Folding project #16774, CANCER research

Research section Research projects and references

Project #16774 overview

Project Summary AI Beta

KRAS is a gene that causes cancer by making cells grow too fast. It's hard to block KRAS with drugs because its shape and how it works make this difficult. The project looks at how KRAS interacts with other proteins, hoping to find new ways to control it using 'molecular glues'. These glues could help degrade KRAS or change how it works, leading to better cancer treatments.

Automated summary; simplified and may not be fully accurate.

Project team

Manager(s): Prof. Xuhui Huang
Institution: University of Wisconsin-Madison

Work unit

Atoms: 134,555
Core: 0x27
Status: Public

Source material

Official Project Description

KRAS is one of the most frequently mutated oncogenes in human cancers, driving uncontrolled cell growth through persistent activation of the MAPK and PI3K signaling pathways.

Despite decades of effort, KRAS has long been considered “undruggable” due to its smooth surface and high affinity for GTP/GDP, which make traditional small-molecule inhibition extremely difficult.

The concept of molecular glues offers a transformative strategy by promoting or stabilizing interactions between KRAS and specific E3 ligases or regulatory partners, leading to selective degradation or allosteric modulation of KRAS.

These projects aim to discover the PPI between VHL and wild type and the G12 mutants.

Further, the novel PPI can aid the discovery of the novel molecular glue compunds that target KRAS.

Reading reference

Related Terms Glossary AI Beta

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

KRAS

Kirsten rat sarcoma viral oncogene homolog

Technical: BiotechnologyOncology / Cancer Research

KRAS is a gene that can become mutated and cause cancer. These mutations lead to uncontrolled cell growth. KRAS has been difficult to target with drugs because of its shape and how it binds to other molecules. A new strategy called 'molecular glues' aims to interact with KRAS and promote its degradation, potentially offering a new way to treat cancers driven by KRAS mutations.

oncogenes

Genes that have the potential to cause cancer when mutated.

Technical: BiotechnologyOncology / Cancer Genetics

Oncogenes are genes that can become activated and contribute to the development of cancer. When these genes are mutated or overexpressed, they can promote uncontrolled cell growth and division, leading to tumor formation.

MAPK

Mitogen-activated protein kinase

Technical: BiotechnologyOncology / Signal Transduction

The MAPK pathway is a crucial signaling cascade involved in cell growth, proliferation, and differentiation. Mutations or dysregulation of this pathway can contribute to cancer development.

PI3K

Phosphoinositide 3-kinase

Technical: BiotechnologyOncology / Signal Transduction

The PI3K pathway is another important signaling pathway involved in cell growth, survival, and metabolism. It plays a role in cancer development through various mechanisms.

E3 ligases

Enzymes that facilitate the ubiquitination of target proteins, marking them for degradation.

Technical: BiotechnologyOncology / Protein Degradation

E3 ligases are enzymes that play a crucial role in protein degradation by attaching ubiquitin tags to target proteins. This tagging process marks the proteins for destruction by cellular machinery.

molecular glues

A novel class of therapeutic agents that promote interactions between proteins.

Technical: BiotechnologyOncology / Drug Discovery

Molecular glues are a new type of drug that works by bringing together specific proteins. This can lead to the activation or degradation of target proteins, offering a potential treatment for diseases like cancer.

VHL

Von Hippel-Lindau tumor suppressor gene

Technical: BiotechnologyOncology / Tumor Suppressor Genes

VHL is a gene that normally acts as a tumor suppressor, helping to regulate cell growth and prevent cancer. Mutations in VHL can lead to the development of various tumors.

PPI

Protein-protein interaction

Technical: BiotechnologyOncology / Protein-Protein Interactions

PPI refers to the interactions between different proteins. These interactions are essential for many cellular processes, including signaling pathways and gene regulation.

compunds

Chemicals with a defined structure and properties.

Technical: BiotechnologyOncology / Drug Discovery

Compounds are chemical substances with a specific molecular structure. In the context of drug discovery, compounds are often screened for their ability to interact with specific targets, such as proteins involved in cancer development.

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	23,343,774	253,998	91.91	0 ^hrs 16 ^mins
2	GeForce RTX 5070 Ti GB203 [GeForce RTX 5070 Ti]	Nvidia	GB203	20,900,405	53,000	394.35	0 ^hrs 4 ^mins
3	GeForce RTX 4080 AD103 [GeForce RTX 4080]	Nvidia	AD103	17,808,245	210,500	84.60	0 ^hrs 17 ^mins
4	GeForce RTX 4080 SUPER AD103 [GeForce RTX 4080 SUPER]	Nvidia	AD103	17,625,432	453,422	38.87	0 ^hrs 37 ^mins
5	GeForce RTX 4070 Ti SUPER AD103 [GeForce RTX 4070 Ti SUPER]	Nvidia	AD103	14,107,067	53,000	266.17	0 ^hrs 5 ^mins
6	GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti]	Nvidia	AD104	13,352,516	184,531	72.36	0 ^hrs 20 ^mins
7	GeForce RTX 4070 SUPER AD104 [GeForce RTX 4070 SUPER]	Nvidia	AD104	11,923,787	134,888	88.40	0 ^hrs 16 ^mins
8	GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti]	Nvidia	GA102	10,044,663	53,000	189.52	0 ^hrs 8 ^mins
9	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	9,852,538	231,234	42.61	0 ^hrs 34 ^mins
10	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	9,535,383	236,714	40.28	0 ^hrs 36 ^mins
11	GeForce RTX 5070 GB205 [GeForce RTX 5070]	Nvidia	GB205	8,901,347	53,000	167.95	0 ^hrs 9 ^mins
12	GeForce RTX 4070 AD104 [GeForce RTX 4070]	Nvidia	AD104	7,829,713	277,902	28.17	0 ^hrs 51 ^mins
13	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	7,559,372	183,350	41.23	0 ^hrs 35 ^mins
14	RTX 4000 Ada Generation AD104GL [RTX 4000 Ada Generation]	Nvidia	AD104GL	7,461,761	53,000	140.79	0 ^hrs 10 ^mins
15	Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE]	AMD	Navi 31	7,330,768	53,000	138.32	0 ^hrs 10 ^mins
16	Instinct MI300X Aqua Vanjaram [Instinct MI300X]	AMD	Aqua Vanjaram	7,203,774	53,000	135.92	0 ^hrs 11 ^mins
17	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	7,011,817	87,972	79.71	0 ^hrs 18 ^mins
18	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	6,221,618	222,717	27.94	0 ^hrs 52 ^mins
19	GeForce RTX 5060 GB206 [GeForce RTX 5060]	Nvidia	GB206	6,074,385	53,000	114.61	0 ^hrs 13 ^mins

20	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	5,900,503	53,000	111.33	0 ^hrs 13 ^mins
21	GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate]	Nvidia	GA104	5,881,110	60,307	97.52	0 ^hrs 15 ^mins
22	TITAN V GV100 [TITAN V] M 12288	Nvidia	GV100	5,426,137	53,000	102.38	0 ^hrs 14 ^mins
23	GeForce RTX 5070 Ti Mobile GB205M [GeForce RTX 5070 Ti Mobile]	Nvidia	GB205M	5,416,409	53,000	102.20	0 ^hrs 14 ^mins
24	Radeon RX 9070(XT) Navi 48 [Radeon RX 9070(XT)]	AMD	Navi 48	5,375,840	168,972	31.81	0 ^hrs 45 ^mins
25	GeForce RTX 4070 Max-Q / Mobile AD106M [GeForce RTX 4070 Max-Q / Mobile]	Nvidia	AD106M	5,153,810	53,000	97.24	0 ^hrs 15 ^mins
26	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 Super]	Nvidia	TU104	4,950,777	53,000	93.41	0 ^hrs 15 ^mins
27	Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT]	AMD	Navi 21	4,941,445	53,000	93.23	0 ^hrs 15 ^mins
28	RTX 4000 SFF Ada Generation AD104GL [RTX 4000 SFF Ada Generation]	Nvidia	AD104GL	4,261,472	53,000	80.41	0 ^hrs 18 ^mins
29	Radeon RX 6800(XT)/6900XT Navi 21 [Radeon RX 6800(XT)/6900XT]	AMD	Navi 21	4,128,869	309,530	13.34	1 ^hrs 48 ^mins
30	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	4,098,164	241,126	17.00	1 ^hrs 25 ^mins
31	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	3,709,412	53,000	69.99	0 ^hrs 21 ^mins
32	GeForce RTX 4060 AD107 [GeForce RTX 4060]	Nvidia	AD107	3,681,986	53,000	69.47	0 ^hrs 21 ^mins
33	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	3,618,722	74,774	48.40	0 ^hrs 30 ^mins
34	Intel Arc B580 Graphics Battlemage G21 [Intel Arc B580 Graphics]	Intel	Battlemage G21	3,501,627	53,000	66.07	0 ^hrs 22 ^mins
35	Radeon RX 7700XT/7800XT Navi 32 [Radeon RX 7700XT/7800XT]	AMD	Navi 32	3,361,557	53,000	63.43	0 ^hrs 23 ^mins
36	GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti]	Nvidia	GA104	3,357,395	237,151	14.16	1 ^hrs 42 ^mins
37	GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti]	Nvidia	AD106	3,058,826	307,474	9.95	2 ^hrs 25 ^mins
38	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,679,438	53,000	50.56	0 ^hrs 28 ^mins
39	Radeon RX 6700(XT)/6800M Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]	AMD	Navi 22 XT-XL	2,587,709	53,000	48.82	0 ^hrs 29 ^mins

40	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	2,567,087	264,123	9.72	2 ^hrs 28 ^mins
41	GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q]	Nvidia	GA106M	2,537,729	71,906	35.29	0 ^hrs 41 ^mins
42	Radeon RX 9060(XT) Navi 44 [Radeon RX 9060(XT)]	AMD	Navi 44	2,434,060	53,000	45.93	0 ^hrs 31 ^mins
43	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	2,339,884	53,000	44.15	0 ^hrs 33 ^mins
44	GeForce RTX 3060 GA104 [GeForce RTX 3060]	Nvidia	GA104	2,295,360	53,000	43.31	0 ^hrs 33 ^mins
45	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	2,157,463	282,586	7.63	3 ^hrs 9 ^mins
46	Radeon RX 6650 XT Navi 23 [Radeon RX 6650 XT]	AMD	Navi 23	1,865,246	53,000	35.19	0 ^hrs 41 ^mins
47	GeForce RTX 4050 Max-Q / Mobile AD107M [GeForce RTX 4050 Max-Q / Mobile]	Nvidia	AD107M	1,693,317	53,000	31.95	0 ^hrs 45 ^mins
48	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	1,425,787	247,645	5.76	4 ^hrs 10 ^mins
49	GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile]	Nvidia	TU106M	1,425,632	53,000	26.90	0 ^hrs 54 ^mins
50	Radeon VII Vega 20 [Radeon VII]	AMD	Vega 20	1,380,389	53,000	26.05	0 ^hrs 55 ^mins
51	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	1,357,465	189,056	7.18	3 ^hrs 21 ^mins
52	GeForce RTX 5080 Max-Q / Mobile GB203M / GN22-X9 [GeForce RTX 5080 Max-Q / Mobile]	Nvidia	GB203M / GN22-X9	1,321,432	53,000	24.93	0 ^hrs 58 ^mins
53	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,257,776	63,147	19.92	1 ^hrs 12 ^mins
54	CMP 30HX TU116 [CMP 30HX]	Nvidia	TU116	1,174,404	53,000	22.16	1 ^hrs 5 ^mins
55	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	1,039,109	100,471	10.34	2 ^hrs 19 ^mins
56	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	929,885	53,000	17.55	1 ^hrs 22 ^mins
57	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	887,227	157,872	5.62	4 ^hrs 16 ^mins
58	Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64]	AMD	Vega 10 XL/XT	878,374	53,000	16.57	1 ^hrs 27 ^mins
59	RTX A2000 GA106 [RTX A2000]	Nvidia	GA106	638,003	53,000	12.04	1 ^hrs 60 ^mins

60	R9 Fury X/NANO Fiji XT [R9 Fury X/NANO]	AMD	Fiji XT	620,469	53,000	11.71	2 ^hrs 3 ^mins
61	Tesla P4 GP104GL [Tesla P4] 5704	Nvidia	GP104GL	608,897	183,976	3.31	7 ^hrs 15 ^mins
62	GeForce GTX 1650 TU117 [GeForce GTX 1650]	Nvidia	TU117	510,678	53,000	9.64	2 ^hrs 29 ^mins
63	RX 5500(M)/Pro 5500M Navi 14 [RX 5500(M)/Pro 5500M]	AMD	Navi 14	494,024	53,000	9.32	2 ^hrs 34 ^mins
64	GeForce RTX 3050 6GB GA107 [GeForce RTX 3050 6GB]	Nvidia	GA107	491,177	53,000	9.27	2 ^hrs 35 ^mins
65	GeForce GTX 1650 TU116 [GeForce GTX 1650] 3091	Nvidia	TU116	442,276	166,940	2.65	9 ^hrs 4 ^mins
66	Radeon RX 580 2048SP Polaris 20 XL [Radeon RX 580 2048SP]	AMD	Polaris 20 XL	427,232	53,000	8.06	2 ^hrs 59 ^mins
67	Radeon PRO W6400 Navi 24 [Radeon PRO W6400]	AMD	Navi 24	382,753	53,000	7.22	3 ^hrs 19 ^mins
68	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	340,369	107,054	3.18	7 ^hrs 33 ^mins
69	Quadro M5000 GM204GL [Quadro M5000]	Nvidia	GM204GL	333,094	53,000	6.28	3 ^hrs 49 ^mins
70	GeForce GTX 1650 TU106 [GeForce GTX 1650]	Nvidia	TU106	320,002	53,000	6.04	3 ^hrs 58 ^mins
71	Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile]	Nvidia	TU117GLM	319,744	147,362	2.17	11 ^hrs 4 ^mins
72	GeForce GTX 980M GM204 [GeForce GTX 980M] 3189	Nvidia	GM204	318,431	53,000	6.01	3 ^hrs 60 ^mins
73	Quadro K5200 GK110 [Quadro K5200]	Nvidia	GK110	294,443	53,000	5.56	4 ^hrs 19 ^mins
74	Quadro P1000 GP107GL [Quadro P1000]	Nvidia	GP107GL	265,044	140,456	1.89	12 ^hrs 43 ^mins
75	GeForce GTX 1070 Mobile GP104BM [GeForce GTX 1070 Mobile] 6463	Nvidia	GP104BM	194,881	53,000	3.68	6 ^hrs 32 ^mins
76	Quadro T400 Mobile TU117GLM [Quadro T400 Mobile]	Nvidia	TU117GLM	162,292	53,000	3.06	7 ^hrs 50 ^mins
77	GeForce GT 1030 GP108 [GeForce GT 1030]	Nvidia	GP108	67,714	73,961	0.92	26 ^hrs 13 ^mins

CPU PPD Averages Beta

Rank Project	CPU Model	Logical Processors (LP)	PPD-PLP AVG PPD per 1 LP	ALL LP-PPD (Estimated)	Make
1	A10-7850K RADEON R7, 12 COMPUTE CORES 4C 8G	4	154,703	618,812	AMD

Research: CANCER Folding Project #16774

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 16774

GPU PPD Averages

CPU PPD Averages Beta

Research: CANCER Folding Project #16774

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages

CPU PPD Averages Beta