PROJECT #18025 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/

All data is being made publicly available in real time at https://console.cloud.google.com/storage/browser/stxfah-bucket

PROJECT INFO

Manager(s): Rafal Wiewiora

Institution: Roivant Sciences (Silicon Therapeutics)

Project URL: roivant.com

PROJECT WORK UNIT SUMMARY

Atoms: 234,724

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Monday, 27 September 2021 17:59:03

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 7,555,460 429,723 17.58 1 hrs 22 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 7,123,493 418,041 17.04 1 hrs 25 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,492,127 410,470 15.82 2 hrs 31 mins
4 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 6,163,065 403,762 15.26 2 hrs 34 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,862,475 373,292 13.03 2 hrs 51 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,600,143 365,836 12.57 2 hrs 55 mins
7 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,364,604 358,855 12.16 2 hrs 58 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,633,825 337,887 10.75 2 hrs 14 mins
9 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 3,406,246 545,952 6.24 4 hrs 51 mins
10 Radeon RX 6900 XT
Navi 21 [Radeon RX 6900 XT]
AMD Navi 21 3,251,512 325,868 9.98 2 hrs 24 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 3,107,055 322,036 9.65 2 hrs 29 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,782,187 310,716 8.95 3 hrs 41 mins
13 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,571,027 301,854 8.52 3 hrs 49 mins
14 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,535,809 300,429 8.44 3 hrs 51 mins
15 TITAN X
GP102 [TITAN X] 6144
Nvidia GP102 2,274,736 289,134 7.87 3 hrs 3 mins
16 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,212,163 285,317 7.75 3 hrs 6 mins
17 Tesla P40
GP102GL [Tesla P40] 11760
Nvidia GP102GL 1,887,947 271,316 6.96 3 hrs 27 mins
18 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,871,175 271,646 6.89 3 hrs 29 mins
19 Radeon RX 5600 OEM/5600 XT/5700/5700 XT
Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]
AMD Navi 10 1,630,563 259,018 6.30 4 hrs 49 mins
20 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,583,850 243,251 6.51 4 hrs 41 mins
21 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,483,858 251,119 5.91 4 hrs 4 mins
22 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,427,636 248,209 5.75 4 hrs 10 mins
23 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 1,403,653 244,989 5.73 4 hrs 11 mins
24 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,386,146 240,992 5.75 4 hrs 10 mins
25 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,276,356 236,533 5.40 4 hrs 27 mins
26 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,269,360 238,229 5.33 5 hrs 30 mins
27 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,237,414 237,131 5.22 5 hrs 36 mins
28 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 969,943 218,277 4.44 5 hrs 24 mins
29 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 768,307 201,557 3.81 6 hrs 18 mins
30 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 632,396 188,959 3.35 7 hrs 10 mins
31 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 625,224 193,935 3.22 7 hrs 27 mins
32 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 549,619 180,732 3.04 8 hrs 54 mins
33 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 509,126 176,669 2.88 8 hrs 20 mins
34 GeForce GTX 1050 Ti Mobile
GP107M [GeForce GTX 1050 Ti Mobile]
Nvidia GP107M 292,330 136,498 2.14 11 hrs 12 mins
35 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 134,594 89,070 1.51 16 hrs 53 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Monday, 27 September 2021 17:59:03

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