PROJECT #18008 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

This project investigates anti-cancer drugs that might overcome drug resistance. The targets considered are major oncogenes like SMARCA2, BRD4, Bcl and BTK. Drug-resistance is a major and unavoidable problem and presently only 20–25NULLof all protein targets are studied. Moreover, the focus of current explorations of targets are their enzymatic functions, while ignoring the functions from their scaffold moiety. Roivant's drug discovery choose to focus on a promising new technology, PROteolysis TArgeting Chimeras (PROTACs) which regulates protein function by degrading target proteins instead of inhibiting them. This method provided more sensitivity to drug-resistant targets, better selectivity, and a greater chance to affect the nonenzymatic functions of targeted proteins. Roivant is leading in the general paradigm shift that looks at the kinetics of reactions instead of binding thermodynamics for its PROTACs drug discovery. Specifically, by understanding the balance between changes of entropy and enthalpy and the competition between a ligand and water molecules in molecular binding, which is known to be crucial for smart drug discovery. Experiments provide measurements, however, computational methods provide information about binding/unbinding processes that allows for a complete picture of molecular recognition not directly available from experiments. All the computed values of kon, koff, ΔH, ΔS, and ΔG use AMBER force fields for Protein-Protein and Protein-Ligand's interactions. The experimental data is used to guide and improve the predictive, modeling tools for PROTAC drug discovery in iterative manner. Roivant is using published PROTAC-bound ternary complexes, plus some data generated internally for the F@h projects, and all simulation data is being made publicly available.

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/

PROJECT INFO

Manager(s): Rafal Wiewiora

Institution: Roivant Sciences (Silicon Therapeutics)

Project URL: roivant.com

PROJECT WORK UNIT SUMMARY

Atoms: 84,624

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Tuesday, 26 October 2021 06:56:06

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 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 5,705,962 489,007 11.67 2 hrs 3 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,917,874 442,126 11.12 2 hrs 9 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,357,059 448,052 9.72 2 hrs 28 mins
4 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 3,474,597 415,760 8.36 3 hrs 52 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,443,679 412,190 8.35 3 hrs 52 mins
6 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,354,752 410,119 8.18 3 hrs 56 mins
7 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,112,452 399,950 7.78 3 hrs 5 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,617,305 378,521 6.91 3 hrs 28 mins
9 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,511,236 373,472 6.72 4 hrs 34 mins
10 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,459,487 370,219 6.64 4 hrs 37 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,320,525 363,484 6.38 4 hrs 46 mins
12 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,302,713 363,143 6.34 4 hrs 47 mins
13 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,057,998 349,689 5.89 4 hrs 5 mins
14 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,054,216 348,710 5.89 4 hrs 4 mins
15 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,039,622 349,098 5.84 4 hrs 6 mins
16 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,019,471 347,480 5.81 4 hrs 8 mins
17 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,995,676 346,439 5.76 4 hrs 10 mins
18 Radeon RX 6800/6800 XT / 6900 XT
Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]
AMD Navi 21 1,930,337 341,807 5.65 4 hrs 15 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,817,795 333,580 5.45 4 hrs 24 mins
20 Tesla P40
GP102GL [Tesla P40] 11760
Nvidia GP102GL 1,686,804 326,562 5.17 5 hrs 39 mins
21 Radeon RX 6700/6700 XT / 6800M
Navi 22 [Radeon RX 6700/6700 XT / 6800M]
AMD Navi 22 1,555,796 310,510 5.01 5 hrs 47 mins
22 Radeon VII
Vega 20 [Radeon VII] 13,284
AMD Vega 20 1,494,380 314,182 4.76 5 hrs 3 mins
23 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,480,150 309,695 4.78 5 hrs 1 mins
24 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,430,320 307,078 4.66 5 hrs 9 mins
25 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,397,629 304,830 4.58 5 hrs 14 mins
26 Quadro P5000
GP104GL [Quadro P5000]
Nvidia GP104GL 1,365,853 305,104 4.48 5 hrs 22 mins
27 Radeon RX 5600 OEM/5600 XT/5700/5700 XT
Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]
AMD Navi 10 1,222,586 293,043 4.17 6 hrs 45 mins
28 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,196,198 291,930 4.10 6 hrs 51 mins
29 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 994,767 264,279 3.76 6 hrs 23 mins
30 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 985,651 236,762 4.16 6 hrs 46 mins
31 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 917,379 259,815 3.53 7 hrs 48 mins
32 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 814,017 230,280 3.53 7 hrs 47 mins
33 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 708,364 244,820 2.89 8 hrs 18 mins
34 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 611,640 233,612 2.62 9 hrs 10 mins
35 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 574,543 225,384 2.55 9 hrs 25 mins
36 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 510,939 219,679 2.33 10 hrs 19 mins
37 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 464,999 212,901 2.18 11 hrs 59 mins
38 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 444,250 199,060 2.23 11 hrs 45 mins
39 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 423,629 200,354 2.11 11 hrs 21 mins
40 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 332,315 190,544 1.74 14 hrs 46 mins
41 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 305,971 185,406 1.65 15 hrs 33 mins
42 GeForce GTX 1050 Mobile
GP107M [GeForce GTX 1050 Mobile]
Nvidia GP107M 246,194 162,301 1.52 16 hrs 49 mins
43 Radeon RX Vega M XL
[Radeon RX Vega M XL]
AMD Vega 179,590 149,079 1.20 20 hrs 55 mins
44 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 104,590 119,958 0.87 28 hrs 32 mins
45 Radeon R7 250/HD 7700
R575A [Radeon R7 250/HD 7700]
AMD R575A 52,949 118,154 0.45 54 hrs 33 mins
46 Radeon RX Vega gfx902
raven [Radeon RX Vega gfx902]
AMD raven 32,502 118,154 0.28 87 hrs 15 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Tuesday, 26 October 2021 06:56:06

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make