While the average density values indicate the cumulative impact of a particular building block, we find relatively large standard deviations (cf. Fig. ). For a more detailed picture of the occurrences of building blocks in a particular subset of the library, we perform the Zscore analysis introduced in Sec. II D. Fig. shows the corresponding results for the molecules with the highest density values (i.e., the top 10% subset) with clear and distinct trends. Consistent with our previous analysis, we observe very large Z-score values for and thus a strong overexpression of B7 and B12. B13 (thiazole) also shows a large Z-score, and so do to a lesser extent B2 (S-linker) and B3 (O-linker) as well. These moieties are clearly favorable if high-density compounds are desired. In addition to assessing the high-density regime, we employ the hypergeometric distribution analysis to identify the prevalence of building blocks in the complete spectrum of density values. For this, we sort our virtual li- brary by increasing density values, divide it into ten equal segments, and perform our analysis within each of these subsets as shown in Fig. . Based on the data from this analysis, we can identify trends in the impact of individual building blocks on the density of organic molecules. The Z-score of building blocks B2, B7, B12, and B13 increases with increasing density values, indicating a direct correlation, whereas it decreases for B1, B4, B9, B10, and B15, indicating an inverse correlation. The former are thus suitable to design organic molecules with higher density, and the latter could be used to achieve compounds with lower density. These findings are consistent with our prior analysis.