As a second approach applied to 3445 MOFs, PCA was instrumental in identifying significant dimensions contributing to variance within MOF textural properties enhancing the MOF textural space exploration. Including PC1 and PC2 in the AL process contributed to robust model training and enhanced predictive accuracy. Furthermore, an in-depth analysis of textural properties within the navigated MOF subset shows the preservation of the overall distribution of textural properties compared with the available data. This diverse and extensive coverage across MOF textural properties is observed in the comparative histograms. This fact is proof of the navigation process's effectiveness in encapsulating and representing essential material characteristics within the navigated subset.