Folding project #18710, CANCER research

Research section Research projects and references

Project #18710 overview

Project Summary AI Beta

Scientists are testing a new computer model called FPOP to find promising cancer treatments. They're using it on beta-lactamase TEM-1, a well-studied protein, and sharing all the data publicly. This project is a partnership between Folding@home and Roivant Sciences.

Automated summary; simplified and may not be fully accurate.

Project team

Manager(s): Rafal Wiewiora
Institution: Roivant Sciences (Silicon Therapeutics)
Website: Open project site

Work unit

Atoms: 46,086
Core: 0x22
Status: Public

No related projects listed.

Source material

Official Project Description

Here we are collecting data to test a new experimental reweighting method called FPOP (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690683/) fot use in modeling of new cancer target hits.

The protein running is the old friend, beta-lactamase TEM-1, for which plenty of experimental data exists. This is a project run by Roivant Sciences (formerly Silicon Therapeutics) as was officially announced in this press release: https://foldingathome.org/2021/04/20/maximizing-the-impact-of-foldinghome-by-engaging-industry-collaborators/ All data is being made publicly available as soon as it is received at https://console.cloud.google.com/storage/browser/stxfah-bucket.

Reading reference

Related Terms Glossary AI Beta

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

FPOP

Experimental reweighting method for protein modeling

Acronym: PharmaceuticalBiotechnology / Drug Discovery

FPOP stands for Fold-Protein Optimization Protocol. It's a new technique being used to improve the accuracy of computer models predicting how proteins fold. This is important for drug discovery, as understanding how proteins fold can help scientists design drugs that interact with them more effectively.

beta-lactamase

An enzyme that breaks down beta-lactam antibiotics

Technical: PharmaceuticalBiotechnology / Antimicrobial Resistance

Beta-lactamase is an enzyme produced by some bacteria that allows them to resist the effects of certain antibiotics, called beta-lactams. These antibiotics work by interfering with the construction of bacterial cell walls. Beta-lactamases break down the beta-lactam ring in these antibiotics, rendering them ineffective.

TEM-1

A type of beta-lactamase enzyme

Technical: PharmaceuticalBiotechnology / Antimicrobial Resistance

TEM-1 is a specific type of beta-lactamase enzyme, commonly found in bacteria like Escherichia coli. It's known for its ability to break down various beta-lactam antibiotics, leading to antibiotic resistance.

Roivant Sciences

A biopharmaceutical company focused on developing new therapies

Company: PharmaceuticalBiotechnology / Drug Development

Roivant Sciences is a pharmaceutical company dedicated to accelerating the development of new drugs. They use innovative approaches and technologies to bring promising treatments to patients faster. Their projects often involve collaborations with academic institutions and other industry partners.

Silicon Therapeutics

A former name for Roivant Sciences

Company: PharmaceuticalBiotechnology / Drug Development

Silicon Therapeutics was the previous name for Roivant Sciences. They rebranded to Roivant Sciences as they expanded their operations and focus.

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 4090 AD102 [GeForce RTX 4090]	Nvidia	AD102	4,757,489	231,806	20.52	1 ^hrs 10 ^mins
2	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	4,334,877	251,125	17.26	1 ^hrs 23 ^mins
3	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	4,238,785	246,059	17.23	1 ^hrs 24 ^mins
4	GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti]	Nvidia	GA102	3,977,124	246,701	16.12	1 ^hrs 29 ^mins
5	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	3,844,065	239,600	16.04	1 ^hrs 30 ^mins
6	GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB]	Nvidia	GA102	3,807,838	242,322	15.71	1 ^hrs 32 ^mins
7	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	3,439,453	232,040	14.82	1 ^hrs 37 ^mins
8	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	3,276,784	228,866	14.32	1 ^hrs 41 ^mins
9	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	3,257,566	230,018	14.16	1 ^hrs 42 ^mins
10	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	3,028,734	222,909	13.59	1 ^hrs 46 ^mins
11	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	2,826,394	220,269	12.83	1 ^hrs 52 ^mins
12	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	2,791,442	217,966	12.81	1 ^hrs 52 ^mins
13	GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate]	Nvidia	GA104	2,749,406	216,275	12.71	1 ^hrs 53 ^mins
14	TITAN X GP102 [TITAN X] 6144	Nvidia	GP102	2,371,728	207,547	11.43	2 ^hrs 6 ^mins
15	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	2,179,061	200,606	10.86	2 ^hrs 13 ^mins
16	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER]	Nvidia	TU104	2,046,413	197,120	10.38	2 ^hrs 19 ^mins
17	GeForce RTX 2080 TU104 [GeForce RTX 2080]	Nvidia	TU104	1,939,655	195,146	9.94	2 ^hrs 25 ^mins
18	GeForce RTX 2070 TU106 [GeForce RTX 2070]	Nvidia	TU106	1,823,389	188,845	9.66	2 ^hrs 29 ^mins
19	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	1,758,577	187,076	9.40	2 ^hrs 33 ^mins

20	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	1,727,962	183,835	9.40	2 ^hrs 33 ^mins
21	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	1,590,647	181,659	8.76	2 ^hrs 44 ^mins
22	GeForce RTX 3060 GA104 [GeForce RTX 3060]	Nvidia	GA104	1,577,969	181,078	8.71	2 ^hrs 45 ^mins
23	Geforce RTX 3070 Ti Laptop GPU GA104 [Geforce RTX 3070 Ti Laptop GPU]	Nvidia	GA104	1,531,105	182,575	8.39	2 ^hrs 52 ^mins
24	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	1,528,746	179,722	8.51	2 ^hrs 49 ^mins
25	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	1,499,197	178,685	8.39	2 ^hrs 52 ^mins
26	GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti]	Nvidia	GA104	1,364,253	172,226	7.92	3 ^hrs 2 ^mins
27	A40 GA102GL [A40]	Nvidia	GA102GL	1,328,298	164,910	8.05	2 ^hrs 59 ^mins
28	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	1,285,803	169,105	7.60	3 ^hrs 9 ^mins
29	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	1,220,600	151,595	8.05	2 ^hrs 59 ^mins
30	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,213,257	165,950	7.31	3 ^hrs 17 ^mins
31	Quadro RTX 4000 TU104GL [Quadro RTX 4000]	Nvidia	TU104GL	1,155,797	163,051	7.09	3 ^hrs 23 ^mins
32	GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186	Nvidia	GP104	1,120,850	162,415	6.90	3 ^hrs 29 ^mins
33	GeForce GTX Titan X GM200 [GeForce GTX Titan X] 6144	Nvidia	GM200	1,045,319	160,053	6.53	3 ^hrs 40 ^mins
34	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	1,036,598	157,980	6.56	3 ^hrs 39 ^mins
35	GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile]	Nvidia	TU116M	1,005,850	155,928	6.45	3 ^hrs 43 ^mins
36	GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti]	Nvidia	TU116	997,142	157,845	6.32	3 ^hrs 48 ^mins
37	Geforce RTX 3050 GA106 [Geforce RTX 3050]	Nvidia	GA106	921,618	151,836	6.07	3 ^hrs 57 ^mins
38	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	917,580	151,863	6.04	3 ^hrs 58 ^mins
39	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	908,964	148,462	6.12	3 ^hrs 55 ^mins

40	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	740,330	140,685	5.26	4 ^hrs 34 ^mins
41	Tesla M40 GM200GL [Tesla M40] 6844	Nvidia	GM200GL	700,566	138,056	5.07	4 ^hrs 44 ^mins
42	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	651,848	136,269	4.78	5 ^hrs 1 ^mins
43	GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER]	Nvidia	TU116	612,650	136,698	4.48	5 ^hrs 21 ^mins
44	GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935	Nvidia	GP106	595,317	121,346	4.91	4 ^hrs 54 ^mins
45	GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile]	Nvidia	GP106M	577,030	129,495	4.46	5 ^hrs 23 ^mins
46	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	522,660	126,798	4.12	5 ^hrs 49 ^mins
47	GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q]	Nvidia	TU117M	498,733	123,026	4.05	5 ^hrs 55 ^mins
48	GeForce GTX 1650 TU117 [GeForce GTX 1650]	Nvidia	TU117	425,623	116,873	3.64	6 ^hrs 35 ^mins
49	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	345,300	111,836	3.09	7 ^hrs 46 ^mins
50	GeForce GTX 980M GM204 [GeForce GTX 980M] 3189	Nvidia	GM204	331,869	104,356	3.18	7 ^hrs 33 ^mins
51	P106-090 GP106 [P106-090]	Nvidia	GP106	281,426	101,809	2.76	8 ^hrs 41 ^mins
52	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	237,371	94,853	2.50	9 ^hrs 35 ^mins
53	GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862	Nvidia	GP107	194,007	97,941	1.98	12 ^hrs 7 ^mins
54	Quadro P1000 GP107GL [Quadro P1000]	Nvidia	GP107GL	141,461	80,837	1.75	13 ^hrs 43 ^mins
55	GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389	Nvidia	GM107	129,498	77,906	1.66	14 ^hrs 26 ^mins
56	GeForce GT 1030 GP108 [GeForce GT 1030]	Nvidia	GP108	115,260	75,501	1.53	15 ^hrs 43 ^mins
57	Quadro K2200 GM107GL [Quadro K2200]	Nvidia	GM107GL	106,252	73,688	1.44	16 ^hrs 39 ^mins
58	Quadro K1200 GM107GL [Quadro K1200]	Nvidia	GM107GL	72,159	64,826	1.11	21 ^hrs 34 ^mins
59	Quadro K620 GM107GL [Quadro K620]	Nvidia	GM107GL	66,913	52,197	1.28	18 ^hrs 43 ^mins

60	Quadro P400 GP107GL [Quadro P400]	Nvidia	GP107GL	40,620	50,439	0.81	29 ^hrs 48 ^mins

Research: CANCER Folding Project #18710

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 18710

GPU PPD Averages

Research: CANCER Folding Project #18710

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages