RESEARCH: ENZYME-DYNAMICS
FOLDING PROJECT #15420 PROFILE
PROJECT TEAM
Manager(s): Adrija DuttaInstitution: UIUC
WORK UNIT INFO
Atoms: 263,915Core: 0x24
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
The project relates to studying how enzymes change shape to bind with other molecules. Using computer simulations, we're looking at the flexibility of enzymes' active sites to see how this affects their ability to interact with different substances. This could help us design better drugs and understand how enzymes work.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Protein function is closely linked to its dynamic structural behavior, particularly in regions involved in molecular recognition.
Using large-scale molecular dynamics simulations, we are studying intrinsic conformational variability across a diverse set of enzymes.
By analyzing binding pocket flexibility, structural rearrangements, and transient conformations, we aim to understand how active-site dynamics influence ligand binding.
These insights can support advances in drug discovery, enzyme engineering, and a deeper understanding of protein function.
RELATED TERMS GLOSSARY AI BETA
Protein
A large biomolecule composed of amino acids.
Proteins are essential building blocks of living organisms. They perform a wide range of functions, including catalyzing biochemical reactions, transporting molecules, providing structural support, and regulating cellular processes. Understanding protein structure and function is crucial for advancements in medicine, agriculture, and biotechnology.
Molecular Dynamics
A computational method for simulating the movement of atoms and molecules over time.
Molecular dynamics simulations are used to study the behavior of biomolecules at the atomic level. They allow researchers to investigate protein folding, ligand binding, and other dynamic processes that are difficult to observe experimentally.
Enzyme
A biological catalyst that speeds up chemical reactions.
Enzymes are essential proteins that play a critical role in virtually all biological processes. They accelerate biochemical reactions by lowering the activation energy required for the reaction to occur. Understanding enzyme function is crucial for developing new drugs and therapies.
Ligand
A molecule that binds to a protein or receptor.
Ligands are molecules that interact with proteins, such as enzymes and receptors. They can bind to specific sites on proteins, triggering various biological responses. Understanding ligand-protein interactions is essential for developing new drugs and therapies.
Drug Discovery
The process of identifying and developing new drugs.
Drug discovery is a complex and time-consuming process that involves identifying potential drug candidates, testing their efficacy and safety, and ultimately bringing them to market. Advances in biotechnology, such as molecular modeling and high-throughput screening, have significantly accelerated the drug discovery process.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:31:33|
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 5080 GB203 [GeForce RTX 5080] |
Nvidia | GB203 | 77,254,697 | 205,931 | 375.15 | 0 hrs 4 mins |
| 2 | GeForce RTX 5090 GB202 [GeForce RTX 5090] |
Nvidia | GB202 | 34,362,758 | 205,931 | 166.87 | 0 hrs 9 mins |
| 3 | GeForce RTX 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 19,729,418 | 205,931 | 95.81 | 0 hrs 15 mins |
| 4 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 19,459,495 | 367,504 | 52.95 | 0 hrs 27 mins |
| 5 | GeForce RTX 4080 SUPER AD103 [GeForce RTX 4080 SUPER] |
Nvidia | AD103 | 17,418,182 | 920,547 | 18.92 | 1 hrs 16 mins |
| 6 | GeForce RTX 5070 Ti GB203 [GeForce RTX 5070 Ti] |
Nvidia | GB203 | 17,337,116 | 205,931 | 84.19 | 0 hrs 17 mins |
| 7 | GeForce RTX 4070 Ti SUPER AD103 [GeForce RTX 4070 Ti SUPER] |
Nvidia | AD103 | 14,421,030 | 205,931 | 70.03 | 0 hrs 21 mins |
| 8 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 12,904,069 | 450,317 | 28.66 | 0 hrs 50 mins |
| 9 | GeForce RTX 4070 SUPER AD104 [GeForce RTX 4070 SUPER] |
Nvidia | AD104 | 11,815,353 | 399,234 | 29.60 | 0 hrs 49 mins |
| 10 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 6,320,472 | 205,931 | 30.69 | 0 hrs 47 mins |
| 11 | GeForce RTX 5060 GB206 [GeForce RTX 5060] |
Nvidia | GB206 | 6,024,074 | 205,931 | 29.25 | 0 hrs 49 mins |
| 12 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 5,803,701 | 205,931 | 28.18 | 0 hrs 51 mins |
| 13 | Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE] |
AMD | Navi 31 | 5,033,021 | 205,931 | 24.44 | 0 hrs 59 mins |
| 14 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 4,906,193 | 205,931 | 23.82 | 1 hrs 0 mins |
| 15 | GeForce RTX 5060 Ti GB206 [GeForce RTX 5060 Ti] |
Nvidia | GB206 | 4,714,714 | 205,931 | 22.89 | 1 hrs 3 mins |
| 16 | Radeon RX 9070(XT) Navi 48 [Radeon RX 9070(XT)] |
AMD | Navi 48 | 4,643,540 | 205,931 | 22.55 | 1 hrs 4 mins |
| 17 | RTX 4000 SFF Ada Generation AD104GL [RTX 4000 SFF Ada Generation] |
Nvidia | AD104GL | 4,545,917 | 205,931 | 22.07 | 1 hrs 5 mins |
| 18 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,457,857 | 205,931 | 21.65 | 1 hrs 7 mins |
| 19 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 3,429,972 | 205,931 | 16.66 | 1 hrs 26 mins |
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| 20 | GeForce RTX 4070 AD104 [GeForce RTX 4070] |
Nvidia | AD104 | 3,400,342 | 596,975 | 5.70 | 4 hrs 13 mins |
| 21 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,092,303 | 205,931 | 15.02 | 1 hrs 36 mins |
| 22 | Radeon RX 6700(XT)/6800M Navi 22 XT-XL [Radeon RX 6700(XT)/6800M] |
AMD | Navi 22 XT-XL | 2,456,436 | 205,931 | 11.93 | 2 hrs 1 mins |
| 23 | Radeon RX 9060(XT) Navi 44 [Radeon RX 9060(XT)] |
AMD | Navi 44 | 2,299,401 | 205,931 | 11.17 | 2 hrs 9 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:31:33|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|