Research section Research projects and references

Research: CANCER Folding Project #17625

Project #17625 overview

Project Summary AI Beta

Researchers are studying how changes in proteins affect their ability to work together. They're focusing on a complex pair of proteins called RIPK2, which is important for our immune system. By making small changes to the proteins and observing the results, scientists hope to learn more about how these proteins function and potentially develop new treatments for diseases.
Automated summary; simplified and may not be fully accurate.

Project team

Manager(s)
Sukrit Singh
Institution
Memorial Sloan-Kettering Cancer-Center

Work unit

Atoms
329,840
Core
0x22
Status
Public
Source material

Official Project Description

The previous FEC work unit test was completed successfully so now we're running larger "full size" WUs that are more scientifically useful for studying protein mutations with Free Energy Calculations.

As before, the approach and technology are similar to the Moonshot, but these set of projects instead are studying protein mutations and are much larger (since proteins are also much larger) In this case we are trying out multiple mutations and their impact upon a protein-protein of a dimerization complex (RIPK2), the most complex case.

Performance data

Hardware Performance for Project 17625

Compare community-sampled Folding@Home output for the GPUs and CPUs processing this project.

Data as of Friday, 14 August 2026 15:32:00

GPU PPD Averages

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 6,417,591 1,885,417 3.40 7 hrs 3 mins
2 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 5,764,025 1,777,984 3.24 7 hrs 24 mins
3 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,060,326 1,558,019 2.61 9 hrs 13 mins
4 GeForce RTX 3070 Mobile / Max-Q
GA104M [GeForce RTX 3070 Mobile / Max-Q]
Nvidia GA104M 2,851,939 1,384,040 2.06 11 hrs 39 mins
5 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,794,274 1,401,262 1.99 12 hrs 2 mins
6 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,113,209 1,234,408 1.71 14 hrs 1 mins
7 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,481,904 1,114,885 1.33 18 hrs 3 mins
8 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 460,156 756,808 0.61 39 hrs 28 mins