PROJECT #18043 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/ All data is being made publicly available in real time at https://console.cloud.google.com/storage/browser/stxfah-bucket.
PROJECT INFO
Manager(s): Rafal Wiewiora
Institution: Roivant Sciences (Silicon Therapeutics)
Project URL: roivant.com
PROJECT WORK UNIT SUMMARY
Atoms: 68,820
Core: OPENMM_22
Status: Public
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Tuesday, 07 February 2023 06:14:51
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 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,959,543 | 414,543 | 14.38 | 2 hrs 40 mins |
2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 5,320,459 | 396,776 | 13.41 | 2 hrs 47 mins |
3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 4,832,462 | 386,572 | 12.50 | 2 hrs 55 mins |
4 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,255,112 | 371,169 | 11.46 | 2 hrs 6 mins |
5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,882,905 | 359,025 | 10.82 | 2 hrs 13 mins |
6 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,408,276 | 343,312 | 9.93 | 2 hrs 25 mins |
7 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 3,387,064 | 344,978 | 9.82 | 2 hrs 27 mins |
8 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 3,207,983 | 335,999 | 9.55 | 3 hrs 31 mins |
9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,940,439 | 320,372 | 9.18 | 3 hrs 37 mins |
10 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,617,961 | 314,141 | 8.33 | 3 hrs 53 mins |
11 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,520,883 | 311,495 | 8.09 | 3 hrs 58 mins |
12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,444,421 | 308,700 | 7.92 | 3 hrs 2 mins |
13 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 2,430,100 | 290,950 | 8.35 | 3 hrs 52 mins |
14 | GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q] |
Nvidia | GA104M | 2,195,749 | 297,921 | 7.37 | 3 hrs 15 mins |
15 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,183,254 | 297,270 | 7.34 | 3 hrs 16 mins |
16 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,984,120 | 287,874 | 6.89 | 3 hrs 29 mins |
17 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,889,421 | 283,350 | 6.67 | 4 hrs 36 mins |
18 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,791,058 | 278,397 | 6.43 | 4 hrs 44 mins |
19 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,571,900 | 266,070 | 5.91 | 4 hrs 4 mins |
20 | Quadro RTX 6000/8000 TU102GL [Quadro RTX 6000/8000] |
Nvidia | TU102GL | 1,476,098 | 261,392 | 5.65 | 4 hrs 15 mins |
21 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,403,962 | 255,118 | 5.50 | 4 hrs 22 mins |
22 | GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile] |
Nvidia | TU106M | 1,350,802 | 254,364 | 5.31 | 5 hrs 31 mins |
23 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,325,351 | 251,273 | 5.27 | 5 hrs 33 mins |
24 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,084,066 | 228,923 | 4.74 | 5 hrs 4 mins |
25 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 885,630 | 218,778 | 4.05 | 6 hrs 56 mins |
26 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 845,485 | 214,360 | 3.94 | 6 hrs 5 mins |
27 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 821,153 | 215,139 | 3.82 | 6 hrs 17 mins |
28 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 805,770 | 213,798 | 3.77 | 6 hrs 22 mins |
29 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 646,290 | 197,199 | 3.28 | 7 hrs 19 mins |
30 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 581,283 | 191,140 | 3.04 | 8 hrs 54 mins |
31 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 544,037 | 183,746 | 2.96 | 8 hrs 6 mins |
32 | Quadro M5000 GM204GL [Quadro M5000] |
Nvidia | GM204GL | 514,387 | 183,435 | 2.80 | 9 hrs 34 mins |
33 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 378,121 | 164,994 | 2.29 | 10 hrs 28 mins |
34 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 366,275 | 163,833 | 2.24 | 11 hrs 44 mins |
35 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 349,681 | 161,231 | 2.17 | 11 hrs 4 mins |
36 | GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q] |
Nvidia | TU117M | 341,662 | 120,968 | 2.82 | 8 hrs 30 mins |
37 | Quadro M4000 GM204GL [Quadro M4000] |
Nvidia | GM204GL | 304,324 | 152,700 | 1.99 | 12 hrs 3 mins |
38 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 301,661 | 153,624 | 1.96 | 12 hrs 13 mins |
39 | T600 TU117GL [T600] |
Intel | TU117GL | 266,796 | 147,602 | 1.81 | 13 hrs 17 mins |
40 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 230,532 | 139,127 | 1.66 | 14 hrs 29 mins |
41 | GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile] |
Nvidia | GP106M | 139,427 | 117,737 | 1.18 | 20 hrs 16 mins |
42 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 135,909 | 117,832 | 1.15 | 21 hrs 48 mins |
43 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 134,020 | 117,113 | 1.14 | 21 hrs 58 mins |
44 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 125,282 | 113,413 | 1.10 | 22 hrs 44 mins |
45 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 81,853 | 90,000 | 0.91 | 26 hrs 23 mins |
46 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 68,275 | 90,000 | 0.76 | 32 hrs 38 mins |
47 | Quadro K620 GM107GL [Quadro K620] |
Nvidia | GM107GL | 56,350 | 90,000 | 0.63 | 38 hrs 20 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Tuesday, 07 February 2023 06:14:51
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|