In order to validate our workflow more rigorously, it is necessary to demonstrate not just ligand coordination atom assignment but the successful generation and evaluation of DFT properties of realistic TMCs. We sought to identify a subset of TMCs with previously unseen (i.e., in the CSD) combinations of ligands with a transition metal. We selected Ti(IV) as our metal center, motivated in part by the fact that transition metal complexes based on Ti(IV) have applications in catalysis, with their performance as chiral and polymerization catalysts being particularly well-documented in the literature, along with more recent applications that indicate their promise as anticancer agents. To choose a coordination symmetry that would result in novel complexes, we considered a previous analysis of the theoretical space of possible TMCs. This analysis distinguished TMCs by the symmetry of the placement of unique ligands around a metal center in an octahedral geometry. Enumeration of these unique symmetry classes and analysis of their relative abundance in the CSD identified equatorial asymmetric (EA) and mer asymmetric trans (MAT) symmetries as under-sampled in experimental, structurally characterized TMCs (SI Appendix, Figure ). We selected these EA and MAT symmetry classes for use in testing our integrated coordination prediction and structure generation workflow, specifically generating complexes with novel metal-ligand coordination never observed in the CSD as an opportunity for generating structures with new combinations of metals and ligands (SI Appendix, Tables S16-S17). these are the only ligands from which EA and MAT structures may be generated. We separate the set of all predicted monodentate, bidentate, and tridentate ligands into combinations of ligands that will yield overall neutral complexes in combination with the EA and MAT symmetries (i.e., 0 to -1 charge for monodentate, 0 to -2 charge for bidentate, and -1 to -2 charge for tridentate, SI Appendix, Tables ). Using these seven subsets, we enumerated all possible combinations of ligand charge and denticity to produce in a net neutral overall complex charged when coordinated to Ti(IV) and randomly select five ligands from each subset to provide a sufficiently large space of possible structures, resulting in 1,175 unique structures (SI Appendix, Tables ). From these 35 total ligands, our models predict the coordination atoms of 32 cases correctly, which corresponds to a molecular accuracy of 91.4% that is 4.5% above our model's baseline performance on the set-aside test set. Examining the cases where the model performs incorrectly, we note two instances of true bidentate ligands with one oxygen and one nitrogen coordinating atom being incorrectly predicted as tridentate. In both cases, our models correctly identify the two true coordinating atoms and incorrectly predict a nearby nitrogen atom as coordinating, resulting in the overall classification as tridentate. In the third case of an incorrect model prediction, a true monodentate ligand with a sulfur coordinating atom is correctly identified as monodentate but with an incorrectly predicted carbon coordinating atom. Inspection of the raw prediction probabilities generated by the model reveal higher probabilities for the carbon atoms in the ligand's benzene substructure, suggesting the model was initially predicting this ligand to have a haptic coordination mode along the conjugated π system along the carbon ring (SI Appendix, Table ). Because the coordinating atoms count prediction model was more confident in the monodentate classification than the coordinating atoms identification model, only the single highest probability coordinating atom was returned, resulting in the incorrect prediction of a single carbon coordinating atom.