RESEARCH: ENZYME-DYNAMICS
FOLDING PROJECT #15412 PROFILE
PROJECT TEAM
Manager(s): Adrija DuttaInstitution: UIUC
WORK UNIT INFO
Atoms: 53,778Core: 0x24
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project uses computer simulations to see how enzymes change shape. By understanding how these changes affect how enzymes bind to other molecules, we can learn more about how they work and develop new drugs.
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
Large biomolecules essential for various biological functions.
Proteins are the building blocks of life. They perform a wide range of functions, from catalyzing biochemical reactions to transporting molecules within cells. Understanding protein structure and function is crucial for advancements in medicine, agriculture, and other fields.
Molecular
Relating to molecules or their interactions.
Molecular refers to the level of study dealing with individual molecules and their behavior. This is essential in understanding biological processes as complex interactions between molecules drive cellular functions.
Recognition
The ability to identify and bind specifically to a target molecule.
Recognition is the process by which molecules interact and bind to each other in a specific manner. This is crucial for many biological processes, such as enzyme catalysis, signal transduction, and immune responses.
Enzymes
Biological catalysts that speed up chemical reactions.
Enzymes are proteins that act as catalysts, accelerating biochemical reactions within cells. They are essential for various metabolic processes, including digestion, energy production, and DNA replication.
Ligand
A molecule that binds to a receptor or enzyme.
Ligands are molecules that bind to specific targets in the body, such as receptors or enzymes. This binding can trigger various biological responses, making ligands important for drug development and understanding how drugs work.
Drug
A substance used to treat or prevent disease.
Drugs are chemical compounds that interact with biological systems to produce a desired effect. They are used to treat a wide range of diseases and conditions, from infections to chronic illnesses.
Binding
The process of molecules attaching to each other.
Binding describes the interaction between molecules, where they attach to each other through various forces. This is a fundamental process in biology, enabling molecules to recognize and interact with each other.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:31:37|
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 | 22,645,977 | 18,286 | 1238.43 | 0 hrs 1 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 16,775,323 | 18,286 | 917.39 | 0 hrs 2 mins |
| 3 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 5,250,959 | 18,286 | 287.16 | 0 hrs 5 mins |
| 4 | Radeon RX 9070(XT) Navi 48 [Radeon RX 9070(XT)] |
AMD | Navi 48 | 4,720,329 | 18,286 | 258.14 | 0 hrs 6 mins |
| 5 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 3,063,043 | 18,286 | 167.51 | 0 hrs 9 mins |
| 6 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,666,979 | 18,286 | 145.85 | 0 hrs 10 mins |
| 7 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,078,635 | 85,136 | 24.42 | 0 hrs 59 mins |
| 8 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,633,479 | 93,571 | 17.46 | 1 hrs 22 mins |
| 9 | Radeon RX 9060(XT) Navi 44 [Radeon RX 9060(XT)] |
AMD | Navi 44 | 1,494,326 | 18,286 | 81.72 | 0 hrs 18 mins |
| 10 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,426,742 | 89,090 | 16.01 | 1 hrs 30 mins |
| 11 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,324,532 | 18,286 | 72.43 | 0 hrs 20 mins |
| 12 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 249,109 | 49,570 | 5.03 | 4 hrs 47 mins |
| 13 | GeForce GTX 1070 Mobile GP104BM [GeForce GTX 1070 Mobile] 6463 |
Nvidia | GP104BM | 240,030 | 18,286 | 13.13 | 1 hrs 50 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:31:37|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|