While many copolymer conjugates were investigated in our initial study, only a small fraction of SCNPs demonstrated significant compactness and flexibility. This is not surprising as designing self-folding behavior in synthetic macromolecules remains challenging. To facilitate further control over these higher order behaviors, we utilized ML techniques to identify samples that demonstrate compactness and protein-like flexibility. To do so, we began by training multiple ENets to make predictions on SCNP parameters of interest (Rg, Rh, Rg/Rh, Porod exponent) directly from chemical representations of polymer conjugate chemistry and chosen molecular descriptors As we were particularly interested in designing compact samples with protein-like features, 30 EPO-SCNPs were proposed for synthesis and characterization with low predicted Rg and high predicted Porod exponent (see Materials and Methods). Since many of these samples demonstrated limited solubility, likely due to large hydrophobic monomer fractions (Table ), DLS and SAXS characterization were completed on 12 of 30 samples. Remarkably, Figure demonstrates that ML-informed design appropriately identified numerous EPO-SCNPs exhibiting more similar physical measurements to the PDB sampled proteins than prior EPO-SCNPs measured during our random screen. While only 5% of SCNPs in the random screen demonstrated Porod exponent ≥ 3.5, ~58% of EPO-SCNPs proposed by the ENets demonstrated Porod exponents above this threshold. Further, these differences are readily observed in the distinction in median Rg and Porod exponent between initial EPO-SCNPs (8.4 nm and 2.7) and ENet proposed EPO-SCNPs (5.7 nm and 3.5). As Rg and Porod exponent shifted towards more protein-like values, Rh remained large for EPO-SCNPs (Figure ). The Rg/Rh of an ideal sphere is 0.775, however, some of the characterized SCNPs exhibited Rg/Rh < 0.775. This phenomenon was even more prevalent in the ML predicted EPO-SCNPs. A few potential reasons for this include adoption of a core-shell structure or molten globule with tight packing of the hydrophobic alkyl side chain surrounded by a more dispersed shell. Because ENet models were generally successful in predicting more compact EPO-SCNPs, we sought to understand the underlying chemical designs that led to compactness within our study.