Integrative motif conservation, entropy, and hotspot analysis uncovers class-specific transmembrane architecture in human olfactory receptors

整合基序保守性、熵和热点分析揭示人类嗅觉受体中类别特异性的跨膜结构

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Abstract

Human olfactory receptors (ORs), the largest subfamily of Class A G protein-coupled receptors (GPCRs), mediate odor recognition through conserved structural elements embedded within their transmembrane (TM) helices. Despite sharing a common GPCR scaffold, ORs exhibit extreme sequence divergence, complicating efforts to define class-specific structural constraints. Here, this comprehensive study presents a motif-centric and spatially resolved computational framework that integrates TM-localized motif conservation, unsupervised stratification, functional hotspot detection, and positional entropy analysis to resolve conserved structural organization within the human OR repertoire. Analysis of 420 high-confidence functional human ORs reveals that conserved TM motif architectures are sufficient to recapitulate the canonical Class I and Class II division through unsupervised clustering of motif conservation features, followed by biology-informed post hoc labeling. While motifs in TM3 and TM6 exhibit broad conservation consistent with core GPCR activation mechanisms, motif clustering and hotspot formation are strikingly enriched in TM1 and TM7, identifying these helices as major sites of structural constraint. Positional entropy analysis further distinguishes rigidly localized motifs from spatially flexible elements, revealing heterogeneous constraint landscapes across TM domains. Class-wise comparisons demonstrate a pronounced enrichment of TM1- and TM7-associated hotspots in Class II receptors. Together, these results reveal that conserved TM motif organization encodes class identity, domain-specific constraint patterns, and motif-dense microdomains within human ORs. This framework provides a mechanistically interpretable foundation for structure-guided modeling, functional mutagenesis, and evolutionary analysis of olfactory receptor signaling.

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