RESEARCH: CANCER
FOLDING PROJECT #18925 PROFILE
PROJECT TEAM
Manager(s): Song YinInstitution: University of Illinois Urbana-Champaign
Project URL: View Project Website
WORK UNIT INFO
Atoms: 85,102Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Lasso peptides are special tiny proteins with unique shapes that can fight cancer and infections. Scientists want to understand how these shapes form so they can design new medicines. This project will use computer simulations to figure out the step-by-step process of how lasso peptides fold into their shapes.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Lasso peptides are ribosomally synthesized and post-translationally modified peptide (RiPP) natural products that display a unique lariat-like, threaded conformation.
Some lasso peptides have been shown to bind human cell-surface receptors and exhibit anticancer properties, while others display antibacterial or antiviral bioactivities.
So studies on the lasso peptide synthesis will significantly facilitate the discovery and application of new drugs. Specifically, previous studies show that the unique lasso topology is formed by a macrolactam ring that is threaded by the C-terminal tail.
While not proven yet, the threading cannot occur after the ring formation.
The general proposed mechanism is that lasso peptide first form a prefolded lariat-like structure, then lasso peptide cyclase catalyzes the ring closure achieved by an isopeptide bond formed between the N-terminal α-amino group of a glycine, alanine, serine, or cysteine and the carboxylic acid side chain of an aspartate or glutamate, which can be located at positions 7, 8, or 9 of the amino acid sequence.
However, MD study on lasso peptide topology is very less and the detailed function of lasso peptide cyclase and the molecular mechanism of the whole lasso peptide cyclization process are not clear.
Therefore, in this study, we will perform Molecular Dynamic simulations for the system of lasso peptide or peptide with cyclase enzyme to explore lasso peptide topology and the cyclization mechanism.
RELATED TERMS GLOSSARY AI BETA
Lasso peptides
Ribosomally synthesized and post-translationally modified peptide natural products with a unique lariat-like conformation.
Lasso peptides are a type of naturally occurring molecule made by ribosomes and further modified after creation. They have a distinctive looping structure and have shown potential as anticancer, antibacterial, and antiviral agents.
RiPP
Ribosomally synthesized and post-translationally modified peptide
RiPP stands for ribosomally synthesized and post-translationally modified peptide. These are naturally occurring molecules produced by ribosomes and further modified after creation.
Macrolactam ring
A cyclic structure formed by the reaction of an amine group with a carboxylic acid group within a peptide chain.
A macrolactam ring is a large, ring-shaped structure found in certain peptides. It forms when a nitrogen atom (amine group) reacts with a carboxyl group (carboxylic acid), closing the peptide chain into a loop.
Lasso peptide cyclase
An enzyme that catalyzes the formation of the macrolactam ring in lasso peptides.
Lasso peptide cyclase is an enzyme responsible for creating the characteristic loop structure in lasso peptides. It facilitates a chemical reaction between specific parts of the peptide chain, forming the macrolactam ring.
Molecular Dynamic simulations
Computer simulations that model the movement of atoms and molecules over time.
Molecular Dynamic simulations are computer programs that simulate how atoms and molecules move and interact. They help researchers understand complex biological processes and design new drugs.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:26:39|
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 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 9,860,096 | 160,898 | 61.28 | 0 hrs 23 mins |
| 2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 9,163,665 | 157,020 | 58.36 | 0 hrs 25 mins |
| 3 | Radeon RX 7900XT/XTX Navi 31 [Radeon RX 7900XT/XTX] |
AMD | Navi 31 | 3,294,419 | 108,042 | 30.49 | 0 hrs 47 mins |
| 4 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 3,117,447 | 110,849 | 28.12 | 0 hrs 51 mins |
| 5 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 3,064,682 | 109,198 | 28.07 | 0 hrs 51 mins |
| 6 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,735,860 | 105,275 | 25.99 | 0 hrs 55 mins |
| 7 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,468,300 | 100,688 | 24.51 | 0 hrs 59 mins |
| 8 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 2,112,497 | 93,227 | 22.66 | 1 hrs 4 mins |
| 9 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,091,760 | 96,459 | 21.69 | 1 hrs 6 mins |
| 10 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 2,035,116 | 85,811 | 23.72 | 1 hrs 1 mins |
| 11 | P102-100 GP102 [P102-100] |
Nvidia | GP102 | 1,924,086 | 88,737 | 21.68 | 1 hrs 6 mins |
| 12 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,840,621 | 89,454 | 20.58 | 1 hrs 10 mins |
| 13 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 1,754,568 | 90,073 | 19.48 | 1 hrs 14 mins |
| 14 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,497,148 | 85,165 | 17.58 | 1 hrs 22 mins |
| 15 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,247,122 | 80,738 | 15.45 | 1 hrs 33 mins |
| 16 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,188,212 | 70,111 | 16.95 | 1 hrs 25 mins |
| 17 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 1,080,167 | 75,327 | 14.34 | 1 hrs 40 mins |
| 18 | Radeon RX 6650XT Navi 23 [Radeon RX 6650XT] |
AMD | Navi 23 | 1,006,176 | 75,493 | 13.33 | 1 hrs 48 mins |
| 19 | Tesla P4 GP104GL [Tesla P4] 5704 |
Nvidia | GP104GL | 1,001,197 | 75,468 | 13.27 | 1 hrs 49 mins |
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| 20 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 947,897 | 73,107 | 12.97 | 1 hrs 51 mins |
| 21 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 893,607 | 70,079 | 12.75 | 1 hrs 53 mins |
| 22 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 758,648 | 68,424 | 11.09 | 2 hrs 10 mins |
| 23 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 674,824 | 64,836 | 10.41 | 2 hrs 18 mins |
| 24 | GeForce GTX 1650 TU116 [GeForce GTX 1650] 3091 |
Nvidia | TU116 | 632,281 | 60,775 | 10.40 | 2 hrs 18 mins |
| 25 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 591,356 | 52,284 | 11.31 | 2 hrs 7 mins |
| 26 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 535,986 | 61,249 | 8.75 | 2 hrs 45 mins |
| 27 | Quadro T1000 Mobile TU117GLM [Quadro T1000 Mobile] |
Nvidia | TU117GLM | 509,220 | 59,827 | 8.51 | 2 hrs 49 mins |
| 28 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 339,222 | 53,071 | 6.39 | 3 hrs 45 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:26:39|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|