RESEARCH: CANCER
FOLDING PROJECT #16986 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 23,400
Core: 0xa8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project relates to studying how tiny protein structures called alpha-helical hairpins fold and what makes them stable. By changing these structures, we hope to design better 'affibody' drugs that can target and fight cancer.

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 protein structure characterized by alpha-helices forming a hairpin shape.

Scientific: Pharmaceuticals
Biotechnology / Protein Structure

Alpha-helical hairpins are a common structural motif in proteins. They consist of two alpha-helices connected by a loop region, creating a hairpin-like shape. This structure is important for various protein functions, including binding to other molecules and mediating interactions within cells.


disulfide cross-linkers

Covalent bonds formed between sulfur atoms in cysteine amino acids within a protein.

Technical: Pharmaceuticals
Biotechnology / Protein Chemistry

Disulfide cross-linkers are covalent bonds that form between two sulfur atoms in cysteine amino acids. These bonds play a crucial role in stabilizing the structure of proteins and influencing their function. They can be important for proper folding and maintaining the shape of proteins, especially in challenging environments.


sequence variants

Alterations in the DNA sequence of a gene that can result in changes to the protein it encodes.

Scientific: Pharmaceuticals
Biotechnology / Genetic Engineering

Sequence variants are variations in the DNA code that can lead to differences in the amino acid sequence of proteins. These changes can have a range of effects, from subtle alterations in protein function to complete loss of function. Studying sequence variants is essential for understanding genetic diseases and developing new therapies.


molecular simulation methods

Computer-based techniques used to model and predict the behavior of molecules.

Technical: Pharmaceuticals, Academia
Biotechnology / Computational Biology

Molecular simulation methods use algorithms to simulate the movements and interactions of atoms and molecules. These simulations can be used to study a wide range of biological processes, such as protein folding, drug binding, and enzyme catalysis. They are valuable tools for understanding complex systems at the molecular level.


protein binder scaffolds

Structural frameworks designed to bind specifically to target proteins.

Scientific: Pharmaceuticals
Biotechnology / Drug Discovery

Protein binder scaffolds are engineered protein structures that serve as templates for binding to specific target proteins. These scaffolds can be used in the development of new drugs by targeting and inhibiting disease-causing proteins or delivering therapeutic molecules to specific cells.


affibody

A small protein domain that binds with high affinity and specificity to a target.

Acronym: Pharmaceuticals
Biotechnology / Drug Discovery

Affibody is a type of engineered protein that exhibits high binding affinity for specific targets. It is derived from the Z domain of Protein A and has been extensively studied for its potential in drug development. Affibody molecules can be used as therapeutic agents, diagnostic tools, and research reagents.


cancer therapeutics

Medical treatments designed to combat cancer.

Scientific: Pharmaceuticals
Biotechnology / Oncology

Cancer therapeutics encompass a broad range of medical interventions aimed at treating and managing cancer. These include surgery, radiation therapy, chemotherapy, immunotherapy, and targeted therapies. The goal of cancer therapeutics is to eliminate or control cancer cells while minimizing harm to healthy tissues.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 00:42:12
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 00:42:12
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 9 7950X 16-CORE 32 47,567 1,522,144 AMD
2 RYZEN 9 3950X 16-CORE 32 26,048 833,536 AMD
3 RYZEN 7 7700X 8-CORE 16 38,407 614,512 AMD
4 RYZEN 7 5800X 8-CORE 16 38,209 611,344 AMD
5 RYZEN 7 7800X3D 8-CORE 16 36,505 584,080 AMD
6 12TH GEN CORE I7-12700K 20 27,281 545,620 Intel
7 RYZEN 9 5950X 16-CORE 32 15,916 509,312 AMD
8 RYZEN 7 5800X3D 8-CORE 16 30,960 495,360 AMD
9 RYZEN 7 5700G 16 30,492 487,872 AMD
10 12TH GEN CORE I9-12900K 24 20,042 481,008 Intel
11 RYZEN 9 3900 12-CORE 24 19,524 468,576 AMD
12 RYZEN 7 5700X 8-CORE 16 23,974 383,584 AMD
13 RYZEN 7 3800X 8-CORE 16 20,575 329,200 AMD
14 RYZEN 5 5600 6-CORE 12 26,023 312,276 AMD
15 RYZEN 9 5900X 12-CORE 24 12,864 308,736 AMD
16 CORE I9-10900X CPU @ 3.70GHZ 20 15,072 301,440 Intel
17 CORE I9-10850K CPU @ 3.60GHZ 20 14,187 283,740 Intel
18 12TH GEN CORE I5-12600K 16 17,619 281,904 Intel
19 RYZEN 9 5900 12-CORE 24 10,572 253,728 AMD
20 RYZEN 9 3900X 12-CORE 24 10,429 250,296 AMD
21 RYZEN 5 5600G 12 19,933 239,196 AMD
22 CORE I7-8700 CPU @ 3.20GHZ 12 19,464 233,568 Intel
23 XEON CPU E5-2680 V3 @ 2.50GHZ 24 9,729 233,496 Intel
24 RYZEN THREADRIPPER 3960X 24-CORE 48 4,592 220,416 AMD
25 CORE I7-9700K CPU @ 3.60GHZ 8 27,429 219,432 Intel
26 RYZEN 5 5600X 6-CORE 12 18,199 218,388 AMD
27 RYZEN 5 3500 6-CORE 6 31,659 189,954 AMD
28 XEON CPU E5-2690 V4 @ 2.60GHZ 28 6,727 188,356 Intel
29 CORE I9-9900K CPU @ 3.60GHZ 16 10,762 172,192 Intel
30 CORE I5-10400 CPU @ 2.90GHZ 12 14,171 170,052 Intel
31 CORE I7-10700 CPU @ 2.90GHZ 16 10,606 169,696 Intel
32 RYZEN 5 3600 6-CORE 12 13,944 167,328 AMD
33 RYZEN 7 2700X EIGHT-CORE 16 10,032 160,512 AMD
34 APPLE M1 MAX 10 15,804 158,040 Apple
35 RYZEN 7 PRO 4750G 16 9,164 146,624 AMD
36 XEON CPU E5-2698 V4 @ 2.20GHZ 16 8,009 128,144 Intel
37 CORE I7-5930K CPU @ 3.50GHZ 12 10,377 124,524 Intel
38 CORE I7-9750H CPU @ 2.60GHZ 12 9,040 108,480 Intel
39 RYZEN 7 5800HS 16 6,248 99,968 AMD
40 RYZEN 7 3700X 8-CORE 16 5,829 93,264 AMD
41 CORE I7-6700K CPU @ 4.00GHZ 8 11,486 91,888 Intel
42 CORE I7-10700T CPU @ 2.00GHZ 16 5,647 90,352 Intel
43 CORE I7-8705G CPU @ 3.10GHZ 8 11,161 89,288 Intel
44 RYZEN THREADRIPPER 2950X 16-CORE 32 2,693 86,176 AMD
45 CORE I7-8700K CPU @ 3.70GHZ 12 7,010 84,120 Intel
46 CORE I9-8950HK CPU @ 2.90GHZ 12 6,812 81,744 Intel
47 11TH GEN CORE I5-11400 @ 2.60GHZ 12 6,338 76,056 Intel
48 EPYC 7251 8-CORE 16 4,683 74,928 AMD
49 XEON CPU X5660 @ 2.80GHZ 24 2,956 70,944 Intel
50 CORE I5-10500T CPU @ 2.30GHZ 12 5,569 66,828 Intel
51 XEON CPU E5-2650 0 @ 2.00GHZ 16 3,931 62,896 Intel
52 CORE I7-4770HQ CPU @ 2.20GHZ 8 7,533 60,264 Intel
53 XEON CPU E3-1245 V3 @ 3.40GHZ 8 7,280 58,240 Intel
54 XEON CPU E5-2620 0 @ 2.00GHZ 12 4,554 54,648 Intel
55 CORE I7-3770 CPU @ 3.40GHZ 8 6,779 54,232 Intel
56 XEON CPU L5640 @ 2.27GHZ 24 2,187 52,488 Intel
57 CORE I7-5820K CPU @ 3.30GHZ 12 4,368 52,416 Intel
58 XEON CPU E3-1240 V2 @ 3.40GHZ 8 6,463 51,704 Intel
59 APPLE M1 PRO 10 4,699 46,990 Apple
60 11TH GEN CORE I5-1145G7 @ 2.60GHZ 8 5,776 46,208 Intel
61 CORE I5-8259U CPU @ 2.30GHZ 8 5,761 46,088 Intel
62 XEON CPU E5-2697 V2 @ 2.70GHZ 24 1,385 33,240 Intel
63 RYZEN 7 3750H 8 3,913 31,304 AMD
64 12TH GEN CORE I5-12600KF 16 1,571 25,136 Intel
65 CORE I7-2760QM CPU @ 2.40GHZ 8 2,797 22,376 Intel
66 RYZEN 7 3700U 8 2,471 19,768 AMD