Nat Methods June 2022 PMID 35637307

ColabFold: making protein folding accessible to all.

Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, Lim Heo, Sergey Ovchinnikov, Martin Steinegger

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Mentions

113

Peak: 34 in May 2022

across 4 sources since May 2022

Extended reach

221,103

potential audience

Total likes

236

Video views

3,071

Mentions per month

May 2022 – May 2025

Where it's discussed

X / Twitter95 posts
News10 articles
Blogs5 articles
YouTube3 videos

AI synopsis

What people are saying

The discussions heavily focus on the publication 'ColabFold: Making protein folding accessible to all,' with participants often describing it as revolutionary and transformative for the field. Phrases like 'accessible to all' and 'democratization of protein folding' illustrate a positive sentiment. The tone is predominantly enthusiastic, with numerous mentions of utilizing ColabFold and related tools for practical applications in research, which contributes to a sense of urgency and significance in the ongoing digital discussions.

AgreementStrong agreement

The majority of discussions reflect strong support for the publication, highlighting its revolutionary nature.

InterestHigh interest

Participants express high levels of curiosity towards the advancements in protein folding and their practical applications.

EngagementModerate engagement

While some comments show deeper engagement with detailed references to methods, others remain more superficial.

ImpactHigh impact

Many believe the publication has significant implications for the field of bioinformatics and protein modeling.

Abstract in brief

ColabFold provides a fast and efficient way to predict protein structures using the combination of MMseqs2 for homology search and AlphaFold2 or RoseTTAFold.
It can execute predictions up to 60 times faster than traditional methods, allowing nearly 1000 structures to be predicted daily on a single GPU server.
As an open-source platform hosted on Google Colaboratory, ColabFold is freely accessible to all users, with additional environmental databases available online.

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All mentions

How to Use Boltz-1x for Protein-Ligand, and DNA Modelling and Docking?

Bioinformatics Insights · May 18, 2025 1,340 views

ColabFold: Accelerating Protein Structure Prediction Efficiently

ColabFold provides a fast and efficient way to predict protein structures using AlphaFold2 and RoseTTAFold. This video explores how ColabFold can execute predictions up to 60 times faster than traditional methods…

Антон Чугунов · Apr 27, 2023 1,298 views

ColabFold: Accelerating Protein Structure Prediction for Everyone

ColabFold provides a fast and efficient way to predict protein structures, leveraging MMseqs2 and AlphaFold2 or RoseTTAFold. This open-source platform is hosted on Google Colaboratory and enables nearly 1000 predictions…

Max Witwer · Jan 9, 2024 434 views

Ashfaq Ahmad

@DrAhmadAshfaq · X

How to Use Boltz-1x for Protein-Ligand, and DNA Modelling and Docking? https://t.co/aKHrhdEw3E via @YouTube The above tutorial will make you able instantly to use and understand the latest package BOLTZ-1X for protein, DNA, and ligand modelling. #bioinformatics

May 18, 2025 · 3 likes · 106 followers View post →

Michael Stam

@mjstam · X

Additional tools: NetSolP - Protein sequence solubility prediction https://t.co/njdQ7Cg8aB ColabFold - Accessible protein folding https://t.co/zbK9Z0IwJq (3/4)

Dec 8, 2024 · 1 like · 288 followers View post →

Sarthak Chauhan

@sarthakiitd · X

ColabFold - Making protein folding accessible to all via Google Colab! https://t.co/QHRBMA6h8s via @YouTube

Jul 12, 2024 · 1 like · 452 followers View post →

Upbm-asso

@UpbmAsso · X

RT @dest_BTK: ✨Destination 2023✨ En 2 ans la prédiction de la structure 3D des protéines par l’#IA a révolutionné le domaine. Elle s’est au…

Jan 9, 2023 · 5 shares · 3,113 followers View post →

desprat

@svtevolution · X

RT @dest_BTK: ✨Destination 2023✨ En 2 ans la prédiction de la structure 3D des protéines par l’#IA a révolutionné le domaine. Elle s’est au…

Jan 9, 2023 · 5 shares · 264 followers View post →

éduscol Biotech STMS

@eduscol_biotech · X

RT @dest_BTK: ✨Destination 2023✨ En 2 ans la prédiction de la structure 3D des protéines par l’#IA a révolutionné le domaine. Elle s’est au…

Jan 8, 2023 · 5 shares · 1,068 followers View post →

La veille techno

@laVeilleTechno · X

RT @dest_BTK: ✨Destination 2023✨ En 2 ans la prédiction de la structure 3D des protéines par l’#IA a révolutionné le domaine. Elle s’est au…

Jan 8, 2023 · 5 shares · 11,310 followers View post →

Destination Biotech

@dest_BTK · X

Jan 8, 2023 · 6 likes · 5 shares · 319 followers View post →

Python Rust Go C CPP Java Kotlin

@pygorustjs · X

RT @Ag_smith: ColabFold: making protein folding accessible to all https://t.co/YzVCYTnARJ @milot_mirdita, @konstinx, @huhlim, @sokrypton, @…

Jan 1, 2023 · 93 shares · 168 followers View post →

bhPluto

@87transceiver · X

ColabFold - Making protein folding accessible to all [NEW RESULTS] https://t.co/JJuWNL3uTg

Sep 5, 2022 · 269 followers View post →

Kitenikinae community based organization

@Kitenikinaecom5 · X

RT @Innov_Inf: ColabFold: making protein folding accessible to all | Nature Methods https://t.co/k79n8GrZJm https://t.co/G2of39gP7t

Aug 8, 2022 · 2 shares · 272 followers View post →

Smart Strong Crawler

@LegionHu · X

RT @Innov_Inf: ColabFold: making protein folding accessible to all | Nature Methods https://t.co/k79n8GrZJm https://t.co/G2of39gP7t

Aug 7, 2022 · 2 shares · 510 followers View post →

The Innovation | Informatics

@Innov_Inf · X

ColabFold: making protein folding accessible to all | Nature Methods https://t.co/k79n8GrZJm https://t.co/G2of39gP7t

Aug 7, 2022 · 5 likes · 2 shares · 3,754 followers View post →

dpdev

@pvcbacteria · X