RESEARCH: CANCER
FOLDING PROJECT #18413 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 64,500
Core: 0xa8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project uses computer simulations to predict how changes to a mini-protein's design can improve its ability to bind to a bacterial enzyme. By making these predictions, scientists hope to develop new antibiotics that are more effective at fighting bacterial infections.

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

OFFICAL PROJECT DESCRIPTION

Can molecular simulation be used for virtual affinity-maturation of de novo designed protein binders? That’s the question this project aims to address.

The Bahl Lab at the Institute for Protein Innovation has had some amazing success using computational design to develop high-affinity mini-proteins that can inhibit protein targets by tightly binding to them.

In practice, the current approach requires the experimental screening of thousands of computational designs to discover a few tight binders, and similarly expensive experimental screens to optimize their binding (i.e.

“affinity maturation”).

If we can make more accurate predictions of how sequence mutations affect binding affinity, we may be able to offload this expensive task to computers, boosting the efficiency of these efforts considerably. In this project, we use relative free energy calculations to predict how single-point mutations of a computationally designed mini-protein alter the binding affinity to the periplasmic protease LapG, an important regulator of bacterial biofilm formation.

These predictions will be compared to high-throughput experimental measurements of binding affinity provided by the Bahl lab.

An important end goal of this work is to develop new classes of inhibitors to make antibiotic therapies more successful.

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RELATED TERMS GLOSSARY AI BETA

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

molecular simulation

Use of computer models to simulate molecular interactions.

Technical: Pharmaceutical
Biotechnology / Drug Discovery

Molecular simulation uses computer programs to imitate how molecules interact with each other. This is helpful for understanding chemical reactions and designing new drugs.


affinity maturation

The process of improving the binding affinity of a molecule to its target.

Technical: Pharmaceutical
Biotechnology / Drug Discovery

Affinity maturation is like refining a drug's ability to latch onto its target. Researchers tweak the drug's structure until it binds more strongly and effectively.


mini-protein

Small proteins with specific functions.

Technical: Pharmaceutical
Biotechnology / Protein Engineering

Mini-proteins are like compact versions of regular proteins. They're smaller but still do important jobs, making them useful for things like drug development.


LapG

Periplasmic protease LapG

Technical: Pharmaceutical
Biotechnology / Microbiology

LapG is a bacterial enzyme that plays a role in biofilm formation. Biofilms are communities of bacteria that can be difficult to treat with antibiotics.


biofilm

A community of microorganisms that adhere to a surface and are encased in a matrix.

Technical: Pharmaceutical
Biotechnology / Microbiology

Biofilms are like bacterial cities. They're communities of bacteria that stick together and form a protective layer. This makes them harder to treat with antibiotics.


antibiotic therapies

The use of antibiotics to treat bacterial infections.

Technical: Healthcare
Pharmaceutical / Infectious Disease Treatment

Antibiotic therapies are treatments that use medicines called antibiotics to fight bacterial infections.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:29:42
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 03:29:42
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 27,914 893,248 AMD
2 RYZEN 9 7900X 12-CORE 24 29,829 715,896 AMD
3 RYZEN 9 5950X 16-CORE 32 21,514 688,448 AMD
4 RYZEN 7 7700X 8-CORE 16 37,704 603,264 AMD
5 12TH GEN CORE I9-12900K 24 23,914 573,936 Intel
6 CORE I5-14600K 20 26,366 527,320 Intel
7 12TH GEN CORE I7-12700K 20 25,304 506,080 Intel
8 RYZEN 7 5700X 8-CORE 16 28,413 454,608 AMD
9 RYZEN 9 5900X 12-CORE 24 18,005 432,120 AMD
10 RYZEN 9 3900 12-CORE 24 17,352 416,448 AMD
11 RYZEN 9 3950X 16-CORE 32 12,627 404,064 AMD
12 11TH GEN CORE I7-11700K @ 3.60GHZ 16 24,921 398,736 Intel
13 RYZEN THREADRIPPER 2950X 16-CORE 32 12,382 396,224 AMD
14 RYZEN 7 5800X 8-CORE 16 24,557 392,912 AMD
15 12TH GEN CORE I7-12700 20 17,883 357,660 Intel
16 CORE I7-10700F CPU @ 2.90GHZ 16 21,738 347,808 Intel
17 RYZEN 9 3900XT 12-CORE 24 14,177 340,248 AMD
18 XEON CPU E5-2690 V4 @ 2.60GHZ 28 11,691 327,348 Intel
19 RYZEN 7 5800X3D 8-CORE 16 20,408 326,528 AMD
20 CORE I9-7920X CPU @ 2.90GHZ 24 12,857 308,568 Intel
21 CORE I9-10850K CPU @ 3.60GHZ 20 14,771 295,420 Intel
22 11TH GEN CORE I9-11900K @ 3.50GHZ 16 18,294 292,704 Intel
23 GENUINE CPU 0000 @ 2.10GHZ 44 6,376 280,544 Intel
24 XEON CPU E5-2680 V2 @ 2.80GHZ 40 6,904 276,160 Intel
25 RYZEN 7 5700G 16 16,458 263,328 AMD
26 CORE I9-10900X CPU @ 3.70GHZ 20 13,003 260,060 Intel
27 RYZEN 7 3800X 8-CORE 16 15,648 250,368 AMD
28 XEON CPU E5-2650 V2 @ 2.60GHZ 32 7,620 243,840 Intel
29 RYZEN 9 3900X 12-CORE 24 9,879 237,096 AMD
30 RYZEN 7 5800H 16 14,645 234,320 AMD
31 RYZEN 5 5600G 12 18,386 220,632 AMD
32 CORE I9-9900K CPU @ 3.60GHZ 16 13,575 217,200 Intel
33 XEON CPU E5-2680 V3 @ 2.50GHZ 24 9,030 216,720 Intel
34 CORE I7-10700K CPU @ 3.80GHZ 16 12,660 202,560 Intel
35 12TH GEN CORE I9-12900H 20 10,029 200,580 Intel
36 13TH GEN CORE I7-13700 24 7,160 171,840 Intel
37 RYZEN 5 1600 SIX-CORE 12 14,104 169,248 AMD
38 RYZEN 7 PRO 4750G 16 10,427 166,832 AMD
39 RYZEN 5 3600 6-CORE 12 13,800 165,600 AMD
40 RYZEN 7 3700X 8-CORE 16 10,133 162,128 AMD
41 CORE I7-10700 CPU @ 2.90GHZ 16 8,051 128,816 Intel
42 CORE I5-10400 CPU @ 2.90GHZ 12 10,229 122,748 Intel
43 XEON CPU E5-2670 0 @ 2.60GHZ 32 3,044 97,408 Intel
44 CORE I7-10700T CPU @ 2.00GHZ 16 5,968 95,488 Intel
45 XEON CPU E5-2680 0 @ 2.70GHZ 16 5,289 84,624 Intel
46 12TH GEN CORE I7-12700KF 20 1,988 39,760 Intel