PROJECT #18007 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: 90,996

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Friday, 23 July 2021 15:14:08

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 5,759,734 519,455 11.09 2 hrs 10 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,273,473 500,722 10.53 2 hrs 17 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,265,318 473,133 9.02 3 hrs 40 mins
4 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 3,741,482 452,950 8.26 3 hrs 54 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,589,175 445,787 8.05 3 hrs 59 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,353,640 434,707 7.71 3 hrs 7 mins
7 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,185,417 427,897 7.44 3 hrs 13 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,661,477 404,106 6.59 4 hrs 39 mins
9 RTX A4000
GA104GL [RTX A4000]
GA104GL 2,578,736 400,790 6.43 4 hrs 44 mins
10 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,423,184 391,542 6.19 4 hrs 53 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,404,944 390,728 6.16 4 hrs 54 mins
12 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,231,504 380,779 5.86 4 hrs 6 mins
13 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,203,714 379,387 5.81 4 hrs 8 mins
14 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,106,475 373,747 5.64 4 hrs 15 mins
15 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 2,073,980 372,183 5.57 4 hrs 18 mins
16 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,052,388 371,319 5.53 4 hrs 21 mins
17 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,039,913 370,046 5.51 4 hrs 21 mins
18 Radeon RX 6800/6800 XT / 6900 XT
Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]
AMD Navi 21 1,970,924 364,250 5.41 4 hrs 26 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,849,661 357,319 5.18 5 hrs 38 mins
20 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,839,401 357,925 5.14 5 hrs 40 mins
21 Radeon VII
Vega 20 [Radeon VII] 13,284
AMD Vega 20 1,589,701 340,869 4.66 5 hrs 9 mins
22 Radeon RX 6700/6700 XT / 6800M
Navi 22 [Radeon RX 6700/6700 XT / 6800M]
AMD Navi 22 1,582,265 333,826 4.74 5 hrs 4 mins
23 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,364,516 322,433 4.23 6 hrs 40 mins
24 Radeon RX 5600 OEM/5600 XT/5700/5700 XT
Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]
AMD Navi 10 1,306,344 318,103 4.11 6 hrs 51 mins
25 Quadro P5000
GP104GL [Quadro P5000]
Nvidia GP104GL 1,034,821 274,276 3.77 6 hrs 22 mins
26 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,001,311 290,714 3.44 7 hrs 58 mins
27 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 924,433 280,509 3.30 7 hrs 17 mins
28 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 880,892 263,414 3.34 7 hrs 11 mins
29 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 869,847 278,616 3.12 8 hrs 41 mins
30 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 620,802 248,681 2.50 10 hrs 37 mins
31 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 588,067 244,611 2.40 10 hrs 59 mins
32 Radeon R9 Fury X
Fiji XT [Radeon R9 Fury X]
AMD Fiji XT 549,352 242,860 2.26 11 hrs 37 mins
33 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 535,213 191,219 2.80 9 hrs 34 mins
34 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 523,714 234,998 2.23 11 hrs 46 mins
35 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 520,308 235,062 2.21 11 hrs 51 mins
36 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 446,095 223,489 2.00 12 hrs 1 mins
37 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 441,153 219,861 2.01 12 hrs 58 mins
38 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 360,464 208,308 1.73 14 hrs 52 mins
39 P106-100
GP106 [P106-100]
Nvidia GP106 354,172 206,447 1.72 14 hrs 59 mins
40 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 308,597 197,097 1.57 15 hrs 20 mins
41 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 238,378 181,322 1.31 18 hrs 15 mins
42 Radeon RX Vega gfx902
raven [Radeon RX Vega gfx902]
AMD raven 196,802 129,151 1.52 16 hrs 45 mins
43 Radeon RX Vega M XL
[Radeon RX Vega M XL]
AMD Vega 137,084 129,151 1.06 23 hrs 37 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 23 July 2021 15:14:08

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