RESEARCH: BIOFILM
FOLDING PROJECT #18446 PROFILE
PROJECT TEAM
Manager(s): Prof. Vincent VoelzInstitution: Temple University
WORK UNIT INFO
Atoms: 60,389Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Bacteria can group together to form sticky biofilms, making them hard to treat with antibiotics. A project relates to a protein called LapD that stops another protein (LapG) from breaking down a key biofilm building block. Scientists are designing mini-proteins that act like LapD to disrupt biofilm formation and use computer simulations to understand how these mini-proteins work.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Biofilms are aggregations of bacteria that occur in response to external stresses.
They are found in natural, industrial, and clinical environments, where they can be an impediment to effective antibiotic treatments.
In Pseudomonas fluorescens, this process is initiated by the Lap system, particularly the LapA adhesin.
LapG, a periplasmic protease, cleaves the N-terminus of LapA, releasing it from its adherent surface and inhibiting the ability to form a biofilm.
LapG’s ability to cleave LapA is prevented by LapD, which keeps the protease away from the cell surface through a unique protein-protein interaction (PPI) interface involving a highly conserved tryptophan of LapD. In an effort to develop molecules that can disrupt biofilm formation, the Bahl lab at the Institute for Protein Innovation has de novo designed high-affinity mini-proteins that mimic LapD and bind LapG.
In this collaborative project, the Voelz lab is using ab initio binding simulations of these mini-proteins to understand the binding mechanism, and investigate how sequence variability influences the binding reaction.
RELATED TERMS GLOSSARY AI BETA
Biofilms
Communities of microorganisms that adhere to surfaces.
Biofilms are groups of bacteria or other microorganisms that stick together and create a protective layer around themselves. They can be found in many environments, including inside the human body. Biofilms can be difficult to treat because they are more resistant to antibiotics than individual bacteria.
Bacteria
Single-celled organisms that lack a nucleus.
Bacteria are tiny living things that are found everywhere. Some bacteria are helpful, while others can cause disease. They reproduce quickly and can adapt to different environments.
Antibiotic
A medicine that kills or inhibits the growth of bacteria.
Antibiotics are drugs that are used to treat bacterial infections. They work by killing or stopping the growth of bacteria. Antibiotics are very important for treating serious infections, but overuse can lead to antibiotic resistance.
Pseudomonas fluorescens
A species of bacteria commonly found in soil and water.
Pseudomonas fluorescens is a type of bacteria that can be found in many places. Some strains are beneficial, while others can cause disease in plants and animals.
Lap system
LapsA, LapG, and LapD proteins involved in biofilm formation.
The Lap system is a set of proteins that bacteria use to build biofilms. It involves three main proteins: LapA, which helps the bacteria stick together; LapG, which cuts LapA loose; and LapD, which prevents LapG from cutting LapA.
LapA
Adhesin protein involved in biofilm formation.
LapA is a protein that helps bacteria stick to surfaces. It is part of the Lap system, which is used by bacteria to build biofilms.
LapG
Periplasmic protease involved in biofilm formation.
LapG is a protein that cuts LapA loose. It is part of the Lap system, which is used by bacteria to build biofilms.
LapD
Protein involved in inhibiting LapG activity.
LapD is a protein that prevents LapG from cutting LapA. It is part of the Lap system, which is used by bacteria to build biofilms.
PPI
Protein-protein interaction.
A PPI is when two proteins interact with each other. This can happen in many ways, and it's important for a lot of biological processes.
Mini-proteins
Small proteins designed for specific functions.
Mini-proteins are small versions of proteins that have been designed to do a specific job. They are being developed for many different applications, such as medicine and agriculture.
Ab initio binding simulations
Computer simulations of protein binding interactions.
Ab initio binding simulations are computer programs that can predict how proteins will bind to each other. This can be used to design new drugs and understand how biological processes work.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:29:04|
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 | 6,062,619 | 134,314 | 45.14 | 0 hrs 32 mins |
| 2 | GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 5,922,879 | 134,544 | 44.02 | 0 hrs 33 mins |
| 3 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 5,633,231 | 130,355 | 43.21 | 0 hrs 33 mins |
| 4 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 5,599,269 | 130,815 | 42.80 | 0 hrs 34 mins |
| 5 | GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB] |
Nvidia | GA102 | 5,354,029 | 130,055 | 41.17 | 0 hrs 35 mins |
| 6 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 5,151,239 | 259,765 | 19.83 | 1 hrs 13 mins |
| 7 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,066,147 | 127,841 | 39.63 | 0 hrs 36 mins |
| 8 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 3,990,782 | 117,439 | 33.98 | 0 hrs 42 mins |
| 9 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 3,959,861 | 117,209 | 33.78 | 0 hrs 43 mins |
| 10 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,860,502 | 115,275 | 33.49 | 0 hrs 43 mins |
| 11 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,737,012 | 115,073 | 32.48 | 0 hrs 44 mins |
| 12 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,165,643 | 107,286 | 29.51 | 0 hrs 49 mins |
| 13 | GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q] |
Nvidia | GA104M | 2,740,996 | 104,724 | 26.17 | 0 hrs 55 mins |
| 14 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 2,693,147 | 102,922 | 26.17 | 0 hrs 55 mins |
| 15 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,649,727 | 101,885 | 26.01 | 0 hrs 55 mins |
| 16 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 2,433,839 | 98,661 | 24.67 | 0 hrs 58 mins |
| 17 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 2,368,552 | 98,812 | 23.97 | 1 hrs 0 mins |
| 18 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,897,986 | 91,489 | 20.75 | 1 hrs 9 mins |
| 19 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,885,154 | 91,885 | 20.52 | 1 hrs 10 mins |
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|
|||||||
| 20 | Radeon RX 6900 XT Navi 21 [Radeon RX 6900 XT] |
AMD | Navi 21 | 1,666,902 | 88,511 | 18.83 | 1 hrs 16 mins |
| 21 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,468,111 | 81,794 | 17.95 | 1 hrs 20 mins |
| 22 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,437,840 | 83,947 | 17.13 | 1 hrs 24 mins |
| 23 | Quadro RTX 4000 TU104GL [Quadro RTX 4000] |
Nvidia | TU104GL | 1,400,459 | 83,016 | 16.87 | 1 hrs 25 mins |
| 24 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,379,912 | 82,229 | 16.78 | 1 hrs 26 mins |
| 25 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 1,308,538 | 78,619 | 16.64 | 1 hrs 27 mins |
| 26 | GeForce GTX Titan X GM200 [GeForce GTX Titan X] 6144 |
Nvidia | GM200 | 1,231,807 | 79,668 | 15.46 | 1 hrs 33 mins |
| 27 | Radeon RX 6700/6700 XT/6750 XT / 6800M Navi 22 [Radeon RX 6700/6700 XT/6750 XT / 6800M] |
AMD | Navi 22 | 1,230,385 | 78,925 | 15.59 | 1 hrs 32 mins |
| 28 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,156,820 | 78,233 | 14.79 | 1 hrs 37 mins |
| 29 | Radeon RX 6600/6600 XT/6600M Navi 23 [Radeon RX 6600/6600 XT/6600M] |
AMD | Navi 23 | 1,147,181 | 78,487 | 14.62 | 1 hrs 39 mins |
| 30 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,083,017 | 75,892 | 14.27 | 1 hrs 41 mins |
| 31 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,078,086 | 75,175 | 14.34 | 1 hrs 40 mins |
| 32 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 973,704 | 75,245 | 12.94 | 1 hrs 51 mins |
| 33 | Radeon PRO W6600 Navi 23 WKS-XL [Radeon PRO W6600] |
AMD | Navi 23 WKS-XL | 957,195 | 73,130 | 13.09 | 1 hrs 50 mins |
| 34 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 914,056 | 71,736 | 12.74 | 1 hrs 53 mins |
| 35 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 879,053 | 71,128 | 12.36 | 1 hrs 57 mins |
| 36 | Radeon Pro W5700 Navi 10 [Radeon Pro W5700] |
AMD | Navi 10 | 813,185 | 62,809 | 12.95 | 1 hrs 51 mins |
| 37 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 735,707 | 66,754 | 11.02 | 2 hrs 11 mins |
| 38 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 717,224 | 64,519 | 11.12 | 2 hrs 10 mins |
| 39 | P106-100 GP106 [P106-100] |
Nvidia | GP106 | 708,880 | 66,280 | 10.70 | 2 hrs 15 mins |
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|
|||||||
| 40 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 699,414 | 61,622 | 11.35 | 2 hrs 7 mins |
| 41 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 696,598 | 66,672 | 10.45 | 2 hrs 18 mins |
| 42 | GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER] |
Nvidia | TU116 | 611,707 | 61,935 | 9.88 | 2 hrs 26 mins |
| 43 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 608,147 | 62,407 | 9.74 | 2 hrs 28 mins |
| 44 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 519,266 | 59,783 | 8.69 | 2 hrs 46 mins |
| 45 | Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT] |
AMD | Navi 10 | 400,849 | 42,453 | 9.44 | 2 hrs 33 mins |
| 46 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 342,598 | 52,087 | 6.58 | 3 hrs 39 mins |
| 47 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 328,849 | 50,991 | 6.45 | 3 hrs 43 mins |
| 48 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 320,040 | 50,871 | 6.29 | 3 hrs 49 mins |
| 49 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 306,432 | 50,019 | 6.13 | 3 hrs 55 mins |
| 50 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 168,348 | 41,036 | 4.10 | 5 hrs 51 mins |
| 51 | Radeon RX Vega M XL [Radeon RX Vega M XL] |
AMD | Vega | 143,192 | 39,024 | 3.67 | 6 hrs 32 mins |
| 52 | Quadro P620 GP107GL [Quadro P620] |
Nvidia | GP107GL | 120,518 | 37,361 | 3.23 | 7 hrs 26 mins |
| 53 | GeForce GT 1030 GP108 [GeForce GT 1030] |
Nvidia | GP108 | 110,601 | 35,730 | 3.10 | 7 hrs 45 mins |
| 54 | GeForce GTX 750 Ti GM107 [GeForce GTX 750 Ti] 1389 |
Nvidia | GM107 | 101,428 | 37,488 | 2.71 | 8 hrs 52 mins |
| 55 | Quadro K2200 GM107GL [Quadro K2200] |
Nvidia | GM107GL | 82,330 | 33,108 | 2.49 | 9 hrs 39 mins |
| 56 | Quadro K620 GM107GL [Quadro K620] |
Nvidia | GM107GL | 64,984 | 27,579 | 2.36 | 10 hrs 11 mins |
| 57 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 58,754 | 28,984 | 2.03 | 11 hrs 50 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:29:04|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|