RESEARCH: PEPTIDE-CONFORMATION-MODELING
FOLDING PROJECT #12105 PROFILE

PROJECT TEAM

Manager(s): Hassan Nadeem
Institution: University of Illinois at Urbana-Champaign

WORK UNIT INFO

Atoms: 41,000
Core: 0x22
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project explores the different shapes short peptides can take. By using computer models and machine learning, we can understand how these shapes affect their function. This knowledge can then be used to design new peptides for things like innovative materials.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

Peptide Conformations Short peptides can be used to observe possible conformations, which are important factors for determining their function.

Insights from these simulations can then be further extended to larger peptides.

In this study, we aim to explore the conformational space of all possible short peptides and using modeling techniques like machine learning to gain insights.

These can then be used for rational design of peptides for applications in biologically-inspired materials.

RELATED TERMS GLOSSARY AI BETA

Note: Glossary items are a high level summary and may not be 100% accurate.

Peptide

A short chain of amino acids linked together.

Scientific: Biomedicine
Biotechnology / Protein Chemistry

Peptides are essential building blocks in proteins. They are chains of amino acids that play diverse roles in biological processes. Understanding peptide structure and function is crucial for developing new drugs, materials, and diagnostics.


Conformations

The different 3-dimensional shapes that a molecule can take.

Scientific: Biomedicine
Biotechnology / Structural Biology

Conformations describe the various spatial arrangements of atoms within a molecule. For peptides, understanding their conformations is critical because shape dictates their function. Different conformations can lead to different interactions with other molecules.


Simulations

Computer models used to imitate complex systems.

Scientific: Biomedicine
Biotechnology / Computational Biology

Simulations are powerful tools in biotechnology to study biological processes. They allow researchers to model and predict how molecules interact and change over time without needing to perform expensive or time-consuming experiments.


Machine Learning

A type of artificial intelligence that allows computers to learn from data.

Scientific: Biomedicine
Biotechnology / Artificial Intelligence

Machine learning is revolutionizing biotechnology by enabling the analysis of vast datasets. Algorithms can identify patterns and make predictions, accelerating drug discovery, personalized medicine, and other applications.


Rational Design

The process of designing molecules with specific properties.

Scientific: Pharmaceuticals
Biotechnology / Drug Discovery

Rational design uses knowledge of molecular structure and function to create new molecules with desired effects. In drug discovery, it aims to develop safer and more effective medications.


Biologically-inspired Materials

Materials that are designed based on biological principles.

Scientific: Manufacturing
Materials Science / Biomimicry

Biologically-inspired materials draw inspiration from nature's designs to create innovative and sustainable products. They can possess properties like self-healing, strength, or adaptability found in living organisms.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:35:52
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 3,172,521 406,173 7.81 3 hrs 4 mins
2 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,628,631 376,214 6.99 3 hrs 26 mins
3 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 2,237,841 354,796 6.31 3 hrs 48 mins
4 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,982,259 347,605 5.70 4 hrs 13 mins
5 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,689,615 331,351 5.10 4 hrs 42 mins
6 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,448,430 309,256 4.68 5 hrs 7 mins
7 P102-100
GP102 [P102-100]
Nvidia GP102 1,356,068 297,492 4.56 5 hrs 16 mins
8 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,321,090 301,072 4.39 5 hrs 28 mins
9 P104-100
GP104 [P104-100]
Nvidia GP104 1,315,194 302,603 4.35 5 hrs 31 mins
10 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,302,360 297,857 4.37 5 hrs 29 mins
11 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,191,216 303,667 3.92 6 hrs 7 mins
12 Tesla P4
GP104GL [Tesla P4] 5704
Nvidia GP104GL 1,159,667 303,833 3.82 6 hrs 17 mins
13 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 884,179 265,837 3.33 7 hrs 13 mins
14 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 878,539 264,902 3.32 7 hrs 14 mins
15 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 869,242 254,673 3.41 7 hrs 2 mins
16 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 733,503 235,484 3.11 7 hrs 42 mins
17 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 646,525 222,373 2.91 8 hrs 15 mins
18 GeForce GTX 1650
TU116 [GeForce GTX 1650] 3091
Nvidia TU116 581,277 238,156 2.44 9 hrs 50 mins
19 GeForce GTX 1060 Mobile
GP106M [GeForce GTX 1060 Mobile]
Nvidia GP106M 498,335 142,988 3.49 6 hrs 53 mins
20 Quadro T1000 Mobile
TU117GLM [Quadro T1000 Mobile]
Nvidia TU117GLM 449,377 211,621 2.12 11 hrs 18 mins
21 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 323,989 187,405 1.73 13 hrs 53 mins
22 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 312,453 209,306 1.49 16 hrs 5 mins
23 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 234,501 170,728 1.37 17 hrs 28 mins
24 RX 5500/5500M/Pro 5500M
Navi 14 [RX 5500/5500M/Pro 5500M]
AMD Navi 14 181,338 145,827 1.24 19 hrs 18 mins
25 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 102,992 120,663 0.85 28 hrs 7 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:35:52
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make