SNUPI is a multiscale analysis framework for the prediction of structured DNA assemblies.
- v3.10 (2024-07-29)
- EtBr-binding simulations
- v3.01 (2024-01-24)
- Minor error fix
- v3.00 (2023-09-27)
- Dynamic simulations
- Restarting simulations
- GPU acceleration
- v2.01 (2022-01-18)
- Minor error fix
- v2.00 (2021-11-19)
- Analysis of wireframe or topologically-closed designs
- export of the oxDNA input file format.
- Improved modeling of the single-stranded DNA
- v1.01 (2021-02-23)
- Support for command line execution (see protocol.pdf)
- Support for mac and linux
- Minor error fix
- v1.00 (2021-01-07)
- Initial upload
- The correct version of the MATLAB Runtime should be installed.
- v3: Runtime version R2022b (9.13)
- v2: Runtime version R2019a (9.6)
- v1: Runtime version R2019a (9.6)
- Download link: http://www.mathworks.com/products/compiler/mcr/index.html
- Execute 'SNUPI.exe'
- The example result files will be saved in the 'OUTPUT' folder.
- To analyze custom design files, modify 'Input.txt'
- Open the terminal
- Move the current directory to the SNUPI folder
- Give permission to execute
- chmod +x *
- Execute SNUPI
- ./run_SNUPI.sh <mcr_directory>
- For example,
- ./run_SNUPI.sh /usr/local/MATLAB/MATLAB_Runtime/R2022b
- The result files will be saved in the 'OUTPUT' folder.
- To analyze custom design files, modify 'Input.txt'
- Open the terminal
- Move the current directory to the SNUPI folder
- Give permission to execute
- chmod +x *
- Execute SNUPI in the FILE folder using Terminal
- ./run_SNUPI.sh <mcr_directory>
- For example,
- ./run_SNUPI.sh /Applications/MATLAB/MATLAB_Runtime/R2022b
- The result files will be saved in the 'OUTPUT' folder.
- To analyze custom design files, modify 'Input.txt'
- Modify the 'Input.txt' file to assign design files.
- In the 'Input.txt' file, <lattice_type> and <file_directory> should be denoted.
- Use caDNAno design files (json and csv).
- The percentage mark ('%') represents comments
- Example designs were already assigned.
- SNUPI framework (static analysis): Rapid computational analysis of DNA origami assemblies at near-atomic resolution, ACS Nano (2021), https://doi.org/10.1021/acsnano.0c07717
- Improved model of single-stranded DNA: Characterizing and harnessing the mechanical properties of short single-stranded DNA in structured assemblies, ACS Nano (2021), https://doi.org/10.1021/acsnano.1c08861
- Partition and relocation framework (free-form structures): Predicting the free-form shape of structured DNA assemblies from their lattice-based design blueprint, ACS Nano (2022), https://doi.org/10.1021/acsnano.1c10347
- Langevin dynamics simulations: A computational model for structural dynamics and reconfiguration of DNA assemblies, Nature Communications (2023), https://doi.org/10.1038/s41467-023-42873-4
- Graph neural network (Deep SNUPI): Prediction of DNA origami shape using graph neural network, Nature Materials (2024), https://doi.org/10.1038/s41563-024-01846-8
- EtBr-binding simulations: Predicting the effect of binding molecules on the shape and mechanical properties of structured DNA assemblies, Nature Communications (2023), https://doi.org/10.1038/s41467-024-50871-3