TAPS: A traveling-salesman based automated path searching method for functional conformational changes of biological macromolecules
KAUST Grant NumberOSR-2016-CRG5-3007
Embargo End Date2020-03-28
Permanent link to this recordhttp://hdl.handle.net/10754/668602
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AbstractLocating the minimum free energy paths (MFEPs) between two conformational states is among the most important tasks of biomolecular simulations. For example, knowledge of the MFEP is critical for focusing the effort of unbiased simulations that are used for the construction of Markov state models to the biologically relevant regions of the system. Typically, existing path searching methods perform local sampling around the path nodes in a pre-selected collective variable (CV) space to allow a gradual downhill evolution of the path toward the MFEP. Despite the wide application of such a strategy, the gradual path evolution and the non-trivial a priori choice of CVs are also limiting its overall efficiency and automation. Here we demonstrate that non-local perpendicular sampling can be pursued to accelerate the search, provided that all nodes are reordered thereafter via a traveling-salesman scheme. Moreover, path-CVs can be computed on-the-fly and used as a coordinate system, minimizing the necessary prior knowledge about the system. Our traveling-salesman based automated path searching method achieves a 5-8 times speedup over the string method with swarms-of-trajectories for two peptide systems in vacuum and solution, making it a promising method for obtaining initial pathways when investigating functional conformational changes between a pair of structures.
CitationZhu, L., Sheong, F. K., Cao, S., Liu, S., Unarta, I. C., & Huang, X. (2019). TAPS: A traveling-salesman based automated path searching method for functional conformational changes of biological macromolecules. The Journal of Chemical Physics, 150(12), 124105. doi:10.1063/1.5082633
SponsorsThis work was supported by the Hong Kong Research Grant Council [Grant Nos. HKUST C6009-15G, 16307718, 16318816, and AoE/P-705/16], King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) (No. OSR-2016-CRG5-3007), Shenzhen Science and Technology Innovation Committee (No. JCYJ20170413173837121), Guangzhou Science Technology and Innovation Commission (No. 201704030116), and Innovation and Technology Commission (No. ITC-CNERC14SC01). X.H. is the Padma Harilela Associate Professor of Science.
JournalThe Journal of Chemical Physics