PROJECT #18003 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: 61,571

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 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,024,167 339,585 14.80 2 hrs 37 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 4,946,467 336,560 14.70 2 hrs 38 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 3,736,657 310,740 12.03 2 hrs 60 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,149,781 290,052 10.86 2 hrs 13 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,123,779 293,357 10.65 2 hrs 15 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,991,735 287,405 10.41 2 hrs 18 mins
7 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,538,618 273,227 9.29 3 hrs 35 mins
8 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,521,178 273,764 9.21 3 hrs 36 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,380,414 267,873 8.89 3 hrs 42 mins
10 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,202,288 261,723 8.41 3 hrs 51 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,200,189 261,719 8.41 3 hrs 51 mins
12 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 2,188,354 261,561 8.37 3 hrs 52 mins
13 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,031,074 254,863 7.97 3 hrs 1 mins
14 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,017,505 254,721 7.92 3 hrs 2 mins
15 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,919,941 250,058 7.68 3 hrs 8 mins
16 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,914,188 249,425 7.67 3 hrs 8 mins
17 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,899,900 249,449 7.62 3 hrs 9 mins
18 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,688,613 237,822 7.10 3 hrs 23 mins
19 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,580,107 234,572 6.74 4 hrs 34 mins
20 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,529,084 231,455 6.61 4 hrs 38 mins
21 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,467,981 223,226 6.58 4 hrs 39 mins
22 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,423,375 225,390 6.32 4 hrs 48 mins
23 Quadro P5000
GP104GL [Quadro P5000]
Nvidia GP104GL 1,217,838 214,950 5.67 4 hrs 14 mins
24 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,106,378 207,649 5.33 5 hrs 30 mins
25 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,087,024 185,814 5.85 4 hrs 6 mins
26 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 947,476 192,321 4.93 5 hrs 52 mins
27 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 654,841 173,548 3.77 6 hrs 22 mins
28 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 609,110 170,678 3.57 7 hrs 44 mins
29 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 598,970 169,207 3.54 7 hrs 47 mins
30 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 530,027 162,446 3.26 7 hrs 21 mins
31 GeForce GTX 1650
TU116 [GeForce GTX 1650] 2984
Nvidia TU116 514,899 161,459 3.19 8 hrs 32 mins
32 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 446,806 154,289 2.90 8 hrs 17 mins
33 P104-100
GP104 [P104-100]
Nvidia GP104 398,682 148,365 2.69 9 hrs 56 mins
34 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 352,853 135,894 2.60 9 hrs 15 mins
35 P106-100
GP106 [P106-100]
Nvidia GP106 310,625 135,973 2.28 11 hrs 30 mins
36 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 270,323 116,759 2.32 10 hrs 22 mins
37 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 137,004 103,715 1.32 18 hrs 10 mins
38 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 101,779 78,422 1.30 18 hrs 30 mins
39 Quadro P500 Mobile
GP108GLM [Quadro P500 Mobile]
Nvidia GP108GLM 25,078 74,045 0.34 71 hrs 52 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