Research section Research projects and references

Research: INFLUENZA Folding Project #18471

Project #18471 overview

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.
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 18471

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

Data as of Sunday, 02 August 2026 21:51:07

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 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