PROJECT #18016 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: 78,834

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Friday, 30 July 2021 00:39:48

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 5,792,911 475,924 12.17 2 hrs 58 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,668,439 472,189 12.00 2 hrs 60 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,332,532 434,663 9.97 2 hrs 24 mins
4 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,624,290 411,085 8.82 3 hrs 43 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,445,057 402,100 8.57 3 hrs 48 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,190,402 392,599 8.13 3 hrs 57 mins
7 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,668,024 371,189 7.19 3 hrs 20 mins
8 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,599,168 367,914 7.06 3 hrs 24 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,534,965 365,141 6.94 3 hrs 27 mins
10 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,413,456 359,293 6.72 4 hrs 34 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,401,971 357,467 6.72 4 hrs 34 mins
12 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,125,239 344,210 6.17 4 hrs 53 mins
13 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,122,189 344,433 6.16 4 hrs 54 mins
14 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,106,690 342,999 6.14 4 hrs 54 mins
15 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 2,106,001 343,688 6.13 4 hrs 55 mins
16 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 2,047,990 340,389 6.02 4 hrs 59 mins
17 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,825,877 325,331 5.61 4 hrs 17 mins
18 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,682,830 315,646 5.33 5 hrs 30 mins
19 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,597,432 313,247 5.10 5 hrs 42 mins
20 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,502,347 306,614 4.90 5 hrs 54 mins
21 Quadro P5000
GP104GL [Quadro P5000]
Nvidia GP104GL 1,399,710 294,846 4.75 5 hrs 3 mins
22 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,271,692 289,136 4.40 5 hrs 27 mins
23 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,247,257 288,473 4.32 6 hrs 33 mins
24 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,100,459 252,550 4.36 6 hrs 30 mins
25 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,072,109 273,228 3.92 6 hrs 7 mins
26 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 892,607 258,277 3.46 7 hrs 57 mins
27 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 748,311 255,917 2.92 8 hrs 12 mins
28 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 726,409 240,614 3.02 8 hrs 57 mins
29 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 567,150 221,289 2.56 9 hrs 22 mins
30 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 547,931 216,685 2.53 9 hrs 29 mins
31 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 485,532 188,804 2.57 9 hrs 20 mins
32 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 460,718 207,444 2.22 11 hrs 48 mins
33 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 419,971 200,178 2.10 11 hrs 26 mins
34 P104-100
GP104 [P104-100]
Nvidia GP104 362,684 160,769 2.26 11 hrs 38 mins
35 P106-100
GP106 [P106-100]
Nvidia GP106 348,153 188,650 1.85 13 hrs 0 mins
36 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 316,894 182,734 1.73 14 hrs 50 mins
37 GeForce GTX 1050 Mobile
GP107M [GeForce GTX 1050 Mobile]
Nvidia GP107M 275,666 174,434 1.58 15 hrs 11 mins
38 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 67,559 113,668 0.59 40 hrs 23 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 30 July 2021 00:39:48

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