Folding project #12113, PEPTIDE-CONFORMATION-MODELING research

Research section Research projects and references

Project #12113 overview

Project Summary AI Beta

Peptides are tiny proteins that can be used as medicine, but they break down easily. The project relates to using a special type of polymer called a 'protein brush' to protect peptides and help them work better. They are studying a specific peptide called Trpzip2 to see how its shape affects the polymer's structure.

Automated summary; simplified and may not be fully accurate.

Project team

Manager(s): Hassan Nadeem
Institution: University of Illinois at Urbana-Champaign

Work unit

Atoms: 56,609
Core: 0x22
Status: Public

Source material

Official Project Description

Protein Brush Polymers Short peptides are considered ideal therapeutics because of their small size and bioactivity, however they are prone to enzyme degradation.

Protein Brush Polymers allow peptides to bind to a hydrophobic backbone in a polymeric scheme which enhances the penetration of these peptides in cell/targets. In this project we simulate Trpzip2, which is a beta-hairpin peptide, for investigation of beta-sheet secondary structure effect on the polymer conformation.

Reading reference

Related Terms Glossary AI Beta

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

Protein

A large biological molecule made up of chains of amino acids.

Scientific: MedicineBiotechnology / Pharmacology

Proteins are essential molecules found in all living organisms. They perform a wide variety of functions, including catalyzing biochemical reactions, transporting molecules, providing structural support, and regulating cellular processes.

Peptides

Short chains of amino acids linked together.

Scientific: MedicineBiotechnology / Pharmacology

Peptides are smaller chains of amino acids compared to proteins. They often have specific functions in the body, such as signaling or regulating cellular processes.

Polymers

Large molecules made up of repeating structural units called monomers.

Scientific: MedicineMaterials Science / Biotechnology

Polymers are long chains of molecules that can have various properties depending on their structure. They are used in a wide range of applications, including plastics, fibers, and biomaterials.

Trpzip2

A beta-hairpin peptide used in protein folding studies.

Scientific: MedicineBiotechnology / Pharmacology

Trpzip2 is a short protein fragment that forms a specific structure known as a beta-hairpin. It is commonly used as a model system to investigate the principles of protein folding and aggregation.

Beta-sheet

A common protein structure consisting of beta strands arranged side by side.

Scientific: MedicineBiotechnology / Structural Biology

Beta-sheets are structural elements in proteins formed by parallel or antiparallel arrangement of beta strands. They contribute to the stability and function of many proteins.

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	10,697,158	319,896	33.44	0 ^hrs 43 ^mins
2	GeForce RTX 4080 AD103 [GeForce RTX 4080]	Nvidia	AD103	9,246,745	307,919	30.03	0 ^hrs 48 ^mins
3	GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti]	Nvidia	AD104	8,283,644	295,919	27.99	0 ^hrs 51 ^mins
4	GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti]	Nvidia	GA102	6,229,316	271,691	22.93	1 ^hrs 3 ^mins
5	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	6,179,489	263,045	23.49	1 ^hrs 1 ^mins
6	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	5,536,348	257,554	21.50	1 ^hrs 7 ^mins
7	RTX A6000 GA102GL [RTX A6000]	Nvidia	GA102GL	5,508,101	261,202	21.09	1 ^hrs 8 ^mins
8	GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB]	Nvidia	GA102	5,381,989	251,841	21.37	1 ^hrs 7 ^mins
9	GeForce RTX 4070 AD104 [GeForce RTX 4070]	Nvidia	AD104	4,836,745	250,380	19.32	1 ^hrs 15 ^mins
10	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	4,234,258	239,749	17.66	1 ^hrs 22 ^mins
11	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	4,232,507	225,983	18.73	1 ^hrs 17 ^mins
12	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	3,896,432	233,235	16.71	1 ^hrs 26 ^mins
13	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	3,826,080	226,375	16.90	1 ^hrs 25 ^mins
14	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	3,519,304	226,470	15.54	1 ^hrs 33 ^mins
15	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	3,006,425	212,518	14.15	1 ^hrs 42 ^mins
16	GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti]	Nvidia	AD106	2,952,325	212,127	13.92	1 ^hrs 43 ^mins
17	GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti]	Nvidia	GA104	2,657,119	205,749	12.91	1 ^hrs 52 ^mins
18	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 Super]	Nvidia	TU104	2,582,262	129,125	20.00	1 ^hrs 12 ^mins
19	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	2,562,656	200,766	12.76	1 ^hrs 53 ^mins

20	GeForce RTX 4060 AD107 [GeForce RTX 4060]	Nvidia	AD107	2,551,457	203,832	12.52	1 ^hrs 55 ^mins
21	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	2,410,991	198,596	12.14	1 ^hrs 59 ^mins
22	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	2,402,535	198,860	12.08	1 ^hrs 59 ^mins
23	GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q]	Nvidia	GA104M	2,358,277	196,978	11.97	2 ^hrs 0 ^mins
24	GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]	Nvidia	GA104M	2,326,381	198,254	11.73	2 ^hrs 3 ^mins
25	GeForce RTX 2080 TU104 [GeForce RTX 2080]	Nvidia	TU104	2,188,816	192,573	11.37	2 ^hrs 7 ^mins
26	GeForce RTX 4060 Max-Q / Mobile AD107M [GeForce RTX 4060 Max-Q / Mobile]	Nvidia	AD107M	2,072,839	190,021	10.91	2 ^hrs 12 ^mins
27	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,072,576	134,217	15.44	1 ^hrs 33 ^mins
28	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A]	Nvidia	TU106	1,921,796	182,942	10.50	2 ^hrs 17 ^mins
29	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	1,835,821	158,154	11.61	2 ^hrs 4 ^mins
30	GeForce RTX 2070 TU106 [GeForce RTX 2070]	Nvidia	TU106	1,819,106	170,431	10.67	2 ^hrs 15 ^mins
31	GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q]	Nvidia	GA106M	1,719,004	139,764	12.30	1 ^hrs 57 ^mins
32	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	1,679,723	176,916	9.49	2 ^hrs 32 ^mins
33	TITAN V GV100 [TITAN V] M 12288	Nvidia	GV100	1,662,340	175,471	9.47	2 ^hrs 32 ^mins
34	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	1,627,592	162,463	10.02	2 ^hrs 24 ^mins
35	GeForce RTX 4050 Max-Q / Mobile AD107M [GeForce RTX 4050 Max-Q / Mobile]	Nvidia	AD107M	1,552,156	179,267	8.66	2 ^hrs 46 ^mins
36	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	1,519,089	171,193	8.87	2 ^hrs 42 ^mins
37	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,244,131	155,966	7.98	3 ^hrs 1 ^mins
38	RTX A2000 GA106 [RTX A2000]	Nvidia	GA106	1,196,431	157,825	7.58	3 ^hrs 10 ^mins
39	TITAN Xp GP102 [TITAN Xp] 12150	Nvidia	GP102	1,161,281	155,637	7.46	3 ^hrs 13 ^mins

40	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,117,847	153,985	7.26	3 ^hrs 18 ^mins
41	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	1,014,337	149,701	6.78	3 ^hrs 33 ^mins
42	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	879,306	141,582	6.21	3 ^hrs 52 ^mins
43	Quadro M6000 GM200GL [Quadro M6000]	Nvidia	GM200GL	801,777	141,681	5.66	4 ^hrs 14 ^mins
44	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	644,294	119,571	5.39	4 ^hrs 27 ^mins
45	GeForce GTX 1650 TU116 [GeForce GTX 1650] 3091	Nvidia	TU116	485,559	117,438	4.13	5 ^hrs 48 ^mins
46	GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q]	Nvidia	TU117M	391,340	108,877	3.59	6 ^hrs 41 ^mins

Research: PEPTIDE-CONFORMATION-MODELING Folding Project #12113

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 12113

GPU PPD Averages

Research: PEPTIDE-CONFORMATION-MODELING Folding Project #12113

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages