RESEARCH: CANCER
FOLDING PROJECT #15312 PROFILE

PROJECT TEAM

Manager(s): Miko Miwa
Institution: UIUC

WORK UNIT INFO

Atoms: 89,572
Core: 0x27
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project relates to graspetides - tiny, powerful proteins with unique ring structures. Scientists will use computer simulations to figure out how these rings form and why different types of graspetides have different ring patterns. This could lead to new medicines based on these amazing molecules.

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) characterized by ATP-grasp ligase-catalyzed macrolactam or macrolactone linkages in their structure.

Scientific: Biopharmaceuticals
Biotechnology / Peptide Chemistry, Antimicrobial Peptides

Graspetides are a type of antimicrobial peptide produced by bacteria. They have a unique structure with rings formed through chemical reactions. These rings give them stability and allow them to fight against viruses, bacteria, and even enzymes. Researchers are studying how the specific sequence of amino acids in graspetides determines the formation of these rings.


RiPPs

Ribosomally synthesized and post-translationally modified peptides

Scientific: Biopharmaceuticals
Biotechnology / Peptide Chemistry

RiPPs are a diverse group of small proteins produced by bacteria. They are made on ribosomes like regular proteins but then undergo further chemical modifications after synthesis. These modifications give them unique properties and functions, such as fighting infections or regulating cellular processes.


ATP-grasp ligase

An enzyme family that catalyzes the formation of macrolactam or macrolactone linkages in peptides.

Technical: Biopharmaceuticals
Biotechnology / Enzymology, Peptide Synthesis

ATP-grasp ligases are specialized enzymes that play a crucial role in building the unique rings found in graspetides. They use energy from ATP (a cellular energy source) to join specific parts of a peptide chain together, forming stable rings. This process is essential for giving graspetides their antimicrobial properties.


Macrolactam

A cyclic structure formed by a peptide bond between the carboxyl group of one amino acid and the amine group of another amino acid.

Scientific: Biopharmaceuticals
Biotechnology / Peptide Chemistry

Macrolactam is a type of ring structure commonly found in peptides. It's formed when the end of a peptide chain connects back to itself through a specific chemical bond. This creates a stable loop, contributing to the overall stability and function of the peptide.


Macrolactone

A cyclic structure formed by an ester bond between the carboxyl group of one amino acid and the hydroxyl group of another.

Scientific: Biopharmaceuticals
Biotechnology / Peptide Chemistry

Macrolactone is another type of ring structure often found in peptides. It's similar to macrolactam but uses a different type of chemical bond – an ester bond – to connect parts of the peptide chain. This creates a stable loop, contributing to the peptide's overall stability and function.


Molecular dynamics (MD)

A computer simulation method used to study the movement and interactions of atoms and molecules over time.

Scientific: Pharmaceuticals
Biotechnology / Computational Biology, Structural Biology

Molecular dynamics (MD) is a powerful tool for understanding how molecules behave. It involves simulating the movements of atoms and molecules in a system over time. This allows researchers to study how proteins fold, how drugs interact with their targets, and other complex biological processes.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:31:47
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 24,314,152 12,072 2014.09 0 hrs 1 mins
2 GeForce RTX 4090
AD102 [GeForce RTX 4090]
Nvidia AD102 19,276,945 61,438 313.76 0 hrs 5 mins
3 GeForce RTX 4080
AD103 [GeForce RTX 4080]
Nvidia AD103 16,129,898 35,306 456.86 0 hrs 3 mins
4 GeForce RTX 4080 SUPER
AD103 [GeForce RTX 4080 SUPER]
Nvidia AD103 16,028,235 22,947 698.49 0 hrs 2 mins
5 GeForce RTX 5070 Ti
GB203 [GeForce RTX 5070 Ti]
Nvidia GB203 12,838,641 49,600 258.84 0 hrs 6 mins
6 GeForce RTX 4070 Ti SUPER
AD103 [GeForce RTX 4070 Ti SUPER]
Nvidia AD103 12,612,545 12,072 1044.78 0 hrs 1 mins
7 GeForce RTX 4070 Ti
AD104 [GeForce RTX 4070 Ti]
Nvidia AD104 11,070,461 135,902 81.46 0 hrs 18 mins
8 GeForce RTX 4070 SUPER
AD104 [GeForce RTX 4070 SUPER]
Nvidia AD104 10,363,869 51,775 200.17 0 hrs 7 mins
9 GeForce RTX 5080
GB203 [GeForce RTX 5080]
Nvidia GB203 10,204,324 12,072 845.29 0 hrs 2 mins
10 GeForce RTX 5070
GB205 [GeForce RTX 5070]
Nvidia GB205 9,568,798 12,072 792.64 0 hrs 2 mins
11 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 8,282,716 163,228 50.74 0 hrs 28 mins
12 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,489,090 153,762 48.71 0 hrs 30 mins
13 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 6,916,922 122,398 56.51 0 hrs 25 mins
14 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 6,885,915 12,072 570.40 0 hrs 3 mins
15 GeForce RTX 5060 Ti
GB206 [GeForce RTX 5060 Ti]
Nvidia GB206 6,247,966 12,072 517.56 0 hrs 3 mins
16 GeForce RTX 4090 Laptop GPU
AD103M / GN21-X11 [GeForce RTX 4090 Laptop GPU]
Nvidia AD103M / GN21-X11 6,128,576 12,072 507.67 0 hrs 3 mins
17 GeForce RTX 4060 Ti
AD106 [GeForce RTX 4060 Ti]
Nvidia AD106 5,897,555 147,245 40.05 0 hrs 36 mins
18 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 5,637,153 111,192 50.70 0 hrs 28 mins
19 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 5,561,276 12,072 460.68 0 hrs 3 mins
20 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 5,356,068 38,951 137.51 0 hrs 10 mins
21 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 Super]
Nvidia TU104 4,869,827 12,072 403.40 0 hrs 4 mins
22 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,333,729 130,620 33.18 0 hrs 43 mins
23 GeForce RTX 5070 Ti Mobile
GB205M [GeForce RTX 5070 Ti Mobile]
Nvidia GB205M 4,296,254 12,072 355.89 0 hrs 4 mins
24 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 4,005,670 237,632 16.86 1 hrs 25 mins
25 GeForce RTX 4070
AD104 [GeForce RTX 4070]
Nvidia AD104 3,929,376 125,692 31.26 0 hrs 46 mins
26 GeForce RTX 4070 Max-Q / Mobile
AD106M [GeForce RTX 4070 Max-Q / Mobile]
Nvidia AD106M 3,788,152 12,072 313.80 0 hrs 5 mins
27 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,452,990 12,072 286.03 0 hrs 5 mins
28 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,381,875 93,346 36.23 0 hrs 40 mins
29 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 3,330,388 12,072 275.88 0 hrs 5 mins
30 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 3,225,888 12,072 267.22 0 hrs 5 mins
31 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,959,381 115,139 25.70 0 hrs 56 mins
32 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,774,547 113,987 24.34 0 hrs 59 mins
33 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 2,464,516 12,072 204.15 0 hrs 7 mins
34 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,307,425 12,072 191.14 0 hrs 8 mins
35 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,215,855 75,426 29.38 0 hrs 49 mins
36 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,728,611 12,072 143.19 0 hrs 10 mins
37 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 1,650,871 12,072 136.75 0 hrs 11 mins
38 RTX A2000
GA106 [RTX A2000]
Nvidia GA106 1,648,084 12,072 136.52 0 hrs 11 mins
39 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,647,824 96,657 17.05 1 hrs 24 mins
40 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 1,478,123 19,656 75.20 0 hrs 19 mins
41 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,445,343 12,072 119.73 0 hrs 12 mins
42 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,260,092 50,963 24.73 0 hrs 58 mins
43 RTX A1000
GA107GL [RTX A1000]
Nvidia GA107GL 1,198,798 12,072 99.30 0 hrs 15 mins
44 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 757,804 73,899 10.25 2 hrs 20 mins
45 GeForce GTX 1650
TU116 [GeForce GTX 1650] 3091
Nvidia TU116 450,897 62,576 7.21 3 hrs 20 mins
46 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 391,873 59,340 6.60 3 hrs 38 mins
47 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 275,034 12,072 22.78 1 hrs 3 mins
48 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 238,527 50,195 4.75 5 hrs 3 mins
49 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 105,449 12,072 8.74 2 hrs 45 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:31:47
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make