Elliott, Luc G 
ORCID: 0009-0002-0181-4041, Simpkin, Adam J ORCID: 0000-0003-1883-9376 and Rigden, Daniel J ORCID: 0000-0002-7565-8937
(2025)
ABCFold: easier running and comparison of AlphaFold 3, Boltz-1, and Chai-1.
Bioinformatics advances, 5 (1).
vbaf153-.
ISSN 2635-0041, 2635-0041
Abstract
<h4>Motivation</h4>The latest generation of deep learning-based structure prediction methods enable accurate modelling of most proteins and many complexes. However, preparing inputs for the locally installed software is not always straightforward, and the results of local runs are not always presented in an ideally accessible fashion. Furthermore, it is not yet clear whether the latest tools perform equivalently for all types of target.<h4>Results</h4>ABCFold facilitates the use of AlphaFold 3, Boltz-1, and Chai-1 with a standardized input to predict atomic structures, with Boltz-1 and Chai-1 being installed on runtime (if required). MSAs can be generated internally using either the JackHMMER MSA search within AlphaFold 3, or with the MMseqs2 API. Alternatively, users can provide their own custom MSAs. This therefore allows AlphaFold 3 to be installed and run without downloading the large databases needed for JackHMMER. There are also straightforward options to use templates, including custom templates. Results from all packages are treated in a unified fashion, enabling easy comparison of results from different methods. A variety of visualization options are available which include information on steric clashes.<h4>Availability and implementation</h4>ABCFold is coded in Python and JavaScript. All scripts and associated documentation are available from https://github.com/rigdenlab/ABCFold or https://pypi.org/project/ABCFold/.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Bioengineering, Machine Learning and Artificial Intelligence |
| Divisions: | Faculty of Health & Life Sciences Faculty of Health & Life Sciences > Inst. Systems, Molec & Integrative Biology > Inst. Systems, Molec & Integrative Biology |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 17 Jul 2025 15:33 |
| Last Modified: | 06 Jan 2026 06:03 |
| DOI: | 10.1093/bioadv/vbaf153 |
| Open Access URL: | https://doi.org/10.1093/bioadv/vbaf153 |
| Related Websites: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3193761 |
| Disclaimer: | The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate. |
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