af2complex
Predicting direct protein-protein interactions with AlphaFold deep learning neural network models. (by FreshAirTonight)
ColabFold
Making Protein folding accessible to all! (by sokrypton)
| af2complex | ColabFold | |
|---|---|---|
| 1 | 7 | |
| 125 | 1,722 | |
| - | - | |
| 1.8 | 8.7 | |
| about 1 year ago | 7 days ago | |
| Python | Jupyter Notebook | |
| - | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
af2complex
Posts with mentions or reviews of af2complex.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-06.
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Is there any software that can predict if two amino acid sequences would interact?
Also, I saw a "AF2Complex" add-on to AlphaFold 2 which seems to do exactly what I'm looking for, but I don't think that it's available on ColabFold yet and I don't have TB storage available. I'm not expecting you to know this, but is there any way to run an AF2 add-on on Colab?
ColabFold
Posts with mentions or reviews of ColabFold.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-06.
- Can I successfully model a small protein from scratch?
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JMol, Mol*3D, PyMol: Anyway to move two proteins relative to each other?
Thanks for the info. Any opinions on ColabFold?
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What is better right now? AlphaFold or RoseTTAFold?
I'm on the software & infrastructure side of things, so perhaps don't have the depth of the answer you're looking for, and would be happy to be corrected. But as far as I understand from the scientists on our team is that "it depends". Both can get results that are remarkably close to one another, but both can also disagree, so it's hard to say what's "better" - it depends on what you consider the ground truth for your experiments, and a number of other factors such as the length of the sequences you're working with. Both are able to predict structure from sequence, recover sequence from structure, as well as "hallucinate" structure and sequence, so it can be helpful to use both to validate your results and increase your confidence. I assume you've seen the ColabFold notebooks, so it should be easy to compare them against each other for your use case.
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Is there any software that can predict if two amino acid sequences would interact?
a word of warning, the requirements are pretty high, if the sequences are not too long try one of the notebooks: https://github.com/sokrypton/ColabFold
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Advice on Alpha Fold 2.0
In the ColabFold GitHub README there is a description of differences between ColabFold, DeepMind's version, and others. Apparently, the usage of templates and mmseqs2 was not available in the default DeepMind's implementation and was added in ColabFold. https://github.com/sokrypton/ColabFold
- I managed to get Googles deepmind Alphafold running. I modeled segment of DNA from M.Genitalia and also compared it to the much less accurate method of homology modeling that was used in days past.
- Deep-learning algorithms can now predict a protein’s 3D shape from its linear sequence — a huge boon to structural biologists
What are some alternatives?
When comparing af2complex and ColabFold you can also consider the following projects:
deepvariant - DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
RoseTTAFold - This package contains deep learning models and related scripts for RoseTTAFold
openfold - Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
3DFI - The 3DFI pipeline predicts the 3D structure of proteins and searches for structural homology in the 3D space.
Invariant-Attention - An implementation of Invariant Point Attention from Alphafold 2
alphafold - Open source code for AlphaFold.
awesome-protein-design - A curated list of awesome protein design research, software and resources.
Biopython - Official git repository for Biopython (originally converted from CVS)