## 4 Discussion and Conclusions  
In conclusion, ssPINE-POKY offers a valuable solution for analyzing complex solid-state NMR (ssNMR) data in structural biology. The integration of ssPINE into the user-friendly graphical interface of ssPINE-POKY, in conjunction with the widely used POKY software for protein structure determination, significantly enhances software functionality and ease of use. Researchers can quickly submit ssPINE jobs, visualize results, and expedite the determination of 3D structures. This combined tool addresses the challenges of analyzing complex ssNMR data, especially for large macromolecular assemblies with high structural complexity and low solubility. This integration positions ssPINE-POKY as a key tool for structural biologists using ssNMR spectroscopy.  
The ssPINE-POKY interface simplifies submission, integrates results into ongoing projects, and allows customizable visualization, empowering users to interpret outcomes according to their preferences. However, there are still notable limitations to be addressed. The quality of ssNMR data, particularly due to overlapping spectral signals, poses an ongoing challenge, leading to time-consuming processes for identifying peaks and analyzing data. Dealing with complex spectra containing multiple peaks and overlapping signals requires further improvement.  
Looking forward, we aim to improve ssPINE-POKY by providing more options for users to customize their experience, adding features to make the initial steps of NMR assignment quicker, adding pre-assignment and labeling capabilities to expedite NMR assignment, implementing advanced spectral processing techniques for peak separation, and integrating automatic structural calculation based on NMR assignments. Additionally, considering the inclusion of new experiments to ssPINE's supported repertoire would provide valuable structural information. By addressing these limitations and implementing improvements, ssPINE-POKY can enhance usability, accuracy, and efficiency in structural biology research.  
Conceptualization, W.L.; methodology, A.E.L.G., M.R. and W.L.; software, A.E.L.G., M.R. and W.L.; validation, A.E.L.G. and W.L.; formal analysis, A.E.L.G. and W.L.; investigation, A.E.L.G.; resources, W.L.; data curation, A.E.L.G.; writing--original draft preparation, A.E.L.G. and W.L.; writing--review and editing, A.E.L.G. and W.L.; visualization, A.E.L.G. and W.L.; supervision, W.L.; project administration, W.L.; funding acquisition, W.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Science Foundation, grant numbers DBI-2413041, DBI-2051595 and DBI-1902076 to W.L., and the University of Colorado Denver.  
Not applicable.  
The ssPINE-POKY program presented in this study is openly available as a plugin in the POKY suite at [[https://poky.clas.ucdenver.edu](https://poky.clas.ucdenver.edu)]([https://poky.clas.ucdenver.edu](https://poky.clas.ucdenver.edu)) (accessed on 30 May 2025). No new data were created or analyzed in this study. One may simulate datasets as demonstrated in [[https://youtu.be/HmLubuDoZxM](https://youtu.be/HmLubuDoZxM)]([https://youtu.be/HmLubuDoZxM](https://youtu.be/HmLubuDoZxM)) (accessed on 30 May 2025) using POKY.  
**Acknowledgments:** We acknowledge useful discussions in the NMR POKY/SPARKY user group ([[https://groups.google.com/g/nmr-sparsky](https://groups.google.com/g/nmr-sparsky)]([https://groups.google.com/g/nmr-sparsky](https://groups.google.com/g/nmr-sparsky)) (accessed on 30 May 2025)).  
**Conflicts of Interest:** The authors declare no conflicts of interest.