Skip to content
#protein folding Dataset Open access

Folding without glutamine: proteome-scale removal of a canonical amino acid Dataset

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

This record contains the data and analysis code underlying the figures of the study Folding without glutamine: proteome-scale removal of a canonical amino acid. Using the Escherichia coli reference proteome as a test case, the work asks whether an entire canonical amino acid can be removed from every protein in a proteome without large structural consequences. It combines ProteinMPNN- and MSA-derived "keep-scores" that rank the twenty amino acids by replaceability, structural comparisons (AlphaFold2/3, ESMFold, FoldMason, flexible alignment, BioEmu, and PyRosetta) of glutamine-free and per-amino-acid-recoded proteomes against their AlphaFoldDB references, and experimental validation of a glutamine-free TEM-1 β-lactamase. The deposit is five files: manifest.md and scripts.md (documentation), and three archives — bin.tgz (scripts), data.tgz (data), and a3m.tgz (the AlphaFold input alignments); manifest.md describes every item and maps it to the figure it supports. The deposit holds the data underlying the figures and the research code as it was used, with standard third-party tool steps documented in the paper's Methods with their versions.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Google DeepMind Blog Nov 25, 2025

AlphaFold: Five years of impact

Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.