Folding project #16921, CANCER research

Research section Research projects and references

Project #16921 overview

Project Summary AI Beta

This project relates to studying how small protein structures fold. Scientists are looking at how chemical bonds and slight changes in the protein's code affect how it folds, hoping to design better proteins that can target and fight cancer.

Automated summary; simplified and may not be fully accurate.

Project team

Manager(s): Prof. Vincent Voelz
Institution: Temple University

Work unit

Atoms: 21,000
Core: OPENMM_22
Status: Public

Source material

Official Project Description

These simulations are designed to test our understanding the folding mechanism of alpha-helical hairpins.

We are trying to study how disulfide cross-linkers and sequence variants affect the folding thermodynamics and kinetics of these proteins, to learn how we might better use molecular simulation methods to design effective protein binder scaffolds, for use as "affibody" cancer therapeutics, for example.

Reading reference

Related Terms Glossary AI Beta

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

simulations

The process of creating computer models to mimic real-world phenomena.

Technical: Medicine, BiotechnologyBiotechnology / Protein Engineering

Simulations are used in biotechnology to study complex biological systems, such as protein folding, by creating virtual models that can be manipulated and observed. This allows researchers to explore how different factors, like chemical bonds and temperature, affect the behavior of proteins.

folding

The process by which a protein assumes its three-dimensional structure.

Scientific: Medicine, BiotechnologyBiotechnology / Protein Engineering

Folding is essential for proteins to function properly. Proteins are long chains of amino acids that must fold into specific shapes to perform their roles in the body. The shape of a protein determines its function, and misfolded proteins can lead to diseases.

alpha-helical hairpins

A type of protein structure consisting of two alpha-helices connected by a short loop.

Scientific: Medicine, BiotechnologyBiotechnology / Protein Structure

Alpha-helical hairpins are a common structural motif in proteins. They are characterized by two alpha-helices that are coiled into a hairpin shape. These structures are important for protein function and interactions.

disulfide cross-linkers

Covalent bonds between cysteine amino acids that stabilize protein structure.

Scientific: Medicine, BiotechnologyBiotechnology / Protein Structure

Disulfide cross-linkers are chemical bonds formed between sulfur atoms in cysteine amino acids. They play a crucial role in stabilizing the three-dimensional shape of proteins and can influence their function.

sequence variants

Changes in the DNA sequence that can alter protein structure and function.

Scientific: Medicine, BiotechnologyBiotechnology / Protein Engineering

Sequence variants are alterations in the genetic code that can lead to changes in protein sequences. These variations can affect protein folding, stability, and activity, potentially leading to different biological outcomes.

thermodynamics

The study of energy changes in chemical and physical processes.

Scientific: Medicine, BiotechnologyBiotechnology / Protein Folding

Thermodynamics explores how energy is transferred and transformed during biological processes. In protein folding, thermodynamics helps understand the factors influencing the stability and preferred conformation of proteins.

kinetics

The study of the rates and mechanisms of chemical reactions.

Scientific: Medicine, BiotechnologyBiotechnology / Protein Folding

Kinetics focuses on how fast chemical reactions occur and the steps involved. In protein folding, kinetics examines the time required for proteins to adopt their final structure and the influence of factors like temperature and concentration.

protein binder scaffolds

Structural frameworks designed to bind specifically to target proteins.

Technical: Medicine, BiotechnologyBiotechnology / Drug Discovery

Protein binder scaffolds are engineered structures that can selectively attach to specific proteins. These scaffolds serve as platforms for developing new drugs and therapies by targeting and modulating protein activity.

affibody

Affibody

Acronym: Medicine, BiotechnologyBiotechnology / Drug Delivery

An engineered protein domain that binds with high affinity and specificity to target molecules. Affibodys are often used in drug delivery systems due to their small size and ability to penetrate tissues.

cancer therapeutics

Drugs or treatments designed to fight cancer.

Technical: Medicine, BiotechnologyMedicine / Oncology

Cancer therapeutics encompass a wide range of medications and therapies aimed at treating various types of cancer. These treatments can target specific cancer cells, inhibit their growth, and reduce tumor size.

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	Tesla V100 SXM2 16GB GV100GL [Tesla V100 SXM2 16GB] M 14899	Nvidia	GV100GL	2,680,144	58,938	45.47	0 ^hrs 32 ^mins
2	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	2,658,252	59,117	44.97	0 ^hrs 32 ^mins
3	GeForce RTX 3080 10GB / 20GB GA102 [GeForce RTX 3080 10GB / 20GB]	Nvidia	GA102	2,526,143	57,823	43.69	0 ^hrs 33 ^mins
4	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	2,328,774	55,854	41.69	0 ^hrs 35 ^mins
5	TITAN RTX TU102 [TITAN RTX] 16310	Nvidia	TU102	2,268,878	56,055	40.48	0 ^hrs 36 ^mins
6	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	2,226,438	55,691	39.98	0 ^hrs 36 ^mins
7	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER]	Nvidia	TU104	1,859,840	52,213	35.62	0 ^hrs 40 ^mins
8	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER]	Nvidia	TU104	1,804,356	52,209	34.56	0 ^hrs 42 ^mins
9	GeForce RTX 2080 TU104 [GeForce RTX 2080]	Nvidia	TU104	1,747,593	50,790	34.41	0 ^hrs 42 ^mins
10	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	1,592,797	49,954	31.89	0 ^hrs 45 ^mins
11	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	1,544,871	48,876	31.61	0 ^hrs 46 ^mins
12	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465	Nvidia	TU106	1,539,124	49,559	31.06	0 ^hrs 46 ^mins
13	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	1,389,925	47,147	29.48	0 ^hrs 49 ^mins
14	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	1,327,821	46,549	28.53	0 ^hrs 50 ^mins
15	GeForce RTX 2080 SUPER Mobile / Max-Q TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q]	Nvidia	TU104M	1,318,967	46,479	28.38	0 ^hrs 51 ^mins
16	GeForce RTX 2080 SUPER Mobile / Max-Q TU104BM [GeForce RTX 2080 SUPER Mobile / Max-Q]	Nvidia	TU104BM	1,231,586	45,614	27.00	0 ^hrs 53 ^mins
17	GeForce GTX 1080 Mobile GP104M [GeForce GTX 1080 Mobile]	Nvidia	GP104M	1,124,771	44,262	25.41	0 ^hrs 57 ^mins
18	Tesla T4 TU104GL [Tesla T4] 8141	Nvidia	TU104GL	1,117,157	43,304	25.80	0 ^hrs 56 ^mins
19	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	1,114,223	43,863	25.40	0 ^hrs 57 ^mins

20	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,104,975	43,540	25.38	0 ^hrs 57 ^mins
21	GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497	Nvidia	TU106	1,100,991	43,293	25.43	0 ^hrs 57 ^mins
22	GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186	Nvidia	GP104	1,078,215	43,227	24.94	0 ^hrs 58 ^mins
23	GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti]	Nvidia	TU116	1,020,877	42,923	23.78	1 ^hrs 1 ^mins
24	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	1,020,439	42,347	24.10	0 ^hrs 60 ^mins
25	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	918,195	41,412	22.17	1 ^hrs 5 ^mins
26	GeForce GTX 1070 Mobile GP104M [GeForce GTX 1070 Mobile]	Nvidia	GP104M	901,484	41,201	21.88	1 ^hrs 6 ^mins
27	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	866,652	40,208	21.55	1 ^hrs 7 ^mins
28	GeForce GTX Titan X GM200 [GeForce GTX Titan X] 6144	Nvidia	GM200	836,968	40,291	20.77	1 ^hrs 9 ^mins
29	Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000]	Nvidia	TU102GL	823,247	39,494	20.84	1 ^hrs 9 ^mins
30	Radeon RX 5600/5600 XT - 5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT / 5700/5700 XT]	AMD	Navi 10	680,027	36,889	18.43	1 ^hrs 18 ^mins
31	GeForce GTX 760 GK104 [GeForce GTX 760] 2258	Nvidia	GK104	669,425	32,360	20.69	1 ^hrs 10 ^mins
32	GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935	Nvidia	GP106	653,942	37,040	17.66	1 ^hrs 22 ^mins
33	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	620,533	35,983	17.25	1 ^hrs 24 ^mins
34	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	601,933	34,126	17.64	1 ^hrs 22 ^mins
35	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	555,948	35,194	15.80	1 ^hrs 31 ^mins
36	Radeon VII Vega 20 [Radeon VII] 13,284	AMD	Vega 20	541,551	34,964	15.49	1 ^hrs 33 ^mins
37	GeForce GTX 1650 TU116 [GeForce GTX 1650] 2984	Nvidia	TU116	505,672	33,966	14.89	1 ^hrs 37 ^mins
38	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	501,459	34,106	14.70	1 ^hrs 38 ^mins
39	Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64]	AMD	Vega 10 XL/XT	482,091	33,057	14.58	1 ^hrs 39 ^mins

40	GeForce GTX 970 GM204 [GeForce GTX 970] 3494	Nvidia	GM204	472,335	33,188	14.23	1 ^hrs 41 ^mins
41	GeForce GTX 780 Ti GK110 [GeForce GTX 780 Ti] 5046	Nvidia	GK110	378,783	30,888	12.26	1 ^hrs 57 ^mins
42	Radeon RX 5500/5500M / Pro 5500M Navi 14 [Radeon RX 5500/5500M / Pro 5500M]	AMD	Navi 14	376,268	30,773	12.23	1 ^hrs 58 ^mins
43	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	320,057	29,155	10.98	2 ^hrs 11 ^mins
44	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	307,422	28,828	10.66	2 ^hrs 15 ^mins
45	Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590]	AMD	Ellesmere XT	296,198	28,258	10.48	2 ^hrs 17 ^mins
46	Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile]	Nvidia	TU117GLM	267,753	27,284	9.81	2 ^hrs 27 ^mins
47	P106-090 GP106 [P106-090]	Nvidia	GP106	264,828	27,313	9.70	2 ^hrs 29 ^mins
48	Radeon R9 Fury X Fiji XT [Radeon R9 Fury X]	AMD	Fiji XT	244,278	26,283	9.29	2 ^hrs 35 ^mins
49	Quadro M2200 GM206 [Quadro M2200]	Nvidia	GM206	229,899	26,074	8.82	2 ^hrs 43 ^mins
50	P104-100 GP104 [P104-100]	Nvidia	GP104	211,543	25,519	8.29	2 ^hrs 54 ^mins
51	P106-100 GP106 [P106-100]	Nvidia	GP106	179,573	24,118	7.45	3 ^hrs 13 ^mins
52	Radeon R9 200/300 Series Hawaii [Radeon R9 200/300 Series]	AMD	Hawaii	166,024	23,122	7.18	3 ^hrs 21 ^mins
53	GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634	Nvidia	GK104	161,570	22,236	7.27	3 ^hrs 18 ^mins
54	Radeon R9 200/300X Series Hawaii [Radeon R9 200/300X Series]	AMD	Hawaii	158,531	22,385	7.08	3 ^hrs 23 ^mins
55	GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389	Nvidia	GM107	134,124	21,960	6.11	3 ^hrs 56 ^mins
56	GeForce GTX 680 GK104 [GeForce GTX 680] 3250	Nvidia	GK104	104,199	20,078	5.19	4 ^hrs 37 ^mins
57	GeForce GT 1030 GP108 [GeForce GT 1030] 1127	Nvidia	GP108	103,466	20,065	5.16	4 ^hrs 39 ^mins
58	GeForce GTX 770 GK104 [GeForce GTX 770] 3213	Nvidia	GK104	100,044	19,935	5.02	4 ^hrs 47 ^mins
59	GeForce GTX 670MX GK106 [GeForce GTX 670MX]	Nvidia	GK106	90,459	17,927	5.05	4 ^hrs 45 ^mins

60	Radeon HD 7800 Pitcairn [Radeon HD 7800]	AMD	Pitcairn	89,498	19,141	4.68	5 ^hrs 8 ^mins
61	Ryzen 4900HS mobile Renoir [Ryzen 4900HS mobile]	AMD	Renoir	32,037	12,009	2.67	8 ^hrs 60 ^mins
62	Quadro K2000 GK107 [Quadro K2000]	Nvidia	GK107	27,581	13,030	2.12	11 ^hrs 20 ^mins
63	GeForce GTS 450 GF106 [GeForce GTS 450]	Nvidia	GF106	13,022	10,034	1.30	18 ^hrs 30 ^mins

Research: CANCER Folding Project #16921

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 16921

GPU PPD Averages

Research: CANCER Folding Project #16921

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages