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• W4287447809 abstract "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." @default.
• W4287447809 created "2022-07-25" @default.
• W4287447809 creator A5074728289 @default.
• W4287447809 creator A5080107164 @default.
• W4287447809 date "2022-08-18" @default.
• W4287447809 modified "2023-10-14" @default.
• W4287447809 title "Protein folding intermediates on the dimensionality reduced landscape with UMAP and native contact likelihood" @default.
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• W4287447809 doi "https://doi.org/10.1063/5.0099094" @default.
• W4287447809 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35987583" @default.
• W4287447809 hasPublicationYear "2022" @default.
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