PROJECT #18014 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: 49,034

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Monday, 27 September 2021 14:58:25

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 4,693,756 267,651 17.54 1 hrs 22 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,490,738 262,918 17.08 1 hrs 24 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 3,666,860 248,154 14.78 2 hrs 37 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,283,159 237,949 13.80 2 hrs 44 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,073,826 231,942 13.25 2 hrs 49 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 2,896,126 229,501 12.62 2 hrs 54 mins
7 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,557,072 221,054 11.57 2 hrs 4 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,460,482 218,235 11.27 2 hrs 8 mins
9 RTX A4000
GA104GL [RTX A4000]
Nvidia GA104GL 2,434,118 218,326 11.15 2 hrs 9 mins
10 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 2,290,055 213,495 10.73 2 hrs 14 mins
11 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,187,813 210,162 10.41 2 hrs 18 mins
12 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,127,888 206,468 10.31 2 hrs 20 mins
13 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,086,540 206,742 10.09 2 hrs 23 mins
14 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A] M 7465
Nvidia TU106 2,004,552 203,736 9.84 2 hrs 26 mins
15 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 1,993,012 203,103 9.81 2 hrs 27 mins
16 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 1,875,984 199,548 9.40 3 hrs 33 mins
17 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,861,992 198,966 9.36 3 hrs 34 mins
18 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,764,730 194,139 9.09 3 hrs 38 mins
19 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,726,141 193,791 8.91 3 hrs 42 mins
20 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,667,608 192,041 8.68 3 hrs 46 mins
21 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,613,093 183,924 8.77 3 hrs 44 mins
22 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,498,788 185,183 8.09 3 hrs 58 mins
23 GeForce RTX 3060
GA106 [GeForce RTX 3060]
Nvidia GA106 1,484,248 184,146 8.06 3 hrs 59 mins
24 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,292,567 176,294 7.33 3 hrs 16 mins
25 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,229,498 159,244 7.72 3 hrs 7 mins
26 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,115,462 166,568 6.70 4 hrs 35 mins
27 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,095,579 161,752 6.77 4 hrs 33 mins
28 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 1,072,359 122,930 8.72 3 hrs 45 mins
29 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 996,342 158,434 6.29 4 hrs 49 mins
30 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 947,834 158,927 5.96 4 hrs 1 mins
31 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 716,169 144,493 4.96 5 hrs 51 mins
32 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 680,351 140,776 4.83 5 hrs 58 mins
33 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 616,539 137,682 4.48 5 hrs 22 mins
34 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 589,221 134,504 4.38 5 hrs 29 mins
35 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 552,718 131,394 4.21 6 hrs 42 mins
36 GeForce GTX 1650
TU116 [GeForce GTX 1650] 2984
Nvidia TU116 536,004 131,574 4.07 6 hrs 53 mins
37 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 368,374 115,962 3.18 8 hrs 33 mins
38 P106-100
GP106 [P106-100]
Nvidia GP106 213,332 80,013 2.67 9 hrs 0 mins
39 GeForce GT 1030
GP108 [GeForce GT 1030] 1127
Nvidia GP108 112,700 63,691 1.77 14 hrs 34 mins
40 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 6,982 53,446 0.13 184 hrs 43 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Monday, 27 September 2021 14:58:25

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