---
title: "EteRNA"
chunk: 2/2
source: "https://en.wikipedia.org/wiki/EteRNA"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T04:14:21.856117+00:00"
instance: "kb-cron"
---

=== Direct player contribution ===
By August 2011, approximately 26,000 players had contributed RNA sequence designs and over 306 designs have been synthesized for in vitro testing.
Eterna citizen scientists discovered a discrepancy in SHAPE and DMS chemical probing when reading strings of 7+ adenosine, and subsequently published their findings in Biochemistry in 2020. It is the first paper written exclusively by citizen scientists to be published in a peer-reviewed journal.
In a 2023 paper, Eterna players design ribosomal RNA mutations for functional improvements (OpenRibosome Challenge). The players receive feedback from in vitro testing and in vivo (living E. coli) after each round to further tweak their designs.
In a 2024 paper, Eterna players improved a research team's design of a minimized E. coli peptidyl transferase center (PTC). The improved version folds into a PTC-like structure without needing ribosomal proteins and interacts with small molecule analogs of tRNAs. The PTC is believed to be the most ancient part of the ribosome derived from the primordial RNA world and this work is a step closer to seeing the ancient version might have worked.

=== Algorithmic improvements based on human plays ===
In January 2014, the results from Eterna have been published in the PNAS journal, with "Eterna participants" listed as co-authors in the paper. Human players compared the success rates of different designs in the test tube (in vitro) and came up with a number of rules. The rules were used to create an RNA design algorithm called EteRNABot with higher performance than existing ones.
In 2016, 100 difficult EteRNA puzzles were compiled into the "Eterna100" in silico (ViennaRNA 1.8) secondary structure design benchmark set. All of these puzzles are known to be solvable because human players have done so, but the best algorithm of the time (out of 6 tested) could only complete 54 out of 100. The results of the challenges were published in the Journal of Molecular Biology in February 2016. The article includes notes on why certain designs were hard based on player experience. This was the first paper based on dominant writing contributions—and co-lead authorship—by non-expert citizen scientists recruited through a video game.
In 2019, EteRNA published "EternaBrain", a deep learning-based model train on human moves. It was abole to solve 61 puzzles out of the 100 in Eterna100.

== See also ==
Citizen science
Foldit
Game with a purpose
List of crowdsourcing projects
Serious game

== References ==

== External links ==
Official website
Eterna Wiki