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Research: INFLUENZA Folding Project #12421

Project #12421 overview

Project Summary AI Beta

Scientists are using computer simulations to understand how miniproteins (tiny proteins) work and bind to viruses like the flu. This research could lead to new and better treatments for infections.
Automated summary; simplified and may not be fully accurate.
Source material

Official 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.

Performance data

Hardware Performance for Project 12421

Compare community-sampled Folding@Home output for the GPUs and CPUs processing this project.

Data as of Sunday, 02 August 2026 22:09:39

CPU PPD Averages Beta

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN THREADRIPPER 7980X 64-CORES 64 25,436 1,627,904 AMD
2 RYZEN 9 9900X 12-CORE 24 53,762 1,290,288 AMD
3 RYZEN 9 7950X3D 16-CORE 32 39,000 1,248,000 AMD
4 RYZEN 9 9950X 16-CORE 32 36,531 1,168,992 AMD
5 CORE I9-14900K 32 31,461 1,006,752 Intel
6 XEON W-3245 CPU @ 3.20GHZ 32 31,428 1,005,696 Intel
7 RYZEN 7 9800X3D 8-CORE 16 60,389 966,224 AMD
8 RYZEN 9 7950X 16-CORE 32 26,418 845,376 AMD
9 RYZEN 7 7800X3D 8-CORE 16 48,586 777,376 AMD
10 RYZEN 9 7900X 12-CORE 24 31,937 766,488 AMD
11 RYZEN 9 5900X 12-CORE 24 29,897 717,528 AMD
12 RYZEN 9 7900 12-CORE 24 26,698 640,752 AMD
13 RYZEN 7 5800X3D 8-CORE 16 38,502 616,032 AMD
14 RYZEN 7 7700 8-CORE 16 37,419 598,704 AMD
15 RYZEN 7 7700X 8-CORE 16 37,253 596,048 AMD
16 12TH GEN CORE I7-12700 20 27,756 555,120 Intel
17 APPLE M2 ULTRA 24 21,560 517,440 Apple
18 13TH GEN CORE I5-13500 20 21,446 428,920 Intel
19 RYZEN 9 5950X 16-CORE 32 12,978 415,296 AMD
20 RYZEN 9 3950X 16-CORE 32 12,410 397,120 AMD
21 RYZEN 7 5700X3D 8-CORE 16 22,671 362,736 AMD
22 RYZEN 7 5800X 8-CORE 16 22,627 362,032 AMD
23 13TH GEN CORE I5-13600K 14 24,982 349,748 Intel
24 12TH GEN CORE I7-12700F 20 17,351 347,020 Intel
25 12TH GEN CORE I7-12700K 20 17,348 346,960 Intel
26 APPLE M1 MAX 10 34,500 345,000 Apple
27 RYZEN 5 5600X 6-CORE 12 27,945 335,340 AMD
28 12TH GEN CORE I9-12900K 24 13,929 334,296 Intel
29 RYZEN 7 5700X 8-CORE 16 20,378 326,048 AMD
30 RYZEN 9 3900X 12-CORE 24 12,355 296,520 AMD
31 RYZEN 9 5900 12-CORE 24 12,112 290,688 AMD
32 13TH GEN CORE I7-13700 24 12,050 289,200 Intel
33 RYZEN 5 5600 6-CORE 12 22,647 271,764 AMD
34 XEON CPU E5-2680 V2 @ 2.80GHZ 40 6,444 257,760 Intel
35 RYZEN 5 5500 12 18,765 225,180 AMD
36 11TH GEN CORE I7-11700K @ 3.60GHZ 16 13,921 222,736 Intel
37 12TH GEN CORE I7-12700H 20 11,061 221,220 Intel
38 CORE I7-10700K CPU @ 3.80GHZ 16 13,458 215,328 Intel
39 RYZEN THREADRIPPER 3960X 24-CORE 48 4,293 206,064 AMD
40 13TH GEN CORE I9-13900K 32 6,036 193,152 Intel
41 RYZEN 5 3600 6-CORE 12 15,841 190,092 AMD
42 RYZEN 7 5700G 16 11,435 182,960 AMD
43 RYZEN 7 3800X 8-CORE 16 11,019 176,304 AMD
44 RYZEN 9 3900XT 12-CORE 24 6,986 167,664 AMD
45 RYZEN 7 5800H 16 10,446 167,136 AMD
46 CORE I9-9900K CPU @ 3.60GHZ 16 10,172 162,752 Intel
47 CORE I5-10600KF CPU @ 4.10GHZ 12 13,263 159,156 Intel
48 XEON CPU E5-2697 V2 @ 2.70GHZ 24 6,429 154,296 Intel
49 CORE I7-5820K CPU @ 3.30GHZ 12 12,217 146,604 Intel
50 CORE I7-5930K CPU @ 3.50GHZ 12 11,830 141,960 Intel
51 11TH GEN CORE I7-11800H @ 2.30GHZ 16 8,352 133,632 Intel
52 11TH GEN CORE I7-11700F @ 2.50GHZ 16 8,039 128,624 Intel
53 CORE I5-14500 20 6,364 127,280 Intel
54 RYZEN 7 3700X 8-CORE 16 7,422 118,752 AMD
55 CORE I7-10700 CPU @ 2.90GHZ 16 7,248 115,968 Intel
56 11TH GEN CORE I9-11900F @ 2.50GHZ 16 6,581 105,296 Intel
57 CORE I7-8700 CPU @ 3.20GHZ 12 8,522 102,264 Intel
58 11TH GEN CORE I7-11700 @ 2.50GHZ 16 6,299 100,784 Intel
59 CORE I9-8950HK CPU @ 2.90GHZ 12 8,299 99,588 Intel
60 APPLE M3 8 12,299 98,392 Apple
61 XEON CPU E5-2660 V3 @ 2.60GHZ 20 4,694 93,880 Intel
62 CORE I7-10700T CPU @ 2.00GHZ 16 5,659 90,544 Intel
63 APPLE M2 8 10,065 80,520 Apple
64 RYZEN 5 2600X SIX-CORE 12 6,579 78,948 AMD
65 APPLE M1 PRO 10 7,436 74,360 Apple
66 CORE I7-8700K CPU @ 3.70GHZ 12 5,069 60,828 Intel
67 XEON CPU E5-2680 0 @ 2.70GHZ 16 3,606 57,696 Intel
68 12TH GEN CORE I5-12450H 12 4,344 52,128 Intel
69 12TH GEN CORE I5-12600K 16 2,893 46,288 Intel
70 12TH GEN CORE I5-12600KF 16 2,558 40,928 Intel
71 RYZEN 7 4800U 16 2,304 36,864 AMD
72 13TH GEN CORE I5-13400F 16 1,207 19,312 Intel