RESEARCH: CANCER
FOLDING PROJECT #18400 PROFILE
PROJECT TEAM
Manager(s): Prof. Vincent VoelzInstitution: Temple University
WORK UNIT INFO
Atoms: 24,700Core: GRO_A8
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project uses computer simulations to predict how changes in a mini-protein's design will affect its ability to bind to a bacterial enzyme. The goal is to develop new antibiotics by finding mini-proteins that strongly block the enzyme and disrupt bacterial biofilm formation.
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
molecular simulation
Using computer models to simulate molecular interactions.
Molecular simulation is a computational technique used to study the behavior of molecules and their interactions. It involves creating digital models of molecules and simulating their movements and interactions over time.
affinity maturation
A process of improving the binding affinity of a molecule to its target.
Affinity maturation is a crucial step in drug development where scientists refine the structure of a molecule to make it bind more strongly and effectively to its intended target. This often involves making small changes to the molecule's sequence and testing its binding strength.
mini-proteins
Small, engineered proteins with specific functions.
Mini-proteins are compact versions of traditional proteins designed to carry out specific tasks. They are often engineered for their stability, solubility, and ability to bind to particular targets. Their small size makes them easier to produce and deliver compared to larger proteins.
binding affinity
The strength of the attraction between a molecule and its target.
Binding affinity describes how strongly a molecule attaches to its intended target. A high binding affinity means the molecule sticks tightly to its target, while a low binding affinity indicates a weaker connection.
periplasmic protease
A type of enzyme found in the periplasmic space of bacteria.
Periplasmic proteases are enzymes located within the periplasm, a region between the cell membrane and the outer membrane of bacteria. They play crucial roles in various cellular processes, including protein degradation, signal transduction, and nutrient utilization.
LapG
Protease LapG
LapG is a specific type of periplasmic protease that plays a vital role in regulating bacterial biofilm formation. Biofilms are communities of bacteria that adhere to surfaces and protect themselves from environmental stresses.
antibiotic therapies
Medical treatments that use antibiotics to kill or inhibit the growth of bacteria.
Antibiotic therapies are medical interventions that utilize drugs called antibiotics to combat bacterial infections. Antibiotics work by targeting specific mechanisms essential for bacterial survival, such as cell wall synthesis or protein production.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:30:03|
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 03:30:03|
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 | 35,146 | 1,124,672 | AMD |
| 2 | RYZEN 7 5800X 8-CORE | 16 | 30,101 | 481,616 | AMD |
| 3 | RYZEN 9 5950X 16-CORE | 32 | 13,646 | 436,672 | AMD |
| 4 | RYZEN 7 3800X 8-CORE | 16 | 21,559 | 344,944 | AMD |
| 5 | CORE I9-10850K CPU @ 3.60GHZ | 20 | 17,169 | 343,380 | Intel |
| 6 | RYZEN 9 3900X 12-CORE | 24 | 12,252 | 294,048 | AMD |
| 7 | CORE I7-8700 CPU @ 3.20GHZ | 12 | 19,719 | 236,628 | Intel |
| 8 | XEON CPU E5-2690 V4 @ 2.60GHZ | 28 | 7,037 | 197,036 | Intel |
| 9 | RYZEN 7 2700X EIGHT-CORE | 16 | 11,053 | 176,848 | AMD |
| 10 | CORE I5-10400 CPU @ 2.90GHZ | 12 | 12,277 | 147,324 | Intel |
| 11 | RYZEN 9 3900XT 12-CORE | 24 | 6,071 | 145,704 | AMD |
| 12 | RYZEN 5 3600 6-CORE | 12 | 10,614 | 127,368 | AMD |
| 13 | RYZEN 5 2600 SIX-CORE | 12 | 8,349 | 100,188 | AMD |
| 14 | CORE I7-6700K CPU @ 4.00GHZ | 8 | 11,013 | 88,104 | Intel |
| 15 | CORE I7-8705G CPU @ 3.10GHZ | 8 | 10,783 | 86,264 | Intel |
| 16 | CORE I5-7200U CPU @ 2.50GHZ | 4 | 12,066 | 48,264 | Intel |
| 17 | CORE I7-10750H CPU @ 2.60GHZ | 12 | 3,927 | 47,124 | Intel |