RESEARCH: CANCER
FOLDING PROJECT #18119 PROFILE
PROJECT TEAM
Manager(s): Rafal WiewioraInstitution: Roivant Sciences (Silicon Therapeutics)
Project URL: View Project Website
WORK UNIT INFO
Atoms: 25,000Core: OPENMM_22
Status: Beta
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how KRAS, a protein involved in cancer growth, works with drugs that aim to block it. By understanding these interactions, scientists hope to design better cancer treatments. The results of their work will be shared publicly.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
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 at https://console.cloud.google.com/storage/browser/stxfah-bucket, 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/ All data is being made publicly available as soon as it is received at https://console.cloud.google.com/storage/browser/stxfah-bucket.
RELATED TERMS GLOSSARY AI BETA
KRas
Kirsten rat sarcoma viral oncogene homolog
KRas is a protein that plays a crucial role in cell growth and division. Mutations in the KRAS gene can lead to uncontrolled cell growth, contributing to cancer development.
GDP
Guanosine diphosphate
GDP is a molecule that binds to KRas protein, keeping it in an inactive state. When GDP is replaced by GTP, KRas becomes active and promotes cell growth.
GTP
Guanosine triphosphate
GTP is a molecule that binds to KRas protein, activating it and promoting cell growth and division. The replacement of GDP with GTP triggers the active state of KRas.
Inhibitors
Substances that block the activity of a specific target, such as KRas protein.
Inhibitors are molecules designed to prevent KRas from functioning properly. By inhibiting KRas, they aim to halt cancer cell growth and spread.
Protein
Large, complex molecules made up of amino acids that perform various functions in living organisms.
Proteins are essential building blocks of cells and tissues. They carry out a wide range of tasks, including catalyzing reactions, transporting molecules, and providing structural support.
Mutation
A permanent change in the DNA sequence of a gene.
Mutations can alter the function of proteins, leading to various diseases, including cancer. In the case of KRas mutations, they prevent the protein from returning to its inactive state, promoting uncontrolled cell growth.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 00:32:00|
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 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,739,775 | 106,039 | 16.41 | 1 hrs 28 mins |
| 2 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 659,626 | 82,639 | 7.98 | 3 hrs 0 mins |
| 3 | GeForce GT 1030 GP108 [GeForce GT 1030] 1127 |
Nvidia | GP108 | 38,645 | 32,217 | 1.20 | 20 hrs 0 mins |
| 4 | GeForce 920M GK208 [GeForce 920M] |
Nvidia | GK208 | 34,408 | 30,973 | 1.11 | 21 hrs 36 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 00:32:00|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|