RESEARCH: INFLUENZA
FOLDING PROJECT #18476 PROFILE
PROJECT TEAM
Manager(s): Dylan NovackInstitution: Temple University
Project URL: View Project Website
WORK UNIT INFO
Atoms: 93,430Core: 0xa8
Status: Public
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TLDR; PROJECT SUMMARY AI BETA
Researchers are using computer simulations to study how tiny proteins called miniproteins bind to a viral protein called hemagglutinin. This could help them design better drugs to fight the flu and other viruses. The project relates to understanding how changes in miniprotein structure affect their ability to bind, and ultimately improve the effectiveness of these potential new treatments.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Designed miniproteins are a class of biomolecules with intermediate sizes—larger than small-molecule drugs, but smaller than monoclonal antibodies.
Miniproteins can be computationally designed to tightly bind protein targets for use as potential therapeutics, a promising new avenue for treating infectious disease. Hemagglutinin is a viral fusion protein that allows H1 influenza A (HA) to bind sialic acid on cell surfaces, as well as being involved in the post-endocytosis mechanism of cellular infection.
The Baker lab at University of Washington has developed de novo designed miniproteins that bind hemagglutinin, and improved their binding through affinity maturation (Chevalier et al.
2017).
Many of the mutations seen in affinity-matured sequences are not found in the binding interface, and it remains an open question how these changes lead to higher affinity.
Furthermore, many of the computational predictions of how single-point mutations affect binding deviate significantly from the experimentally determined values. Could all-atom molecular simulation approaches achieve more accurate predictions? In this set of simulations, we aim to use massively parallel expanded ensemble simulations to predict mutational effects on affinities to hemagglutinin.
By pairing these simulations with other simulations aimed at modeling the binding reactions of these miniproteins to hemagglutinin, we aim to have a relatively complete picture of a miniprotein-target binding reaction and how mutations affect it.
These studies are a large-scale investigation on how miniprotein binding reactions work in atomic detail, towards a better understanding of computational design and modulation of miniprotein therapeutics.
RELATED TERMS GLOSSARY AI BETA
Miniproteins
Small proteins with therapeutic potential.
Miniproteins are designed proteins of intermediate size, larger than small molecule drugs but smaller than antibodies. They can be engineered to bind specific targets and have potential as therapeutics for various diseases.
Monoclonal Antibodies
Laboratory-produced antibodies that target specific antigens.
Monoclonal antibodies are laboratory-created antibodies designed to recognize and bind to a specific antigen (a molecule on the surface of cells or pathogens). They are used in various therapies, including cancer treatment and autoimmune disease management.
Hemagglutinin
Viral protein that binds to sialic acid on cell surfaces.
Hemagglutinin is a viral protein found on the surface of influenza viruses. It plays a crucial role in the initial stages of infection by binding to sialic acid receptors on host cells, allowing the virus to attach and enter.
Affinity Maturation
Process of improving the binding affinity of a molecule.
Affinity maturation is a process used in biotechnology to enhance the binding strength of molecules, such as antibodies or miniproteins. It involves introducing mutations and selecting variants with higher affinity for their target.
Molecular Simulation
Computer-based modeling of molecular interactions.
Molecular simulation is a computational technique used to study the behavior of molecules at an atomic level. It involves simulating the movement and interactions of atoms and molecules over time, providing insights into their structure, dynamics, and properties.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:28:25|
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PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:28:25|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|---|---|---|---|---|
| 1 | RYZEN 7 7700X 8-CORE | 16 | 35,979 | 575,664 | AMD |
| 2 | RYZEN 9 5950X 16-CORE | 32 | 15,772 | 504,704 | AMD |
| 3 | 12TH GEN CORE I7-12700K | 20 | 21,807 | 436,140 | Intel |
| 4 | RYZEN 7 5800X 8-CORE | 16 | 22,315 | 357,040 | AMD |
| 5 | RYZEN 7 5700X 8-CORE | 16 | 21,501 | 344,016 | AMD |
| 6 | XEON PLATINUM 8370C CPU @ 2.80GHZ | 16 | 19,138 | 306,208 | Intel |
| 7 | RYZEN 7 5700G | 16 | 18,042 | 288,672 | AMD |
| 8 | RYZEN 7 3800X 8-CORE | 16 | 16,167 | 258,672 | AMD |
| 9 | CORE I7-10700K CPU @ 3.80GHZ | 16 | 14,333 | 229,328 | Intel |
| 10 | 12TH GEN CORE I7-12700 | 20 | 11,353 | 227,060 | Intel |
| 11 | RYZEN 7 3700X 8-CORE | 16 | 13,643 | 218,288 | AMD |
| 12 | 11TH GEN CORE I9-11900K @ 3.50GHZ | 16 | 9,035 | 144,560 | Intel |
| 13 | 12TH GEN CORE I7-12700H | 20 | 5,468 | 109,360 | Intel |
| 14 | CORE I7-10700T CPU @ 2.00GHZ | 16 | 5,687 | 90,992 | Intel |
| 15 | XEON CPU E5-2697 V2 @ 2.70GHZ | 24 | 1,473 | 35,352 | Intel |
| 16 | 12TH GEN CORE I5-12600KF | 16 | Intel |