# Unavailability of experimental 3D structural data on protein folding dynamics and necessity for a new generation of structure prediction methods in this context

## TL;DR

This paper highlights the lack of 3D structural data on protein folding intermediates and explores the need for new prediction methods to study folding dynamics and related diseases.

## Contribution

A centralized resource of available 3D structural data on folding intermediates and an assessment of current structure prediction methods for these intermediates.

## Key findings

- Only six studies provide 3D structural data on folding intermediates, with limited coverage.
- AlphaFold2 performs poorly in predicting co-translational folding intermediates.
- New methods incorporating folding dynamics show promise for predicting non-native structures.

## Abstract

Protein folding is a dynamic process during which a protein’s amino acid sequence undergoes a series of 3D conformational changes en route to reaching a native 3D structure; these conformations are called folding intermediates. While data on native 3D structures are abundant, data on 3D structures of non-native intermediates remain sparse, due to limitations of current technologies for experimental determination of 3D structures. Yet, analyzing folding intermediates is crucial for understanding folding dynamics and misfolding-related diseases. Hence, we search the literature for available (experimentally and computationally obtained) 3D structural data on folding intermediates, organizing the data in a centralized resource. Also, we assess whether existing methods, designed for predicting native structures, can be utilized to predict structures of non-native intermediates.

Our literature search reveals six studies that provide 3D structural data on folding intermediates (two for post-translational and four for co-translational folding), each focused on a single protein, with 2–4 intermediates. Our assessment shows that an established method for predicting native structures, AlphaFold2, does not perform well for non-native intermediates in the context of co-translational folding; a recent study on post-translational folding concluded the same for even more existing methods. Yet, we identify in the literature recent pioneering methods designed explicitly to predict 3D structures of folding intermediates by incorporating intrinsic biophysical characteristics of folding dynamics, which show promise. This study assesses the current landscape and future directions of the field of 3D structural analysis of protein folding dynamics.

https://github.com/Aywells/3Dpfi or https://academicweb.nd.edu/∼cone/3Dpfi/.