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- Title
Pathfinder: Protein folding pathway prediction based on conformational sampling.
- Authors
Huang, Zhaohong; Cui, Xinyue; Xia, Yuhao; Zhao, Kailong; Zhang, Guijun
- Abstract
The study of protein folding mechanism is a challenge in molecular biology, which is of great significance for revealing the movement rules of biological macromolecules, understanding the pathogenic mechanism of folding diseases, and designing protein engineering materials. Based on the hypothesis that the conformational sampling trajectory contain the information of folding pathway, we propose a protein folding pathway prediction algorithm named Pathfinder. Firstly, Pathfinder performs large-scale sampling of the conformational space and clusters the decoys obtained in the sampling. The heterogeneous conformations obtained by clustering are named seed states. Then, a resampling algorithm that is not constrained by the local energy basin is designed to obtain the transition probabilities of seed states. Finally, protein folding pathways are inferred from the maximum transition probabilities of seed states. The proposed Pathfinder is tested on our developed test set (34 proteins). For 11 widely studied proteins, we correctly predicted their folding pathways and specifically analyzed 5 of them. For 13 proteins, we predicted their folding pathways to be further verified by biological experiments. For 6 proteins, we analyzed the reasons for the low prediction accuracy. For the other 4 proteins without biological experiment results, potential folding pathways were predicted to provide new insights into protein folding mechanism. The results reveal that structural analogs may have different folding pathways to express different biological functions, homologous proteins may contain common folding pathways, and α-helices may be more prone to early protein folding than β-strands. Author summary: The study of protein folding mechanism is an important part of basic science and has vital significance in many aspects. The key to the study of protein folding mechanism is to capture the conformational changes from the fast protein folding process. Biological experiments are more difficult to obtain protein metastable structures than computational methods. It is computationally expensive to simulate the complete folding pathway of macromolecular proteins by molecular dynamics methods. Here, we design a protein folding pathway prediction method based on conformational sampling to provide new ideas for existing research. This method obtains the structural information of the intermediate state through large-scale sampling and clustering, combines the resampling algorithm to explore the transition probability of the intermediate state, and predicts the protein folding pathway. The results show that we validate the method on five widely studied proteins, and also reveal the folding mechanism of some proteins. And Pathfinder complements the existing protein folding data from the perspective of computational simulation, which needs to be further verified by biological experiments. Finally, Pathfinder predicts unresolved protein folding pathways, providing insights into unknown folding mechanisms.
- Subjects
PROTEIN folding; MOLECULAR dynamics; BIOMACROMOLECULES; MOLECULAR biology; PROTEIN structure; MACROMOLECULAR dynamics
- Publication
PLoS Computational Biology, 2023, Vol 19, Issue 9, p1
- ISSN
1553-734X
- Publication type
Article
- DOI
10.1371/journal.pcbi.1011438