RESEARCH: CANCER
FOLDING PROJECT #15309 PROFILE

PROJECT TEAM

Manager(s): Miko Miwa
Institution: UIUC

WORK UNIT INFO

Atoms: 66,837
Core: 0x27
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project investigates how different types of graspetides, small proteins with unique rings, fold into their shapes. By using computer simulations, researchers will explore the order in which these rings form and try to understand what makes each type of graspetide unique.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

Graspetides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by the ATP-grasp ligase–catalyzed macrolactam or macrolactone linkages in their structure.

These macrocycles impart structural stability and diverse bioactivities, including antimicrobial, antiviral, and enzyme inhibitory effects.

Graspetides are classified into distinct groups based on sequence motifs, cyclization patterns, and biosynthetic machinery.

While each group exhibits characteristic ring topologies, the molecular basis by which core peptide sequence and folding pathways dictate the order of ring formation remains poorly understood. In this study, we will investigate model species from multiple graspetide groups using atomic-level molecular dynamics (MD) simulations.

By comparing folding trajectories across these representative systems, we aim to identify conserved and group-specific determinants of ring pattern formation, and to assess whether distinct biosynthetic groups exhibit preferences for particular ring closure orders.

RELATED TERMS GLOSSARY AI BETA

Note: Glossary items are a high level summary and may not be 100% accurate.

Graspetides

A class of ribosomally synthesized and post-translationally modified peptides (RiPPs).

Scientific: Pharmaceutical Research
Biotechnology / Peptides

Graspetides are a type of peptide produced by living organisms. They have unique structures with rings called macrolactam or macrolactone linkages. These rings make them strong and give them various abilities, such as fighting bacteria and viruses. Scientists are studying how graspetides form these rings and what makes different types unique.


Ribosomally synthesized and post-translationally modified peptides (RiPPs)

Ribosomally synthesized and post-translationally modified peptides (RiPPs)

Scientific: Pharmaceutical Research
Biotechnology / Peptides

RiPPs are a special type of peptide made by ribosomes (the protein factories in cells). After being made by ribosomes, RiPPs go through changes that make them more complex and useful. They have many important functions in living things.


Macrolactam

A cyclic amide formed by the reaction of an amine with a carboxylic acid.

Scientific: Pharmaceutical Research
Biotechnology / Peptides

Macrolactam is a type of ring structure found in some peptides. It's formed when a part of the peptide chain connects back to itself through a chemical bond. This makes the peptide more stable and can give it special properties.


Macrolactone

A cyclic ester formed by the reaction of a carboxylic acid with an alcohol.

Scientific: Pharmaceutical Research
Biotechnology / Peptides

Macrolactone is another type of ring structure found in some peptides. It's formed when a part of the peptide chain connects back to itself through a different chemical bond. Like macrolactam, it makes the peptide more stable and can give it special properties.


Molecular dynamics (MD)

Molecular dynamics (MD)

Scientific: Pharmaceutical Research
Biotechnology / Simulation

Molecular dynamics is a computer simulation technique used to study how atoms and molecules move and interact over time. It's a powerful tool for understanding the behavior of complex systems like proteins and DNA.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:31:49
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 5090
GB202 [GeForce RTX 5090]
Nvidia GB202 20,658,913 7,838 2635.74 0 hrs 1 mins
2 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 16,913,503 34,851 485.31 0 hrs 3 mins
3 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 15,227,143 21,817 697.95 0 hrs 2 mins
4 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 14,211,006 16,230 875.60 0 hrs 2 mins
5 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 11,819,532 35,951 328.77 0 hrs 4 mins
6 GeForce RTX 4070 Ti SUPER
AD103 [GeForce RTX 4070 Ti SUPER]
Nvidia AD103 11,457,593 7,838 1461.80 0 hrs 1 mins
7 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 10,601,162 108,276 97.91 0 hrs 15 mins
8 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 9,851,592 70,742 139.26 0 hrs 10 mins
9 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 9,346,549 7,838 1192.47 0 hrs 1 mins
10 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 8,295,915 7,838 1058.42 0 hrs 1 mins
11 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,841,074 83,134 94.32 0 hrs 15 mins
12 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 7,017,646 7,838 895.34 0 hrs 2 mins
13 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,990,873 114,403 61.11 0 hrs 24 mins
14 GeForce RTX 5060 Ti
GB206 [GeForce RTX 5060 Ti]
Nvidia GB206 6,582,463 7,838 839.81 0 hrs 2 mins
15 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 6,498,258 7,838 829.07 0 hrs 2 mins
16 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 6,308,244 276,217 22.84 1 hrs 3 mins
17 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 5,550,747 106,708 52.02 0 hrs 28 mins
18 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 5,506,498 56,026 98.28 0 hrs 15 mins
19 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 5,388,450 7,838 687.48 0 hrs 2 mins
20 GeForce RTX 5060
GB206 [GeForce RTX 5060]
Nvidia GB206 5,284,162 7,838 674.17 0 hrs 2 mins
21 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 5,266,207 68,617 76.75 0 hrs 19 mins
22 GeForce RTX 5070 Ti Mobile
GB205M [GeForce RTX 5070 Ti Mobile]
Nvidia GB205M 4,943,472 7,838 630.71 0 hrs 2 mins
23 GeForce RTX 4070 Max-Q / Mobile
AD106M [GeForce RTX 4070 Max-Q / Mobile]
Nvidia AD106M 4,908,032 7,838 626.18 0 hrs 2 mins
24 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,379,718 99,621 43.96 0 hrs 33 mins
25 RTX 4000 SFF Ada Generation
AD104GL [RTX 4000 SFF Ada Generation]
Nvidia AD104GL 4,354,263 7,838 555.53 0 hrs 3 mins
26 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 3,737,013 91,896 40.67 0 hrs 35 mins
27 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,320,872 7,838 423.69 0 hrs 3 mins
28 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,281,642 7,838 418.68 0 hrs 3 mins
29 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,023,852 86,864 34.81 0 hrs 41 mins
30 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,824,429 85,719 32.95 0 hrs 44 mins
31 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,505,173 7,838 319.62 0 hrs 5 mins
32 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 2,357,684 7,838 300.80 0 hrs 5 mins
33 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,343,219 33,323 70.32 0 hrs 20 mins
34 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 2,254,918 7,838 287.69 0 hrs 5 mins
35 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,434,173 46,177 31.06 0 hrs 46 mins
36 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,329,045 7,838 169.56 0 hrs 8 mins
37 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,320,405 7,838 168.46 0 hrs 9 mins
38 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 1,276,382 7,838 162.85 0 hrs 9 mins
39 RTX A1000
GA107GL [RTX A1000]
Nvidia GA107GL 1,188,569 7,838 151.64 0 hrs 9 mins
40 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 829,362 56,880 14.58 1 hrs 39 mins
41 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 447,224 45,165 9.90 2 hrs 25 mins
42 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 104,919 7,838 13.39 1 hrs 48 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:31:49
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make