RESEARCH: INFLUENZA
FOLDING PROJECT #18478 PROFILE

PROJECT TEAM

Manager(s): Dylan Novack
Institution: Temple University
Project URL: View Project Website

WORK UNIT INFO

Atoms: 93,435
Core: 0xa8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

This project studies miniproteins – tiny proteins that can be designed to block viruses. They're looking at how changes in the miniprotein affect its ability to bind to a flu virus protein, using powerful computer simulations. This could help us design better antiviral drugs.

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

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

Miniproteins

Small proteins designed for therapeutic purposes.

Scientific: Pharmaceuticals
Biotechnology / Drug Development

Miniproteins are artificially created proteins with sizes between small molecules and antibodies. They have the potential to be highly effective drugs because they can be specifically designed to target certain proteins in the body.


Hemagglutinin

A viral protein that allows influenza A to attach to and infect cells.

Scientific: Biotechnology
Virology / Influenza Virus

Hemagglutinin is a key protein found on the surface of influenza A viruses. It helps the virus bind to sialic acid receptors on cell surfaces, allowing it to enter and infect cells. Hemagglutinin is a target for antiviral drugs and vaccines.


Monoclonal Antibodies

Lab-produced antibodies that target specific antigens.

Scientific: Pharmaceuticals
Immunology / Biopharmaceuticals

Monoclonal antibodies are engineered immune system proteins designed to bind to specific targets (antigens) in the body. They are used as therapeutics to treat a wide range of diseases, including cancer, autoimmune disorders, and infectious diseases.


Affinity Maturation

A process of improving the binding affinity of a protein to its target.

Scientific: Biotechnology
Protein Engineering / Drug Design

Affinity maturation is a technique used in drug development to enhance the binding strength of a protein (often an antibody or miniprotein) to its desired target. This process involves making small changes to the protein's structure, which can result in significantly improved binding affinity and therapeutic efficacy.


Molecular Simulation

A computer-based method for modeling the behavior of molecules.

Scientific: Biotechnology
Computational Biology / Drug Discovery

Molecular simulations use mathematical models to simulate the movements and interactions of atoms and molecules. These simulations can be used to study a wide range of biological processes, including protein folding, drug binding, and enzyme catalysis.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:28:22
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PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 03:28:22
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 EPYC 7B12 64-CORE 64 18,171 1,162,944 AMD
2 RYZEN 9 7950X 16-CORE 32 30,760 984,320 AMD
3 RYZEN 7 7700X 8-CORE 16 41,707 667,312 AMD
4 RYZEN 9 7900X 12-CORE 24 25,744 617,856 AMD
5 RYZEN 7 5800X3D 8-CORE 16 30,542 488,672 AMD
6 RYZEN 9 5950X 16-CORE 32 14,588 466,816 AMD
7 RYZEN 7 5700X 8-CORE 16 23,645 378,320 AMD
8 RYZEN 7 5800X 8-CORE 16 22,472 359,552 AMD
9 12TH GEN CORE I5-12600K 16 19,946 319,136 Intel
10 XEON PLATINUM 8370C CPU @ 2.80GHZ 16 17,506 280,096 Intel
11 XEON CPU E5-2680 V2 @ 2.80GHZ 40 6,674 266,960 Intel
12 RYZEN 7 5700G 16 16,445 263,120 AMD
13 12TH GEN CORE I7-12700 20 12,062 241,240 Intel
14 CORE I7-10700K CPU @ 3.80GHZ 16 14,494 231,904 Intel
15 RYZEN 7 3700X 8-CORE 16 12,816 205,056 AMD
16 12TH GEN CORE I7-12700F 20 10,149 202,980 Intel
17 CORE I9-9900K CPU @ 3.60GHZ 16 10,460 167,360 Intel
18 CORE I9-7940X CPU @ 3.10GHZ 28 5,578 156,184 Intel
19 11TH GEN CORE I9-11900K @ 3.50GHZ 16 9,574 153,184 Intel
20 EPYC 7262 8-CORE 16 8,753 140,048 AMD
21 RYZEN THREADRIPPER 2950X 16-CORE 32 4,120 131,840 AMD
22 12TH GEN CORE I7-12700H 20 5,697 113,940 Intel
23 CORE I7-10700T CPU @ 2.00GHZ 16 5,578 89,248 Intel
24 XEON CPU E5-2697 V2 @ 2.70GHZ 24 2,839 68,136 Intel
25 12TH GEN CORE I7-1270P 16 3,019 48,304 Intel