Stolzer, M. | Search bioRxiv

bioRxiv2025

Vector semantics of multidomain protein architectures

Multidomain proteins are mosaics of domains, protein modules that are associated with a specific structure or function and are found in diverse combinations. This modular organization facilitates the evolution of novel protein functions, but the principles that govern the relationship between the domain content of a protein and its function is poorly understood. In particular, do domains always contribute the same function, or does the functional contribution of a domain depend on the neighboring domains in the protein? To answer this question, we used vector embeddings, which account for local contextual signals, to model the protein domain content of multidomain proteins. We observe that multidomain architectures that are semantically similar share more functional attributes than multidomain architectures selected based on domain content similarity, alone, suggesting that context is important for understanding the relationship between domain content and protein function. Surprisingly, vector semantics also identified multidomain architecture pairs with significantly high functional similarity, despite having no domains in common at all, suggesting that vector semantics may be discovering domain "synonyms". Taken together, our results underscore the importance of contextual models for understanding the interplay between domain architecture evolution and functional innovation in multidomain proteins.

evolutionary biology↗

bioRxiv2025

Evolution of the Metazoan Protein Domain Toolkit Revealed by a Birth-Death-Gain Model

Domains, sequence fragments that encode protein modules with a distinct structure and function, are the basic building blocks of proteins. The set of domains encoded in the genome serves as the functional toolkit of the species. Here, we use a phylogenetic Birth-Death-Gain model to investigate the evolution of this protein toolkit in metazoa. Given a species tree and the set of protein domain families in each present-day species, this approach estimates the most likely rates of domain origination, duplication and loss. Statistical hierarchical clustering of domain family rates reveals sets of domains with similar rate profiles, consistent with groups of domains evolving in concert. Moreover, we find that domains with similar functions tend to have similar rate profiles. Interestingly, domains with functions associated with metazoan innovations, including immune response, cell adhesion, tissue repair, and signal transduction, tend to have the fastest rates. We further infer the expected ancestral domain content and the history of domain family gains, losses, expansions, and contractions on each branch of the species tree. In contrast to recent reports of widespread loss during metazoan evolution, we observe little evidence of genome streamlining. Rather, our analysis reveals an ongoing process of domain family replacement and resizing, consistent with extensive remodeling of the protein domain repertoire. The use of a powerful, probabilistic Birth-Death-Gain model reveals an unexpected level of genomic plasticity and a striking harmony between the evolution of domain usage in metazoan proteins and organismal innovation.

evolutionary biology↗