# Contact-Map-Driven Exploration of Heterogeneous Protein-Folding Paths

## TL;DR

This paper introduces a new method for exploring different protein-folding paths using contact maps, improving accuracy and reliability compared to previous approaches.

## Contribution

The paper introduces a topologically informed metric, a reformulated folding path generation, and a new structural back-mapping algorithm for heterogeneous protein-folding paths.

## Key findings

- The enhanced contact-map-based strategy reliably generates structurally sound folding intermediates.
- The method successfully identifies alternative folding mechanisms of a multifolding-pathway protein.
- The approach outperforms previous strategies by reducing irrelevant intermediates and aligning with molecular dynamics results.

## Abstract

We have recently
shown how physically realizable protein-folding
pathways can be generated using directed walks in the space of inter-residue
contact-maps; combined with a back-transformation to move from protein
contact-maps to Cartesian coordinates, we have demonstrated how this
approach can generate protein-folding trajectory ensembles without
recourse to molecular dynamics. In this article, we demonstrate that
this framework can be used to study a challenging protein-folding
problem that is known to exhibit two different folding paths which
were previously identified through molecular dynamics simulation at
several different temperatures. From the viewpoint of protein-folding
mechanism prediction, this particular problem is extremely challenging
to address, specifically involving folding to an identical nontrivial
compact native structure along distinct pathways defined by heterogeneous
secondary structural elements. Here, we show how our previously reported
contact-map-based protein-folding strategy can be significantly enhanced
to enable accurate and robust prediction of heterogeneous folding
paths by (i) introducing a novel topologically informed metric for
comparing two protein contact maps, (ii) reformulating our graph-represented
folding path generation, and (iii) introducing a new and more reliable
structural back-mapping algorithm. These changes improve the reliability
of generating structurally sound folding intermediates and dramatically
decrease the number of physically irrelevant folding intermediates
generated by our previous simulation strategy. Most importantly, we
demonstrate how our enhanced folding algorithm can successfully identify
the alternative folding mechanisms of a multifolding-pathway protein,
in line with direct molecular dynamics simulations.