PROJECT #18017 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: 98,391

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Saturday, 01 April 2023 12:14:47

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 6,183,329 295,378 20.93 1 hrs 9 mins
2 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 4,615,312 267,928 17.23 1 hrs 24 mins
3 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,555,386 258,349 17.63 1 hrs 22 mins
4 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 3,980,864 255,691 15.57 2 hrs 32 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,766,245 249,752 15.08 2 hrs 35 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 3,706,584 247,814 14.96 2 hrs 36 mins
7 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 3,464,579 396,289 8.74 3 hrs 45 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 2,775,464 225,740 12.29 2 hrs 57 mins
9 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,570,020 220,342 11.66 2 hrs 3 mins
10 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,542,958 219,619 11.58 2 hrs 4 mins
11 TITAN Xp
GP102 [TITAN Xp] 12150
Nvidia GP102 2,522,957 218,612 11.54 2 hrs 5 mins
12 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 2,328,719 213,282 10.92 2 hrs 12 mins
13 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 2,071,037 205,309 10.09 2 hrs 23 mins
14 Radeon RX 6800/6800 XT / 6900 XT
Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]
AMD Navi 21 2,045,706 204,314 10.01 2 hrs 24 mins
15 GeForce RTX 2080
TU104 [GeForce RTX 2080]
Nvidia TU104 2,035,861 199,820 10.19 2 hrs 21 mins
16 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,839,572 195,675 9.40 3 hrs 33 mins
17 Radeon VII
Vega 20 [Radeon VII] 13,284
AMD Vega 20 1,676,870 190,969 8.78 3 hrs 44 mins
18 GeForce RTX 3070 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3070 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,675,578 190,979 8.77 3 hrs 44 mins
19 Radeon RX 5600 OEM/5600 XT/5700/5700 XT
Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]
AMD Navi 10 1,383,268 178,725 7.74 3 hrs 6 mins
20 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,243,646 173,371 7.17 3 hrs 21 mins
21 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,238,797 172,804 7.17 3 hrs 21 mins
22 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 1,099,070 165,701 6.63 4 hrs 37 mins
23 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,036,896 162,331 6.39 4 hrs 45 mins
24 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 705,932 143,020 4.94 5 hrs 52 mins
25 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 629,456 138,422 4.55 5 hrs 17 mins
26 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 462,071 112,264 4.12 6 hrs 50 mins
27 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 390,844 111,626 3.50 7 hrs 51 mins
28 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 269,336 103,948 2.59 9 hrs 16 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Saturday, 01 April 2023 12:14:47

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