
14	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	2,163,037	84,687	25.54	0 ^hrs 56 ^mins
15	GeForce RTX 2080 SUPER Mobile / Max-Q TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q]	Nvidia	TU104M	2,134,371	83,991	25.41	0 ^hrs 57 ^mins
16	GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497	Nvidia	TU106	2,097,332	83,528	25.11	0 ^hrs 57 ^mins
17	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	1,841,350	80,249	22.95	1 ^hrs 3 ^mins
18	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	1,816,224	79,398	22.87	1 ^hrs 3 ^mins
19	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	1,713,055	77,281	22.17	1 ^hrs 5 ^mins

20	GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q]	Nvidia	GA106M	1,680,485	77,800	21.60	1 ^hrs 7 ^mins
21	Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]	AMD	Navi 21	1,626,876	76,254	21.33	1 ^hrs 7 ^mins
22	GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186	Nvidia	GP104	1,406,063	72,737	19.33	1 ^hrs 14 ^mins
23	GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile]	Nvidia	TU106M	1,333,638	72,547	18.38	1 ^hrs 18 ^mins
24	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	1,168,620	69,556	16.80	1 ^hrs 26 ^mins
25	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,018,701	66,029	15.43	1 ^hrs 33 ^mins
26	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	977,825	60,755	16.09	1 ^hrs 29 ^mins
27	GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti]	Nvidia	TU116	928,143	64,082	14.48	1 ^hrs 39 ^mins
28	P104-100 GP104 [P104-100]	Nvidia	GP104	808,823	61,074	13.24	1 ^hrs 49 ^mins
29	GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER]	Nvidia	TU116	754,446	59,662	12.65	1 ^hrs 54 ^mins
30	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	664,370	57,307	11.59	2 ^hrs 4 ^mins
31	Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]	AMD	Navi 10	585,449	53,631	10.92	2 ^hrs 12 ^mins
32	GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935	Nvidia	GP106	575,832	54,568	10.55	2 ^hrs 16 ^mins
33	GeForce GTX 970 GM204 [GeForce GTX 970] 3494	Nvidia	GM204	566,429	54,354	10.42	2 ^hrs 18 ^mins
34	P106-100 GP106 [P106-100]	Nvidia	GP106	514,340	52,649	9.77	2 ^hrs 27 ^mins
35	GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q]	Nvidia	TU117M	492,906	51,891	9.50	2 ^hrs 32 ^mins
36	GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984	Nvidia	TU116	398,857	48,375	8.25	2 ^hrs 55 ^mins
37	Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64]	AMD	Vega 10 XL/XT	361,213	42,786	8.44	2 ^hrs 51 ^mins
38	Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series]	AMD	Hawaii	348,903	46,281	7.54	3 ^hrs 11 ^mins
39	Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590]	AMD	Ellesmere XT	264,887	39,612	6.69	3 ^hrs 35 ^mins

40	Radeon R9 200/300 Series Hawaii [Radeon R9 200/300 Series]	AMD	Hawaii	260,777	42,256	6.17	3 ^hrs 53 ^mins
41	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	252,480	41,820	6.04	3 ^hrs 59 ^mins
42	Radeon R9 280/HD 7900/8950 Tahiti PRO [Radeon R9 280/HD 7900/8950]	AMD	Tahiti PRO	232,510	40,248	5.78	4 ^hrs 9 ^mins
43	GeForce GTX 1050 Ti Mobile GP107M [GeForce GTX 1050 Ti Mobile]	Nvidia	GP107M	224,013	40,064	5.59	4 ^hrs 18 ^mins
44	P106-090 GP106 [P106-090]	Nvidia	GP106	221,074	39,834	5.55	4 ^hrs 19 ^mins
45	GeForce GTX 950 GM206 [GeForce GTX 950] 1572	Nvidia	GM206	210,270	38,178	5.51	4 ^hrs 21 ^mins
46	GeForce GTX 1050 Mobile GP107M [GeForce GTX 1050 Mobile]	Nvidia	GP107M	189,786	37,704	5.03	4 ^hrs 46 ^mins
47	GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634	Nvidia	GK104	158,097	35,151	4.50	5 ^hrs 20 ^mins
48	Radeon RX Vega M XL [Radeon RX Vega M XL]	AMD	Vega	122,191	32,714	3.74	6 ^hrs 26 ^mins
49	Radeon HD 7800 Pitcairn [Radeon HD 7800]	AMD	Pitcairn	115,878	32,038	3.62	6 ^hrs 38 ^mins
50	Quadro P620 GP107GL [Quadro P620]	Nvidia	GP107GL	115,397	32,163	3.59	6 ^hrs 41 ^mins
51	GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389	Nvidia	GM107	112,889	31,547	3.58	6 ^hrs 42 ^mins
52	GeForce GTX 770 GK104 [GeForce GTX 770] 3213	Nvidia	GK104	111,249	30,516	3.65	6 ^hrs 35 ^mins
53	Quadro K2200 GM107GL [Quadro K2200]	Nvidia	GM107GL	110,628	31,679	3.49	6 ^hrs 52 ^mins
54	Radeon RX 460 Baffin XT [Radeon RX 460]	AMD	Baffin XT	98,587	30,484	3.23	7 ^hrs 25 ^mins
55	GeForce GT 1030 GP108 [GeForce GT 1030] 1127	Nvidia	GP108	90,221	29,558	3.05	7 ^hrs 52 ^mins
56	GTX 650 Ti Boost GK106 [GTX 650 Ti Boost]	Nvidia	GK106	78,623	28,237	2.78	8 ^hrs 37 ^mins
57	Quadro K1200 GM107GL [Quadro K1200]	Nvidia	GM107GL	75,067	27,856	2.69	8 ^hrs 54 ^mins
58	Quadro K620 GM107GL [Quadro K620]	Nvidia	GM107GL	50,204	24,308	2.07	11 ^hrs 37 ^mins
59	GeForce 920M GK208 [GeForce 920M]	Nvidia	GK208	26,390	19,710	1.34	17 ^hrs 55 ^mins

60	Radeon APU A4-6000 R2 Mullins [Radeon APU A4-6000 R2]	AMD	Mullins	2,334	11,370	0.21	116 ^hrs 55 ^mins

Research: CANCER Folding Project #17742

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 17742

GPU PPD Averages

Research: CANCER Folding Project #17742

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages