RESEARCH: CANCER
FOLDING PROJECT #16966 PROFILE

PROJECT TEAM

Manager(s): Prof. Vincent Voelz
Institution: Temple University

WORK UNIT INFO

Atoms: 23,400
Core: GRO_A8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project relates to studying how tiny protein building blocks fold into specific shapes. We want to see how changes in the proteins' makeup affect their folding, hoping to learn how to design better 'affibody' drugs that can target cancer cells.

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

OFFICAL PROJECT DESCRIPTION

These simulations are designed to test our understanding the folding mechanism of alpha-helical hairpins.

We are trying to study how disulfide cross-linkers and sequence variants affect the folding thermodynamics and kinetics of these proteins, to learn how we might better use molecular simulation methods to design effective protein binder scaffolds, for use as "affibody" cancer therapeutics, for example.

RELATED TERMS GLOSSARY AI BETA

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

alpha-helical

A type of secondary protein structure characterized by a helix formed by hydrogen bonding between amino acids.

Technical: Biomedicine
Biotechnology / Protein Structure

Alpha-helices are common structural motifs in proteins. They form a spiral shape due to hydrogen bonds between the backbone atoms of amino acids. This shape is important for protein stability and function.


disulfide cross-linkers

Covalent bonds between sulfur atoms in cysteine amino acids, contributing to protein stability and folding.

Technical: Pharmaceuticals
Biotechnology / Protein Structure

Disulfide cross-linkers are strong covalent bonds that can form between two cysteine amino acids in a protein. These bonds help stabilize the protein's three-dimensional structure and can influence its function.


sequence variants

Alterations in the DNA sequence of a gene that can result in changes to protein structure and function.

Technical: Biomedicine
Biotechnology / Genetic Engineering

Sequence variants are variations in the order of nucleotides within a gene. These changes can lead to altered amino acid sequences in the resulting protein, potentially affecting its properties and function.


molecular simulation

Computer-based models that mimic the behavior of molecules and biological systems.

Technical: Bioinformatics
Biotechnology / Computational Biology

Molecular simulations use computer algorithms to simulate the movement and interactions of atoms and molecules. This allows researchers to study complex biological processes and design new drugs or materials.


affibody

Affibody- Engineered protein binding domain derived from bacterial cell surface proteins.

Technical: Pharmaceuticals
Biotechnology / Protein Engineering

Affibodys are small engineered proteins with high affinity for specific targets. They have potential applications in diagnostics and therapeutics, such as delivering drugs to cancer cells.


cancer therapeutics

Medications or treatments designed to prevent, control, or cure cancer.

Technical: Pharmaceuticals
Biotechnology / Oncology

Cancer therapeutics aim to eliminate or inhibit the growth of cancerous cells. This can involve various approaches, such as chemotherapy, radiation therapy, and targeted therapies.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:42:29
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:42:29
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 9 3950X 16-CORE 32 27,790 889,280 AMD
2 RYZEN 9 5950X 16-CORE 32 14,160 453,120 AMD
3 RYZEN 9 5900X 12-CORE 24 17,203 412,872 AMD
4 RYZEN 7 5800X 8-CORE 16 22,079 353,264 AMD
5 RYZEN 9 3900 12-CORE 24 12,886 309,264 AMD
6 XEON CPU E5-2680 V3 @ 2.50GHZ 24 11,967 287,208 Intel
7 RYZEN 9 3900X 12-CORE 24 10,552 253,248 AMD
8 11TH GEN CORE I7-11700K @ 3.60GHZ 16 15,141 242,256 Intel
9 RYZEN THREADRIPPER 3960X 24-CORE 48 4,822 231,456 AMD
10 XEON CPU E5-2690 V4 @ 2.60GHZ 28 8,060 225,680 Intel
11 RYZEN 5 5600X 6-CORE 12 17,976 215,712 AMD
12 RYZEN 7 3700X 8-CORE 16 12,893 206,288 AMD
13 11TH GEN CORE I9-11900K @ 3.50GHZ 16 12,729 203,664 Intel
14 RYZEN 9 3900XT 12-CORE 24 8,008 192,192 AMD
15 RYZEN 7 3800X 8-CORE 16 11,531 184,496 AMD
16 CORE I7-9700K CPU @ 3.60GHZ 8 22,030 176,240 Intel
17 CORE I7-10700K CPU @ 3.80GHZ 16 10,727 171,632 Intel
18 CORE I7-8700 CPU @ 3.20GHZ 12 13,626 163,512 Intel
19 CORE I9-10900X CPU @ 3.70GHZ 20 7,997 159,940 Intel
20 CORE I5-10400F CPU @ 2.90GHZ 12 11,945 143,340 Intel
21 RYZEN 5 3600 6-CORE 12 11,100 133,200 AMD
22 RYZEN 7 2700X EIGHT-CORE 16 7,555 120,880 AMD
23 RYZEN THREADRIPPER 1920X 12-CORE 24 4,910 117,840 AMD
24 EPYC 7571 32-CORE 64 1,644 105,216 AMD
25 CORE I7-6700K CPU @ 4.00GHZ 8 12,608 100,864 Intel
26 RYZEN 5 2600 SIX-CORE 12 6,250 75,000 AMD
27 CORE I5-8300H CPU @ 2.30GHZ 8 7,784 62,272 Intel
28 RYZEN 7 4700U 8 7,343 58,744 AMD
29 11TH GEN CORE I5-1135G7 @ 2.40GHZ 8 7,186 57,488 Intel
30 CORE I7-3840QM CPU @ 2.80GHZ 8 7,029 56,232 Intel
31 CORE I5-9300H CPU @ 2.40GHZ 8 6,488 51,904 Intel
32 CORE I7-8550U CPU @ 1.80GHZ 8 5,684 45,472 Intel
33 CORE I7-4790T CPU @ 2.70GHZ 8 3,554 28,432 Intel
34 CORE I7-3610QM CPU @ 2.30GHZ 8 3,075 24,600 Intel
35 FX-8320 EIGHT-CORE 8 1,784 14,272 AMD