Protein folding intermediates on the dimensionality reduced landscape with UMAP and native contact likelihood

To understand protein folding mechanisms from molecular dynamics (MD) simulations, it is important to explore not only folded/unfolded states but also representative intermediate structures on the conformational landscape. Here, we propose a novel approach to construct the landscape using the uniform manifold approximation and projection (UMAP) method, which reduces the dimensionality without losing data-point proximity. In the approach, native contact likelihood is used as feature variables rather than the conventional Cartesian coordinates or dihedral angles of protein structures. We tested the performance of UMAP for coarse-grained MD simulation trajectories of B1 domain in protein G and observed on-pathway transient structures and other metastable states on the UMAP conformational landscape. In contrast, these structures were not clearly distinguished on the dimensionality reduced landscape using principal component analysis or time-lagged independent component analysis. This approach is also useful to obtain dynamical information through Markov state modeling and would be applicable to large-scale conformational changes in many other biomacromolecules. (C) 2022 Author(s).

Automated summary

In this study, a novel approach using the UMAP method was proposed to construct protein conformational landscapes, and native contact likelihood was used as feature variables to explore intermediate structures in protein folding. This method is useful for studying large-scale conformational changes in biomacromolecules.