Due to the inherent sequential and structural similarities among kinases, capturing their distinctive features for targeted ligand design presents a desirable yet challenging task. Modi & Dunbrack 33 facilitated this process by curating a multiple sequence alignment guided by kinase secondary structure regions, potentially enabling the capture of subtle variations in domain architectures. This refined MSA served as a valuable prior for adapting protein embeddings generated from AlphaFold2, ESM2 and ProtBert models. Following padding and trimming procedures, these embeddings were flattened, scaled, and subsequently visualized using Uniform Manifold Approximation and Projection (UMAP). As depicted in Figure , the analysis reveals a significant impact of padding, which effectively streamed evolutionary information from MSA to protein embeddings and aligned clusters with kinase family annotations. Trimming, while slightly dispersing these clusters, maintained the overall structural configuration.