PROJECT #18013 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: 49,887

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Friday, 03 December 2021 04:36:08

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 4,840,172 272,125 17.79 1 hrs 21 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,633,135 267,527 17.32 1 hrs 23 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 3,613,684 248,163 14.56 2 hrs 39 mins
4 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,285,123 240,244 13.67 2 hrs 45 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,068,397 233,726 13.13 2 hrs 50 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,983,926 232,014 12.86 2 hrs 52 mins
7 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,514,000 219,905 11.43 2 hrs 6 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,396,234 216,271 11.08 2 hrs 10 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,312,233 213,418 10.83 2 hrs 13 mins
10 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,199,908 210,683 10.44 2 hrs 18 mins
11 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,107,722 207,478 10.16 2 hrs 22 mins
12 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 1,976,384 202,206 9.77 2 hrs 27 mins
13 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,907,599 200,624 9.51 3 hrs 31 mins
14 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,894,443 200,516 9.45 3 hrs 32 mins
15 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,828,309 196,971 9.28 3 hrs 35 mins
16 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,827,284 198,315 9.21 3 hrs 36 mins
17 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,710,816 194,051 8.82 3 hrs 43 mins
18 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,687,501 191,885 8.79 3 hrs 44 mins
19 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,557,957 187,226 8.32 3 hrs 53 mins
20 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,499,378 183,133 8.19 3 hrs 56 mins
21 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,487,818 184,110 8.08 3 hrs 58 mins
22 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,484,166 184,371 8.05 3 hrs 59 mins
23 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,360,929 177,991 7.65 3 hrs 8 mins
24 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 1,261,038 175,144 7.20 3 hrs 20 mins
25 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,139,402 160,253 7.11 3 hrs 23 mins
26 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,089,775 163,697 6.66 4 hrs 36 mins
27 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,035,495 164,663 6.29 4 hrs 49 mins
28 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 974,811 160,471 6.07 4 hrs 57 mins
29 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 912,480 156,709 5.82 4 hrs 7 mins
30 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 698,039 143,493 4.86 5 hrs 56 mins
31 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 637,204 139,005 4.58 5 hrs 14 mins
32 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 599,001 135,864 4.41 5 hrs 27 mins
33 GeForce GTX 1650
TU117 [GeForce GTX 1650] 3091
Nvidia TU117 529,124 131,495 4.02 6 hrs 58 mins
34 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 504,873 129,151 3.91 6 hrs 8 mins
35 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 473,052 121,088 3.91 6 hrs 9 mins
36 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 445,911 124,207 3.59 7 hrs 41 mins
37 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 337,389 113,213 2.98 8 hrs 3 mins
38 GeForce GTX 1050 Mobile
GP107M [GeForce GTX 1050 Mobile]
Nvidia GP107M 265,239 104,146 2.55 9 hrs 25 mins
39 P106-100
GP106 [P106-100]
Nvidia GP106 258,230 103,243 2.50 10 hrs 36 mins
40 GeForce GTX 1050 Ti Mobile
GP107M [GeForce GTX 1050 Ti Mobile]
Nvidia GP107M 233,735 99,403 2.35 10 hrs 12 mins
41 P104-100
GP104 [P104-100]
Nvidia GP104 159,193 53,545 2.97 8 hrs 4 mins
42 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 155,350 53,545 2.90 8 hrs 16 mins
43 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 122,573 80,727 1.52 16 hrs 48 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 03 December 2021 04:36:08

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