PROJECT #18015 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: 69,696

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 5,015,344 386,168 12.99 2 hrs 51 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 4,767,437 378,234 12.60 2 hrs 54 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,086,057 362,212 11.28 2 hrs 8 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,372,382 339,067 9.95 2 hrs 25 mins
5 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,334,828 339,455 9.82 2 hrs 27 mins
6 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 2,779,666 313,235 8.87 3 hrs 42 mins
7 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,565,122 310,946 8.25 3 hrs 55 mins
8 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,471,663 307,780 8.03 3 hrs 59 mins
9 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,343,651 301,949 7.76 3 hrs 6 mins
10 RTX A4000
GA104GL [RTX A4000]
GA104GL 2,295,519 300,205 7.65 3 hrs 8 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,236,958 297,845 7.51 3 hrs 12 mins
12 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,031,477 288,206 7.05 3 hrs 24 mins
13 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,003,641 285,525 7.02 3 hrs 25 mins
14 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,003,536 287,215 6.98 3 hrs 26 mins
15 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 1,982,625 286,123 6.93 3 hrs 28 mins
16 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,971,610 284,979 6.92 3 hrs 28 mins
17 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,969,839 285,540 6.90 3 hrs 29 mins
18 Quadro RTX 6000/8000
TU102GL [Quadro RTX 6000/8000]
Nvidia TU102GL 1,847,574 280,130 6.60 4 hrs 38 mins
19 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,764,029 271,098 6.51 4 hrs 41 mins
20 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,712,985 272,747 6.28 4 hrs 49 mins
21 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,619,933 267,163 6.06 4 hrs 57 mins
22 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,515,264 262,978 5.76 4 hrs 10 mins
23 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,511,717 249,196 6.07 4 hrs 57 mins
24 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,499,776 265,243 5.65 4 hrs 15 mins
25 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,366,404 247,773 5.51 4 hrs 21 mins
26 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,274,417 246,868 5.16 5 hrs 39 mins
27 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,188,137 242,018 4.91 5 hrs 53 mins
28 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 995,871 219,966 4.53 5 hrs 18 mins
29 Quadro P5000
GP104GL [Quadro P5000]
Nvidia GP104GL 985,211 190,983 5.16 5 hrs 39 mins
30 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 941,512 219,212 4.29 6 hrs 35 mins
31 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 869,636 217,566 4.00 6 hrs 0 mins
32 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 635,241 193,480 3.28 7 hrs 19 mins
33 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 586,494 190,828 3.07 8 hrs 49 mins
34 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 559,909 185,791 3.01 8 hrs 58 mins
35 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 528,997 184,248 2.87 8 hrs 22 mins
36 Quadro T2000 Mobile / Max-Q
TU117GLM [Quadro T2000 Mobile / Max-Q]
Nvidia TU117GLM 429,872 171,951 2.50 10 hrs 36 mins
37 GeForce GTX 1650
TU116 [GeForce GTX 1650] 2984
Nvidia TU116 334,605 148,631 2.25 11 hrs 40 mins
38 P106-100
GP106 [P106-100]
Nvidia GP106 316,718 155,263 2.04 12 hrs 46 mins
39 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 283,462 132,691 2.14 11 hrs 14 mins
40 GeForce GTX 1050 Mobile
GP107M [GeForce GTX 1050 Mobile]
Nvidia GP107M 266,194 146,238 1.82 13 hrs 11 mins
41 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 221,481 134,612 1.65 15 hrs 35 mins
42 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 142,493 89,130 1.60 15 hrs 1 mins
43 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 87,238 89,130 0.98 25 hrs 31 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