Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.
Bibliographical noteKAUST Repository Item: Exported on 2022-06-03
Acknowledgements: We acknowledge the support from National Basic Research Program of China (973 program, No. 2013CB834703), Hong Kong Research Grants Council Nos. 16304215, 16302214, C6009-15G, F-HKUST605/15, M-HKUST601/13, AoE/M-09/12, and T13-607/12R. This research made use of the resources of the Supercomputing Laboratory at King Abdullah University of Science and Technology. X.H. is the Padma Harilela Associate Professor of Science. F.K.S. acknowledges support from the Hong Kong Ph.D. Fellowship Scheme 2012/13 (No. PF11-08816).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Physical and Theoretical Chemistry