
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.08.25.609581
preprint
1
Article
AlphaFold2 knows some protein folding principles
Chang Liwei http://orcid.org/0000-0001-5847-0820

Perez Alberto http://orcid.org/0000-0002-5054-5338

26 8 2024
2024.08.25.609581https://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
http://biorxiv.org/lookup/doi/10.1101/2024.08.25.609581
nihpp-2024.08.25.609581.pdf
AlphaFold2 (AF2) has revolutionized protein structure prediction. However, a common confusion lies in equating the protein structure prediction problem with the protein folding problem . The former provides a static structure, while the latter explains the dynamic folding pathway to that structure. We challenge the current status quo and advocate that AF2 has indeed learned some protein folding prin- ciples, despite being designed for structure prediction. AF2’s high-dimensional parameters encode an imperfect biophysical scoring function. Typically, AF2 uses multiple sequence alignments (MSAs) to guide the search within a narrow re- gion of its learned surface. In our study, we operate AF2 without MSAs or initial templates, forcing it to sample its entire energy landscape — more akin to an ab initio approach. Among over 7,000 proteins, a fraction fold using sequence alone, highlighting the smoothness of AF2’s learned energy surface. Additionally, by combining recycling and iterative predictions, we discover multiple AF2 interme- diate structures in good agreement with known experimental data. AF2 appears to follow a “local first, global later” folding mechanism. For designed proteins with more optimized local interactions, AF2’s energy landscape is too smooth to detect intermediates even when it should. Our current work sheds new light on what AF2 has learned and opens exciting possibilities to advance our understanding of protein folding and for experimental discovery of folding intermediates.
==== Body
pmc
