RESEARCH: INFLUENZA
FOLDING PROJECT #12407 PROFILE

PROJECT TEAM

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

WORK UNIT INFO

Atoms: 93,425
Core: 0xa8
Status: Public

TLDR; PROJECT SUMMARY AI BETA

Researchers are using computer simulations to understand how miniproteins (tiny disease-fighting proteins) bind to viruses like the flu. They want to see how changes to miniprotein design affect their ability to stop viruses, which could lead to better 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

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

Miniproteins

Small proteins designed for therapeutic use.

Scientific: Pharmaceutical
Biotechnology / Drug Design

Miniproteins are engineered proteins smaller than traditional antibodies. They can be designed to bind specific targets in the body, like viruses or disease-causing proteins, making them promising new treatments.


Hemagglutinin

A viral protein that allows influenza to attach to cells.

Scientific: Biomedical Research
Virology / Influenza Virus

Hemagglutinin is a crucial protein found on the surface of influenza viruses. It binds to sugar molecules called sialic acids on human cells, enabling the virus to attach and enter our bodies.


Affinity Maturation

Process of improving a protein's binding affinity.

Technical: Pharmaceutical
Biotechnology / Protein Engineering

Affinity maturation is a technique used to enhance the ability of proteins, like antibodies or miniproteins, to bind their target molecules more strongly. This process often involves making small changes to the protein's structure through mutations.


Molecular Simulation

Computer-based method to study molecular behavior.

Scientific: Biotechnology Research
Computational Biology / Biomolecular Modeling

Molecular simulations use mathematical models and algorithms to simulate the movements and interactions of atoms and molecules. This allows scientists to study complex biological processes at the atomic level.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:34:47
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PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:34:47
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 35,518 1,136,576 AMD
2 RYZEN THREADRIPPER 3960X 24-CORE 48 16,933 812,784 AMD
3 RYZEN 9 5900X 12-CORE 24 31,399 753,576 AMD
4 CORE I9-14900KF 24 29,577 709,848 Intel
5 RYZEN 9 7900 12-CORE 24 29,020 696,480 AMD
6 CORE I9-14900K 32 20,298 649,536 Intel
7 RYZEN 9 7900X 12-CORE 24 26,244 629,856 AMD
8 RYZEN 7 7800X3D 8-CORE 16 37,265 596,240 AMD
9 RYZEN 9 5950X 16-CORE 32 17,112 547,584 AMD
10 CORE I5-14600K 20 26,348 526,960 Intel
11 RYZEN 5 7600 6-CORE 12 39,905 478,860 AMD
12 RYZEN 9 7950X3D 16-CORE 32 14,058 449,856 AMD
13 RYZEN 9 3900 12-CORE 24 18,651 447,624 AMD
14 13TH GEN CORE I5-13500 20 21,852 437,040 Intel
15 12TH GEN CORE I5-12400F 12 34,560 414,720 Intel
16 RYZEN 7 7700X 8-CORE 16 25,726 411,616 AMD
17 RYZEN 7 5800X3D 8-CORE 16 25,558 408,928 AMD
18 RYZEN 7 5800X 8-CORE 16 24,651 394,416 AMD
19 RYZEN 7 5700X 8-CORE 16 23,213 371,408 AMD
20 12TH GEN CORE I7-12700F 20 18,312 366,240 Intel
21 RYZEN 5 7600X 6-CORE 12 27,706 332,472 AMD
22 13TH GEN CORE I5-13600K 14 23,074 323,036 Intel
23 RYZEN 9 3900X 12-CORE 24 12,908 309,792 AMD
24 RYZEN 5 5600 6-CORE 12 23,504 282,048 AMD
25 RYZEN 7 5700G 16 17,550 280,800 AMD
26 11TH GEN CORE I7-11700K @ 3.60GHZ 16 16,767 268,272 Intel
27 12TH GEN CORE I5-12400 12 21,463 257,556 Intel
28 CORE I9-10900K CPU @ 3.70GHZ 20 12,493 249,860 Intel
29 13TH GEN CORE I9-13900K 32 7,724 247,168 Intel
30 13TH GEN CORE I7-13700 24 10,219 245,256 Intel
31 CORE I7-10700K CPU @ 3.80GHZ 16 14,905 238,480 Intel
32 RYZEN 9 3900XT 12-CORE 24 9,522 228,528 AMD
33 11TH GEN CORE I7-11700KF @ 3.60GHZ 16 14,204 227,264 Intel
34 XEON CPU E5-2683 V4 @ 2.10GHZ 32 7,092 226,944 Intel
35 XEON GOLD 5120 CPU @ 2.20GHZ 28 8,046 225,288 Intel
36 RYZEN 9 5900 12-CORE 24 9,113 218,712 AMD
37 RYZEN 5 5600X 6-CORE 12 17,117 205,404 AMD
38 RYZEN 5 7640HS W/ RADEON 760M GRAPHICS 12 14,907 178,884 AMD
39 RYZEN 9 3950X 16-CORE 32 5,574 178,368 AMD
40 RYZEN THREADRIPPER 2990WX 32-CORE 64 2,718 173,952 AMD
41 RYZEN 5 3600 6-CORE 12 14,350 172,200 AMD
42 CORE I5-10600KF CPU @ 4.10GHZ 12 13,418 161,016 Intel
43 CORE I7-5930K CPU @ 3.50GHZ 12 12,911 154,932 Intel
44 CORE I7-5820K CPU @ 3.30GHZ 12 12,162 145,944 Intel
45 RYZEN 7 3700X 8-CORE 16 8,752 140,032 AMD
46 13TH GEN CORE I7-13700K 24 5,487 131,688 Intel
47 RYZEN 5 2600X SIX-CORE 12 10,659 127,908 AMD
48 11TH GEN CORE I9-11900F @ 2.50GHZ 16 7,156 114,496 Intel
49 11TH GEN CORE I7-11700F @ 2.50GHZ 16 6,573 105,168 Intel
50 CORE I5-10400 CPU @ 2.90GHZ 12 8,466 101,592 Intel
51 CORE I9-8950HK CPU @ 2.90GHZ 12 7,821 93,852 Intel
52 CORE I7-10700T CPU @ 2.00GHZ 16 5,865 93,840 Intel
53 XEON CPU X5690 @ 3.47GHZ 24 3,525 84,600 Intel
54 CORE I7-9750H CPU @ 2.60GHZ 12 6,752 81,024 Intel
55 RYZEN 5 5600H 12 6,564 78,768 AMD
56 XEON CPU E5-2697 V2 @ 2.70GHZ 24 3,272 78,528 Intel
57 APPLE M1 PRO 10 7,314 73,140 Apple
58 XEON CPU X5680 @ 3.33GHZ 12 4,712 56,544 Intel
59 RYZEN 5 5500U 12 4,380 52,560 AMD
60 CORE I7-8700K CPU @ 3.70GHZ 12 4,342 52,104 Intel
61 RYZEN 7 4800U 16 2,579 41,264 AMD
62 CORE I7-7820X CPU @ 3.60GHZ 16 2,447 39,152 Intel
63 12TH GEN CORE I5-12600KF 16 2,417 38,672 Intel
64 12TH GEN CORE I7-12700K 20 Intel