RESEARCH: INFLUENZA
FOLDING PROJECT #18471 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 14,112
Core: 0xa8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

Miniproteins are tiny proteins that can be designed to fight diseases. Scientists want to understand how changes in miniprotein design affect their ability to bind to viral proteins, like those found in the flu. They're using computer simulations to see how different miniprotein designs work at an atomic level. This could lead to better treatments for infectious diseases.

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 engineered proteins with therapeutic potential.

Technical: Pharmaceuticals
Biotechnology / Drug Discovery

Miniproteins are artificially created proteins smaller than antibodies. They are being explored as drugs due to their ability to bind specific targets in the body. Researchers can design miniproteins to target diseases like infections.


Hemagglutinin

A viral protein that allows influenza to bind to cells.

Scientific: Healthcare
Medicine / Virology

Hemagglutinin is a crucial protein found on the surface of influenza viruses. It enables the virus to attach to and infect human cells by binding to sialic acid molecules on cell surfaces. This process is essential for the virus to replicate and spread.


Affinity Maturation

The process of improving the binding strength of a protein to its target.

Technical: Pharmaceuticals
Biotechnology / Protein Engineering

Affinity maturation is a technique used in biotechnology to enhance the effectiveness of proteins like antibodies. It involves making small changes to the protein's structure to increase its ability to bind tightly to its desired target molecule, often resulting in improved therapeutic outcomes.


Molecular Simulation

Computer-based modeling of molecular interactions.

Scientific: Research & Development
Medicine / Computational Biology

Molecular simulations use computer programs to recreate the movements and interactions of atoms and molecules. This allows scientists to study how proteins bind to each other or to drugs, how cells function, and other complex biological processes.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Sunday, 26 April 2026 03:28:33
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PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Sunday, 26 April 2026 03:28:33
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 7 5700G 16 50,842 813,472 AMD
2 RYZEN 9 7900X 12-CORE 24 27,041 648,984 AMD
3 RYZEN 7 7700X 8-CORE 16 37,045 592,720 AMD
4 RYZEN 7 5800X3D 8-CORE 16 29,546 472,736 AMD
5 RYZEN 7 5700X 8-CORE 16 27,350 437,600 AMD
6 RYZEN 9 5950X 16-CORE 32 12,681 405,792 AMD
7 11TH GEN CORE I7-11700K @ 3.60GHZ 16 20,874 333,984 Intel
8 RYZEN 7 5800X 8-CORE 16 19,557 312,912 AMD
9 RYZEN 5 5600 6-CORE 12 25,432 305,184 AMD
10 CORE I7-10700K CPU @ 3.80GHZ 16 17,026 272,416 Intel
11 RYZEN 7 3700X 8-CORE 16 15,979 255,664 AMD
12 RYZEN 5 5600X 6-CORE 12 18,480 221,760 AMD
13 RYZEN 5 3500 6-CORE 6 33,701 202,206 AMD
14 11TH GEN CORE I9-11900K @ 3.50GHZ 16 11,377 182,032 Intel
15 RYZEN 5 3600 6-CORE 12 13,183 158,196 AMD
16 12TH GEN CORE I7-12700 20 7,572 151,440 Intel
17 CORE I5-8400 CPU @ 2.80GHZ 6 25,082 150,492 Intel
18 CORE I7-7700K CPU @ 4.20GHZ 8 16,469 131,752 Intel
19 CORE I7-5930K CPU @ 3.50GHZ 12 10,656 127,872 Intel
20 CORE I7-5820K CPU @ 3.30GHZ 12 9,912 118,944 Intel
21 CORE I9-8950HK CPU @ 2.90GHZ 12 8,345 100,140 Intel
22 CORE I7-8705G CPU @ 3.10GHZ 8 12,443 99,544 Intel
23 CORE I7-6700T CPU @ 2.80GHZ 8 11,887 95,096 Intel
24 XEON CPU E3-1270 V5 @ 3.60GHZ 8 11,764 94,112 Intel
25 XEON CPU E5-1630 V3 @ 3.70GHZ 8 9,836 78,688 Intel
26 CORE I7-6700K CPU @ 4.00GHZ 8 9,806 78,448 Intel
27 CORE I7-4770HQ CPU @ 2.20GHZ 8 7,915 63,320 Intel
28 CORE I7-3770K CPU @ 3.50GHZ 8 7,719 61,752 Intel
29 XEON CPU X5680 @ 3.33GHZ 12 4,626 55,512 Intel
30 APPLE M1 8 6,938 55,504 Apple
31 XEON CPU E5-2697 V2 @ 2.70GHZ 24 1,066 25,584 Intel