Virus-targeted host proteins evolve under dual selective pressures. Negative selection preserves within-host interactions, while positive selection promotes adaptive changes to evade viral engagement. Viral and endogenous within-host partners can compete for binding, bringing distinct pressures together on the same interaction interface. Yet, the spatial organization of distinct selective pressures across virus-targeted host proteins, and how such pressures manifest across diverse interaction contexts, remains largely unknown. Here, we integrate an evolutionarily annotated map of human-virus protein-protein interactions (PPIs) with intra-protein residue-residue contact maps to probe the spatial organization of residue-level selective pressures across PPI interfaces of virus-targeted host proteins. Across all PPI interfaces collectively, we find that residues under positive selection are spatially clustered, whereas those under negative selection are broadly dispersed, with additional spatial segregation between positive and strongly negatively selected sites. Moreover, while positive selection is unevenly distributed across interfaces bound exclusively by viral proteins (exogenous-specific), they are more uniformly distributed across interfaces shared between viral and within-host partners (mimic-targeted), suggesting that adaptive pressure from viral targeting acts on the entire mimic-targeted interface, whereas it acts on only a subset of the exogenous-specific interface. Strikingly, clustering of positively selected residues is more pronounced between mimic-targeted and other interface types than within exogenous- or endogenous-specific interfaces alone, suggesting that mimic-targeted interfaces may serve as focal points of adaptive evolution. Overall, our multiscale framework of PPI interfaces and residue-level contacts reveals heterogeneous, context-dependent landscapes of selective pressures across virus-targeted host proteins, providing a high-resolution view of how adaptation and constraint are intricately balanced and coordinated within the host.
Behavior change beyond intervention: an activity-theoretical perspective on human-centered design of personal health technology
IntroductionModern personal technologies, such as smartphone apps with artificial intelligence (AI) capabilities, have a significant potential for helping people make necessary changes in their behavior


