In the pipeline approach, the pipeline-ascent approach has the best bins test performance compared to all other approaches. Δabins(pipeline-ascent) is almost halved compared to Δabins(ascent). Additional histogram analyses of duplicate conformer appearance frequency over the re-optimization process in terms of ropt have been conducted (Figure ). The chance of getting duplicate conformers with the pipeline-ascent priority lists is approximately halved during the first 30% of the re-optimizations compared to the ascent approach. The mean PGMT of the pipeline-x approach is similar to the ascent approach. Mean PGMT = 0.14 implies that approximately 14% of the conformers in the priority need to be re-optimized before obtaining the global minimum structure. However, the mean Δabins value of the pipeline-x approach is noticeably lower than the pipeline-ascent approach. The pipeline-mix approach, with the parameter Q set to 0.2, improves the bins test parameter without significantly reducing the global minimum test performance. With this setting, the global minimum structure can be obtained in the first 30% of the re-optimizations about 80% of the time (Figure ). We also investigated whether further steps improve the performance (SI Section 6.B). The aim is to extract and use the energy and structural data from the re-optimized conformers to improve the proposed priority list. The ideas that have been attempted include: 1) Sequential clustering process with certain FF structures replaced by the re-optimized DFT structures in the input SDF; 2) Varying the x parameter according to percentage of structural duplicates in the group of re-optimized conformers when using the pipeline-x method; 3) Prioritizing conformers from the same clusters as the most stable DFT re-optimized structure; 4) Using clusters-distance array from the K-Means clustering process to make the prioritization decisions. Overall, only marginal improvements in the global minimum test were observed (Figure , marked as post-processing). This demonstrates the effectiveness of the standard pipeline approaches. Implementing the pipeline approach in generating the priority list led to a shift in data points toward the bottom left corner in the mean PGMT vs mean Δabins plot. The clustering process with dihedral angles as descriptors offered by the pipeline effectively groups conformationally similar conformers, which led to the noticeable improvement in the bins test parameter by the pipeline approaches. Differences in performance are also reflected in the mean overall parameter (Figure ), calculated from the mean Δabins and mean PGMT. The overall parameters for all other pipeline approaches are noticeably lower compared to the nonclustering approaches. Overall, the clustering approaches outperform the non-pipeline approach in prioritizing the global minimum structure and without duplications from different force field (FF) structures re-optimizing to same structure.