RESEARCH: CANCER
FOLDING PROJECT #18402 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 24,700
Core: 0xa8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project uses computer simulations to see how changing the design of tiny proteins can make them bind better to a bacterial target. This could lead to new, more effective antibiotics.

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.

.

RELATED TERMS GLOSSARY AI BETA

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

molecular simulation

Using computer models to simulate molecular behavior.

Technical: Pharmaceuticals
Biotechnology / Drug Discovery

Molecular simulation uses computer programs to imitate how atoms and molecules interact. This helps scientists understand chemical reactions, predict protein folding, and design new drugs.


affinity maturation

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

Technical: Pharmaceuticals
Biotechnology / Drug Discovery

Affinity maturation is like fine-tuning a key to fit a lock better. Scientists use this process to create drugs that bind more strongly to their target proteins, making them more effective.


mini-protein

A small protein with a specific function.

Technical: Pharmaceuticals
Biotechnology / Protein Engineering

Mini-proteins are tiny versions of regular proteins. They have the same ability to bind to other molecules, but they are much smaller and easier to produce.


periplasmic protease

An enzyme found in the periplasm of bacteria.

Scientific: Pharmaceuticals
Biotechnology / Bacterial Physiology

Periplasmic proteases are enzymes that break down proteins. They are located in a space between the cell membrane and the outer membrane of bacteria.


bacterial biofilm

A community of bacteria that live together in a slimy matrix.

Scientific: Pharmaceuticals
Microbiology / Biofilm Formation

Bacterial biofilms are like cities for bacteria. They form on surfaces and are very difficult to kill because the bacteria are protected by their sticky matrix.


antibiotic therapies

Treatments that use antibiotics to kill or inhibit the growth of bacteria.

Scientific: Healthcare
Pharmacology / Antimicrobial Agents

Antibiotic therapies are used to treat bacterial infections. They work by killing or stopping the growth of bacteria.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:30:00
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 03:30:00
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 27,938 894,016 AMD
2 RYZEN 9 3950X 16-CORE 32 23,631 756,192 AMD
3 RYZEN 7 5800X 8-CORE 16 44,077 705,232 AMD
4 RYZEN 9 5950X 16-CORE 32 21,395 684,640 AMD
5 RYZEN 9 5900X 12-CORE 24 27,248 653,952 AMD
6 RYZEN 7 7700X 8-CORE 16 40,158 642,528 AMD
7 RYZEN 9 7900X 12-CORE 24 23,382 561,168 AMD
8 RYZEN 7 5800X3D 8-CORE 16 33,554 536,864 AMD
9 RYZEN 7 5700X 8-CORE 16 25,658 410,528 AMD
10 RYZEN 7 5700G 16 23,137 370,192 AMD
11 12TH GEN CORE I7-12700K 20 16,796 335,920 Intel
12 11TH GEN CORE I9-11900K @ 3.50GHZ 16 20,754 332,064 Intel
13 RYZEN 7 3800X 8-CORE 16 20,255 324,080 AMD
14 11TH GEN CORE I7-11700K @ 3.60GHZ 16 19,994 319,904 Intel
15 RYZEN 9 3900XT 12-CORE 24 12,482 299,568 AMD
16 CORE I9-10900X CPU @ 3.70GHZ 20 14,715 294,300 Intel
17 CORE I9-10850K CPU @ 3.60GHZ 20 14,459 289,180 Intel
18 RYZEN 5 5600X 6-CORE 12 23,732 284,784 AMD
19 RYZEN 7 PRO 7840U W/ RADEON 780M GRAPHICS 16 17,779 284,464 AMD
20 RYZEN 9 3900X 12-CORE 24 11,194 268,656 AMD
21 RYZEN 9 5900HS 16 16,416 262,656 AMD
22 CORE I7-10700K CPU @ 3.80GHZ 16 16,238 259,808 Intel
23 RYZEN 5 PRO 5650G 12 20,442 245,304 AMD
24 EPYC 7401P 24-CORE 48 4,678 224,544 AMD
25 CORE I9-7940X CPU @ 3.10GHZ 28 7,957 222,796 Intel
26 XEON W-2245 CPU @ 3.90GHZ 16 13,918 222,688 Intel
27 CORE I9-9900K CPU @ 3.60GHZ 16 13,525 216,400 Intel
28 RYZEN 5 5600G 12 16,997 203,964 AMD
29 XEON CPU E5-2680 V3 @ 2.50GHZ 24 8,408 201,792 Intel
30 RYZEN 7 5800H 16 12,535 200,560 AMD
31 RYZEN 7 3700X 8-CORE 16 12,366 197,856 AMD
32 XEON CPU E5-2690 V4 @ 2.60GHZ 28 6,866 192,248 Intel
33 RYZEN 5 2600X SIX-CORE 12 15,425 185,100 AMD
34 RYZEN 5 3600 6-CORE 12 14,748 176,976 AMD
35 CORE I7-9700K CPU @ 3.60GHZ 8 21,169 169,352 Intel
36 RYZEN 7 PRO 4750G 16 10,398 166,368 AMD
37 CORE I7-8700 CPU @ 3.20GHZ 12 13,149 157,788 Intel
38 12TH GEN CORE I3-12100 8 19,146 153,168 Intel
39 CORE I5-9600K CPU @ 3.70GHZ 6 25,120 150,720 Intel
40 RYZEN 7 2700X EIGHT-CORE 16 9,402 150,432 AMD
41 XEON GOLD 6128 CPU @ 3.40GHZ 12 12,411 148,932 Intel
42 12TH GEN CORE I9-12900K 24 6,096 146,304 Intel
43 CORE I7-10750H CPU @ 2.60GHZ 12 12,009 144,108 Intel
44 CORE I7-9700 CPU @ 3.00GHZ 8 17,984 143,872 Intel
45 XEON CPU E5-2650 V2 @ 2.60GHZ 32 4,347 139,104 Intel
46 CORE I7-5930K CPU @ 3.50GHZ 12 10,663 127,956 Intel
47 11TH GEN CORE I9-11900F @ 2.50GHZ 16 7,728 123,648 Intel
48 CORE I7-7700K CPU @ 4.20GHZ 8 14,777 118,216 Intel
49 11TH GEN CORE I5-11400 @ 2.60GHZ 12 9,594 115,128 Intel
50 XEON CPU E5-2670 0 @ 2.60GHZ 32 3,408 109,056 Intel
51 XEON CPU E5-2650L V4 @ 1.70GHZ 28 3,830 107,240 Intel
52 CORE I7-8705G CPU @ 3.10GHZ 8 11,555 92,440 Intel
53 CORE I7-4790K CPU @ 4.00GHZ 8 11,316 90,528 Intel
54 XEON CPU E3-1270 V5 @ 3.60GHZ 8 11,160 89,280 Intel
55 RYZEN 5 1600 SIX-CORE 12 7,014 84,168 AMD
56 CORE I9-8950HK CPU @ 2.90GHZ 12 6,753 81,036 Intel
57 APPLE M1 MAX 10 8,039 80,390 Apple
58 CORE I7-10700T CPU @ 2.00GHZ 16 4,987 79,792 Intel
59 APPLE M1 8 8,989 71,912 Apple
60 CORE I7-6700 CPU @ 3.40GHZ 8 8,342 66,736 Intel
61 XEON CPU E5-2680 0 @ 2.70GHZ 16 4,014 64,224 Intel
62 CORE I7-4770 CPU @ 3.40GHZ 8 7,350 58,800 Intel
63 CORE I7-4770HQ CPU @ 2.20GHZ 8 7,342 58,736 Intel
64 XEON W-10855M CPU @ 2.80GHZ 12 4,657 55,884 Intel
65 APPLE M1 PRO 10 5,099 50,990 Apple
66 CORE I7-6700K CPU @ 4.00GHZ 8 6,256 50,048 Intel
67 CORE I7-4770K CPU @ 3.50GHZ 8 5,879 47,032 Intel
68 RYZEN 7 4700U 8 5,349 42,792 AMD
69 RYZEN 5 5500U 12 3,413 40,956 AMD
70 CORE I5-8365U CPU @ 1.60GHZ 8 4,932 39,456 Intel
71 XEON CPU E31245 @ 3.30GHZ 8 4,512 36,096 Intel
72 CORE I7-2760QM CPU @ 2.40GHZ 8 3,225 25,800 Intel
73 12TH GEN CORE I5-12600KF 16 1,549 24,784 Intel
74 FX-8150 EIGHT-CORE 8 2,905 23,240 AMD
75 CORE I5-10210U CPU @ 1.60GHZ 7 3,179 22,253 Intel
76 XEON CPU E5-1620 V2 @ 3.70GHZ 8 2,340 18,720 Intel
77 CORE I7 CPU 975 @ 3.33GHZ 8 2,291 18,328 Intel