RESEARCH: CANCER
FOLDING PROJECT #16964 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 uses computer simulations to understand how tiny proteins fold into shapes. They're looking at how chemical bonds and slight changes in the protein's code affect how it folds. The goal is to learn how to design these proteins as drugs, like 'affibody' cancer treatments.

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 hairpins

A type of secondary protein structure characterized by a helix shape.

Scientific: Biotechnology
Biotechnology / Protein Structure

Alpha-helical hairpins are common structural motifs in proteins. They consist of short alpha helices connected by turns or loops, forming hairpin shapes. These structures are important for protein function and stability.


disulfide cross-linkers

Covalent bonds formed between two cysteine amino acids in a protein.

Technical: Biotechnology
Biotechnology / Protein Chemistry

Disulfide cross-linkers are covalent bonds that form between sulfur atoms in cysteine amino acids within proteins. These bonds contribute to protein stability and folding by creating strong links between different parts of the molecule.


sequence variants

Variations in the order of nucleotides in a DNA sequence.

Scientific: Biotechnology
Biotechnology / Genetics

Sequence variants are changes in the DNA code that can result in different amino acid sequences in proteins. These variations can have diverse effects on protein function and contribute to genetic diversity.


protein binder scaffolds

Structural frameworks that bind to specific proteins.

Technical: Biotechnology
Biotechnology / Drug Discovery

Protein binder scaffolds are designed to bind specifically to target proteins. They can be used as tools for studying protein function or as therapeutic agents to block or modulate protein activity.


affibody

A synthetic protein based on the Z domain of protein A.

Acronym: Biotechnology
Biotechnology / Drug Discovery

Affibody is a type of engineered protein that binds to specific targets with high affinity. It consists of a small domain derived from protein A and has applications in drug development, diagnostics, and imaging.


cancer therapeutics

Medications used to treat cancer.

Technical: Pharmaceutical
Biotechnology / Oncology

Cancer therapeutics encompass a wide range of treatments aimed at combating cancer cells. These include chemotherapy, radiation therapy, immunotherapy, and targeted therapies.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:42:32
Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
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PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 00:42:32
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 31,969 1,023,008 AMD
2 RYZEN 9 5950X 16-CORE 32 24,390 780,480 AMD
3 RYZEN 7 5800X 8-CORE 16 25,306 404,896 AMD
4 RYZEN 9 3900XT 12-CORE 24 15,500 372,000 AMD
5 RYZEN THREADRIPPER 2970WX 24-CORE 48 7,749 371,952 AMD
6 RYZEN 9 3900 12-CORE 24 13,993 335,832 AMD
7 RYZEN 9 5900X 12-CORE 24 13,918 334,032 AMD
8 CORE I9-10900KF CPU @ 3.70GHZ 20 15,447 308,940 Intel
9 CORE I7-10875H CPU @ 2.30GHZ 16 18,017 288,272 Intel
10 XEON CPU E5-2690 V4 @ 2.60GHZ 28 10,059 281,652 Intel
11 RYZEN THREADRIPPER 3960X 24-CORE 48 5,770 276,960 AMD
12 11TH GEN CORE I9-11900K @ 3.50GHZ 16 17,208 275,328 Intel
13 RYZEN 5 5600X 6-CORE 12 22,033 264,396 AMD
14 11TH GEN CORE I7-11700K @ 3.60GHZ 16 16,262 260,192 Intel
15 XEON CPU E5-2680 V4 @ 2.40GHZ 28 8,996 251,888 Intel
16 CORE I9-10900X CPU @ 3.70GHZ 20 12,213 244,260 Intel
17 RYZEN 7 3700X 8-CORE 16 13,796 220,736 AMD
18 RYZEN 7 3800X 8-CORE 16 13,444 215,104 AMD
19 CORE I7-10700K CPU @ 3.80GHZ 16 11,787 188,592 Intel
20 11TH GEN CORE I9-11900F @ 2.50GHZ 16 11,161 178,576 Intel
21 RYZEN 5 3600 6-CORE 12 14,363 172,356 AMD
22 CORE I7-8700 CPU @ 3.20GHZ 12 13,667 164,004 Intel
23 RYZEN 9 4900HS 16 9,902 158,432 AMD
24 XEON CPU E5-2680 V3 @ 2.50GHZ 24 6,576 157,824 Intel
25 RYZEN 7 2700X EIGHT-CORE 16 9,594 153,504 AMD
26 CORE I5-10400 CPU @ 2.90GHZ 12 11,725 140,700 Intel
27 XEON CPU E5-2690 V2 @ 3.00GHZ 20 6,859 137,180 Intel
28 CORE I7-10870H CPU @ 2.20GHZ 16 8,445 135,120 Intel
29 RYZEN THREADRIPPER 1920X 12-CORE 24 5,200 124,800 AMD
30 CORE I7-9700T CPU @ 2.00GHZ 8 14,167 113,336 Intel
31 CORE I7-6700K CPU @ 4.00GHZ 8 13,911 111,288 Intel
32 CORE I3-9100F CPU @ 3.60GHZ 4 27,208 108,832 Intel
33 CORE I5-10400F CPU @ 2.90GHZ 12 9,006 108,072 Intel
34 RYZEN 5 2600 SIX-CORE 12 7,732 92,784 AMD
35 11TH GEN CORE I5-11400 @ 2.60GHZ 12 6,620 79,440 Intel
36 CORE I5-10300H CPU @ 2.50GHZ 8 9,521 76,168 Intel
37 XEON W-10855M CPU @ 2.80GHZ 12 5,927 71,124 Intel
38 11TH GEN CORE I5-1135G7 @ 2.40GHZ 8 7,990 63,920 Intel
39 CORE I5-8300H CPU @ 2.30GHZ 8 6,937 55,496 Intel
40 CORE I7-4790T CPU @ 2.70GHZ 8 6,553 52,424 Intel
41 CORE I5-8250U CPU @ 1.60GHZ 8 6,483 51,864 Intel
42 XEON CPU X5670 @ 2.93GHZ 12 4,220 50,640 Intel
43 CORE I7-8550U CPU @ 1.80GHZ 8 6,189 49,512 Intel
44 CORE I5-8600K CPU @ 3.60GHZ 6 7,465 44,790 Intel
45 PHENOM II X6 1090T 6 4,770 28,620 AMD
46 CORE I7-3610QM CPU @ 2.30GHZ 8 3,154 25,232 Intel
47 RYZEN 5 3500U 8 2,755 22,040 AMD