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Research: PEPTIDE-CONFORMATION-MODELING Folding Project #12106

Project #12106 overview

Project Summary AI Beta

This project relates to studying how small protein pieces (peptides) fold into different shapes. By using computer models and learning from these shapes, scientists hope to design new peptides for use in things like special materials inspired by nature.
Automated summary; simplified and may not be fully accurate.

Project team

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

Work unit

Atoms
3,500
Core
0x22
Status
Beta
Source material

Official 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.

Performance data

Hardware Performance for Project 12106

Compare community-sampled Folding@Home output for the GPUs and CPUs processing this project.

Data as of Sunday, 02 August 2026 22:11:57

GPU PPD Averages

Rank
Project 		Model Name
Folding@Home Identifier 		Make
Brand 		GPU
Model 		PPD
Average 		Points WU
Average 		WUs Day
Average 		WU Time
Average
1 Radeon 660M-680M
Rembrandt [Radeon 660M-680M]		 AMD Rembrandt 1,063,320 39,312 27.05 0 hrs 53 mins