The latent space is able to capture protein stability in its structure. The ancestral sequences are often associated with enhanced stability compared to their extant counterparts . We hypothesized that the structure of the VAE latent space might encode stability and predict that the more stable variants of our target protein, DhaA, would be located closer to the origin compared to the wild type. To test this hypothesis, we mapped two sets of experimentally measured stability values to the latent space of Model 1. The first set consisted of six ancestral sequences from the previous protein engineering campaign of the thoroughly characterized dehalogenases: DbjA, DbeA, DhaA, DmxA, and DmmA . The second set consisted of 24 previously engineered DhaA variants incorporating both evolutionary and energy-based mutations based on the FireProt method . The sequences were aligned to those in the training MSA and mapped to the latent space. Their latent space coordinates were closer to the origin of the latent space (Fig. ), supporting the notion that the latent space captures the information about the stability landscape. The observations were also recapitulated for HLD I-II dataset and Model 2.