RESEARCH: CANCER
FOLDING PROJECT #15320 PROFILE
PROJECT TEAM
Manager(s): Miko MiwaInstitution: UIUC
WORK UNIT INFO
Atoms: 152,829Core: 0x27
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project explores how graspetides, a type of naturally occurring protein, fold into unique shapes. By using computer simulations, researchers will try to understand the rules that govern how these proteins form their characteristic rings and if different types of graspetides have specific ways of folding.
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
Graspetides
A class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by macrolactam or macrolactone linkages.
Graspetides are a unique type of molecule produced by living organisms. They're made up of smaller building blocks called amino acids, linked together in specific patterns. These patterns create rings that give graspetides their strength and allow them to perform various functions like fighting infections or blocking the activity of enzymes.
Ribosomally synthesized and post-translationally modified peptides (RiPPs)
Ribosomally synthesized and post-translationally modified peptides (RiPPs)
This refers to a group of molecules made by ribosomes within cells. They are initially produced as simpler chains that then undergo chemical changes after they are created. These modifications often turn them into potent drugs or tools used in research.
Macrolactam
A cyclic amide formed by the reaction between an amino group and a carboxyl group in a molecule.
Think of macrolactams as large rings formed by chemical connections within a molecule. These rings often give molecules extra strength and stability.
Macrolactone
A cyclic ester formed by the reaction between a hydroxyl group and a carboxyl group in a molecule.
Macrolactones are similar to macrolactams but instead of an amide bond, they have an ester bond. They also form rings within molecules, providing stability.
Molecular Dynamics (MD) Simulations
Molecular Dynamics (MD) Simulations
This involves using powerful computers to model how atoms and molecules move and interact over time. It's a way to understand how molecules behave without having to do physical experiments.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:31:44|
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 | 37,530,178 | 25,956 | 1445.92 | 0 hrs 1 mins |
| 2 | GeForce RTX 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 20,300,273 | 221,956 | 91.46 | 0 hrs 16 mins |
| 3 | GeForce RTX 5080 GB203 [GeForce RTX 5080] |
Nvidia | GB203 | 18,589,433 | 25,956 | 716.19 | 0 hrs 2 mins |
| 4 | GeForce RTX 4080 SUPER AD103 [GeForce RTX 4080 SUPER] |
Nvidia | AD103 | 16,225,501 | 174,245 | 93.12 | 0 hrs 15 mins |
| 5 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 15,833,936 | 273,649 | 57.86 | 0 hrs 25 mins |
| 6 | GeForce RTX 5070 Ti GB203 [GeForce RTX 5070 Ti] |
Nvidia | GB203 | 13,410,604 | 65,161 | 205.81 | 0 hrs 7 mins |
| 7 | GeForce RTX 4070 Ti SUPER AD103 [GeForce RTX 4070 Ti SUPER] |
Nvidia | AD103 | 12,450,960 | 25,956 | 479.69 | 0 hrs 3 mins |
| 8 | GeForce RTX 4070 SUPER AD104 [GeForce RTX 4070 SUPER] |
Nvidia | AD104 | 10,901,417 | 61,250 | 177.98 | 0 hrs 8 mins |
| 9 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 10,686,062 | 268,474 | 39.80 | 0 hrs 36 mins |
| 10 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 10,397,951 | 295,219 | 35.22 | 0 hrs 41 mins |
| 11 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 10,221,344 | 253,447 | 40.33 | 0 hrs 36 mins |
| 12 | GeForce RTX 5070 GB205 [GeForce RTX 5070] |
Nvidia | GB205 | 9,822,225 | 25,956 | 378.42 | 0 hrs 4 mins |
| 13 | Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE] |
AMD | Navi 31 | 7,021,025 | 63,092 | 111.28 | 0 hrs 13 mins |
| 14 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 6,730,185 | 25,956 | 259.29 | 0 hrs 6 mins |
| 15 | GeForce RTX 5060 Ti GB206 [GeForce RTX 5060 Ti] |
Nvidia | GB206 | 6,551,562 | 25,956 | 252.41 | 0 hrs 6 mins |
| 16 | GeForce RTX 4060 Ti AD106 [GeForce RTX 4060 Ti] |
Nvidia | AD106 | 6,233,722 | 319,793 | 19.49 | 1 hrs 14 mins |
| 17 | GeForce RTX 5070 Ti Mobile GB205M [GeForce RTX 5070 Ti Mobile] |
Nvidia | GB205M | 5,946,915 | 25,956 | 229.12 | 0 hrs 6 mins |
| 18 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 5,934,467 | 219,816 | 27.00 | 0 hrs 53 mins |
| 19 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,344,457 | 65,011 | 82.21 | 0 hrs 18 mins |
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| 20 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 5,219,528 | 162,134 | 32.19 | 0 hrs 45 mins |
| 21 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,766,893 | 143,510 | 33.22 | 0 hrs 43 mins |
| 22 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 Super] |
Nvidia | TU104 | 4,656,892 | 25,956 | 179.41 | 0 hrs 8 mins |
| 23 | Radeon RX 9070(XT) Navi 48 [Radeon RX 9070(XT)] |
AMD | Navi 48 | 4,559,958 | 135,242 | 33.72 | 0 hrs 43 mins |
| 24 | GeForce RTX 4070 Max-Q / Mobile AD106M [GeForce RTX 4070 Max-Q / Mobile] |
Nvidia | AD106M | 4,542,519 | 25,956 | 175.01 | 0 hrs 8 mins |
| 25 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 4,490,571 | 225,728 | 19.89 | 1 hrs 12 mins |
| 26 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 4,321,336 | 25,956 | 166.49 | 0 hrs 9 mins |
| 27 | GeForce RTX 4070 AD104 [GeForce RTX 4070] |
Nvidia | AD104 | 3,916,694 | 158,960 | 24.64 | 0 hrs 58 mins |
| 28 | Radeon RX 6800(XT)/6900XT Navi 21 [Radeon RX 6800(XT)/6900XT] |
AMD | Navi 21 | 3,683,691 | 162,666 | 22.65 | 1 hrs 4 mins |
| 29 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 3,250,614 | 25,956 | 125.24 | 0 hrs 11 mins |
| 30 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,227,372 | 199,372 | 16.19 | 1 hrs 29 mins |
| 31 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,200,087 | 25,956 | 123.29 | 0 hrs 12 mins |
| 32 | GeForce RTX 4050 Max-Q / Mobile AD107M [GeForce RTX 4050 Max-Q / Mobile] |
Nvidia | AD107M | 2,985,726 | 25,956 | 115.03 | 0 hrs 13 mins |
| 33 | GeForce RTX 3060 GA104 [GeForce RTX 3060] |
Nvidia | GA104 | 2,372,597 | 25,956 | 91.41 | 0 hrs 16 mins |
| 34 | Radeon RX 6700(XT)/6800M Navi 22 XT-XL [Radeon RX 6700(XT)/6800M] |
AMD | Navi 22 XT-XL | 1,988,189 | 25,956 | 76.60 | 0 hrs 19 mins |
| 35 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 1,403,073 | 25,956 | 54.06 | 0 hrs 27 mins |
| 36 | GeForce GTX 1070 Mobile GP104BM [GeForce GTX 1070 Mobile] 6463 |
Nvidia | GP104BM | 592,745 | 75,000 | 7.90 | 3 hrs 2 mins |
| 37 | R9 Fury X/NANO Fiji XT [R9 Fury X/NANO] |
AMD | Fiji XT | 519,967 | 25,956 | 20.03 | 1 hrs 12 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:31:44|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|