PROJECT #18106 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

We are simulating publicly available protein and small molecule structures of the currently very hot cancer target KRas, see https://www.fiercepharma.com/pharma/amgen-s-lumakras-becomes-first-fda-approved-kras-inhibitor-for-lung-cancer-patients for recent developments.

Folding@home has previously looked at this protein (in project 10490), and the following part of the description is copied from there: This project is "studying a small protein called KRAS, which forms a key link in growth signaling and cancer.

This gene is something like a molecular switch with a timer.

When it is bound to a molecule called GDP, it is off, and does not signal that the cell should grow.

However, other proteins can cause it to swap its GDP for a GTP, turning KRAS on.

In the on state, it signals that the cell should grow and divide.

Normally, after some time, KRAS, with the aid of some partners, will chemically convert its GTP to GDP and return to its inactive state. In many cancers, this protein becomes mutated, and cannot return to its off state.

The result? The cells continue to divide without limit.

What’s worse, cancers with this protein mutated tend to have much poorer prognoses.

As a result, scientists have been trying to target this protein for decades." We are investigating the dynamic behavior of KRas with these publicly disclosed inhibitors so that we can apply this knowledge to our own drug design.

At the same time, we are further testing the adaptive sampling methodology.

All data is being made publicly available, and insights from methodology developments will be shared.

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: 19,678

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Tuesday, 27 September 2022 13:39:57

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	3,002,499	127,812	23.49	1 ^hrs 1 ^mins
2	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	2,991,841	126,355	23.68	1 ^hrs 1 ^mins
3	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	2,491,744	158,159	15.75	2 ^hrs 31 ^mins
4	TITAN Xp GP102 [TITAN Xp] 12150	Nvidia	GP102	2,243,098	115,656	19.39	1 ^hrs 14 ^mins
5	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	2,152,057	114,490	18.80	1 ^hrs 17 ^mins
6	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	1,977,802	110,888	17.84	1 ^hrs 21 ^mins
7	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465	Nvidia	TU106	1,779,827	107,119	16.62	1 ^hrs 27 ^mins
8	GeForce RTX 2080 TU104 [GeForce RTX 2080]	Nvidia	TU104	1,480,044	100,488	14.73	2 ^hrs 38 ^mins
9	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	1,474,597	100,679	14.65	2 ^hrs 38 ^mins
10	GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti]	Nvidia	GA104	1,458,181	100,376	14.53	2 ^hrs 39 ^mins
11	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	82,999	21,637	3.84	6 ^hrs 15 ^mins
12	GeForce GT 1030 GP108 [GeForce GT 1030] 1127	Nvidia	GP108	65,465	35,818	1.83	13 ^hrs 8 ^mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA