Folding project #12601, ALCHEMICAL-BINDING-ENERGY research

Research section Research projects and references

Project #12601 overview

Project Summary AI Beta

Alchemiscale lets users design experiments to study how molecules bind together. These experiments are then run by volunteers' computers through Folding@Home, a project that uses computing power for scientific research.

Automated summary; simplified and may not be fully accurate.

Project team

Manager(s): David L. Dotson
Institution: Chodera Lab

Work unit

Atoms: 50,000
Core: 0x26
Status: Public

Source material

Official Project Description

Relative binding free energy calculations orchestrated via alchemiscale.org.

Networks of alchemical transformations are submitted by alchemiscale users, and transformations that can be performed by Folding@Home are executed via these PROJECTs.

Reading reference

Related Terms Glossary AI Beta

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

Relative binding free energy

The difference in free energy between a ligand bound to a receptor and the unbound state.

Scientific: BiotechnologyBiochemistry / Molecular modeling

Relative binding free energy calculations help scientists understand how strongly a molecule (ligand) binds to another molecule (receptor). This information is crucial for drug development as it allows researchers to identify molecules that effectively bind to specific targets in the body.

alchemiscale.org

A platform for collaborative drug discovery using alchemical transformations.

Platform: BiotechnologyComputational Chemistry / Drug discovery

Alchemiscale.org is a web-based platform that facilitates the development of new drugs by enabling researchers to share and execute computational experiments involving molecular simulations.

Networks

Interconnected structures of nodes and edges.

Technical: BiotechnologyComputer Science / Graph Theory

In the context of alchemiscale.org, networks represent connections between different computational tasks or molecules involved in drug discovery.

PROJECTs

Project for the execution of alchemical transformations.

Acronym: BiotechnologyComputational Chemistry / Drug discovery

PROJECTs are computational tasks submitted to the Folding@Home platform via alchemiscale.org. These projects involve simulating molecular interactions and contribute to the discovery of new drugs.

Folding@Home

A distributed computing platform for scientific research.

Platform: BiotechnologyBioinformatics / Distributed computing

Folding@Home is a network of volunteer computers that work together to perform complex simulations. In the context of alchemiscale.org, Folding@Home is used to execute computational projects related to drug discovery.

alchemical transformations

Changes in the structure of molecules that are simulated computationally.

Scientific: BiotechnologyBiochemistry / Molecular modeling

Alchemical transformations involve simulating modifications to molecular structures. This allows researchers to explore how changes in a molecule's properties affect its interactions with other molecules, which is crucial for drug design.

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 4080 SUPER AD103 [GeForce RTX 4080 SUPER]	Nvidia	AD103	34,338,552	46,725	734.91	0 ^hrs 2 ^mins
2	GeForce RTX 4080 AD103 [GeForce RTX 4080]	Nvidia	AD103	32,170,099	46,725	688.50	0 ^hrs 2 ^mins
3	GeForce RTX 5090 GB202 [GeForce RTX 5090]	Nvidia	GB202	24,947,081	46,725	533.91	0 ^hrs 3 ^mins
4	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	17,134,634	315,007	54.39	0 ^hrs 26 ^mins
5	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	15,128,943	307,828	49.15	0 ^hrs 29 ^mins
6	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	11,474,178	192,511	59.60	0 ^hrs 24 ^mins
7	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	10,009,505	316,178	31.66	0 ^hrs 45 ^mins
8	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	9,893,902	222,555	44.46	0 ^hrs 32 ^mins
9	GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate]	Nvidia	GA104	8,046,668	145,903	55.15	0 ^hrs 26 ^mins
10	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	7,991,027	46,725	171.02	0 ^hrs 8 ^mins
11	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A]	Nvidia	TU106	7,113,376	46,725	152.24	0 ^hrs 9 ^mins
12	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	6,461,547	46,725	138.29	0 ^hrs 10 ^mins
13	GeForce RTX 2070 TU106 [GeForce RTX 2070]	Nvidia	TU106	6,431,394	271,169	23.72	1 ^hrs 1 ^mins
14	TITAN V GV100 [TITAN V] M 12288	Nvidia	GV100	6,173,690	46,725	132.13	0 ^hrs 11 ^mins
15	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	5,416,197	256,908	21.08	1 ^hrs 8 ^mins
16	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	5,395,437	66,345	81.32	0 ^hrs 18 ^mins
17	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	5,104,148	240,817	21.20	1 ^hrs 8 ^mins
18	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	4,586,732	167,738	27.34	0 ^hrs 53 ^mins
19	GeForce RTX 4060 AD107 [GeForce RTX 4060]	Nvidia	AD107	3,946,695	46,725	84.47	0 ^hrs 17 ^mins

20	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	3,875,795	118,853	32.61	0 ^hrs 44 ^mins
21	GeForce RTX 3060 GA104 [GeForce RTX 3060]	Nvidia	GA104	3,855,395	46,725	82.51	0 ^hrs 17 ^mins
22	GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q]	Nvidia	GA106M	3,693,588	226,904	16.28	1 ^hrs 28 ^mins
23	GeForce RTX 2060 TU106 [Geforce RTX 2060]	Nvidia	TU106	3,665,648	195,316	18.77	1 ^hrs 17 ^mins
24	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	3,398,952	220,595	15.41	1 ^hrs 33 ^mins
25	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 Super]	Nvidia	TU106	2,870,967	46,725	61.44	0 ^hrs 23 ^mins
26	Quadro RTX 4000 TU104GL [Quadro RTX 4000]	Nvidia	TU104GL	2,861,215	46,725	61.24	0 ^hrs 24 ^mins
27	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	2,806,804	207,256	13.54	1 ^hrs 46 ^mins
28	RTX A2000 GA106 [RTX A2000]	Nvidia	GA106	2,751,634	46,725	58.89	0 ^hrs 24 ^mins
29	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	2,743,636	46,725	58.72	0 ^hrs 25 ^mins
30	RTX A1000 GA107GL [RTX A1000]	Nvidia	GA107GL	2,721,071	46,725	58.24	0 ^hrs 25 ^mins
31	GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti]	Nvidia	TU116	2,639,890	46,725	56.50	0 ^hrs 25 ^mins
32	RTX A2000 12GB GA106 [RTX A2000 12GB]	Nvidia	GA106	2,235,250	46,725	47.84	0 ^hrs 30 ^mins
33	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	2,220,653	46,725	47.53	0 ^hrs 30 ^mins
34	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	2,059,269	46,725	44.07	0 ^hrs 33 ^mins
35	GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile]	Nvidia	TU116M	1,633,113	172,334	9.48	2 ^hrs 32 ^mins
36	Tesla P4 GP104GL [Tesla P4] 5704	Nvidia	GP104GL	1,584,482	170,264	9.31	2 ^hrs 35 ^mins
37	GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER]	Nvidia	TU116	1,532,268	168,406	9.10	2 ^hrs 38 ^mins
38	GeForce GTX 1070 Mobile GP104BM [GeForce GTX 1070 Mobile] 6463	Nvidia	GP104BM	1,178,105	46,725	25.21	0 ^hrs 57 ^mins
39	RX 470/480/570/580/590 Ellesmere XT [RX 470/480/570/580/590]	AMD	Ellesmere XT	821,178	137,451	5.97	4 ^hrs 1 ^mins

40	GeForce GTX 1650 TU117 [GeForce GTX 1650]	Nvidia	TU117	808,375	100,987	8.00	2 ^hrs 60 ^mins
41	GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862	Nvidia	GP107	807,230	46,725	17.28	1 ^hrs 23 ^mins
42	GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti]	Nvidia	AD106	614,191	27,851	22.05	1 ^hrs 5 ^mins
43	Quadro P1000 GP107GL [Quadro P1000]	Nvidia	GP107GL	524,437	118,333	4.43	5 ^hrs 25 ^mins
44	Radeon R9 285/380 Tonga PRO [Radeon R9 285/380]	AMD	Tonga PRO	457,686	114,591	3.99	6 ^hrs 1 ^mins
45	RX Vega M GL Polaris 22 XL [RX Vega M GL]	AMD	Polaris 22 XL	324,176	46,725	6.94	3 ^hrs 28 ^mins
46	Quadro K1200 GM107GL [Quadro K1200]	Nvidia	GM107GL	242,793	46,725	5.20	4 ^hrs 37 ^mins
47	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	229,145	46,725	4.90	4 ^hrs 54 ^mins
48	Ryzen 7000 Series iGPU Raphael [Ryzen 7000 Series iGPU]	AMD	Raphael	74,962	62,420	1.20	19 ^hrs 59 ^mins
49	FirePro W2100 Oland GL [FirePro W2100]	AMD	Oland GL	24,614	46,725	0.53	45 ^hrs 34 ^mins

Research: ALCHEMICAL-BINDING-ENERGY Folding Project #12601

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 12601

GPU PPD Averages

Research: ALCHEMICAL-BINDING-ENERGY Folding Project #12601

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages