Proteins, as the primary executors of physiological activity, serve as a key factor in disease diagnosis and treatment. Research into their structures, functions, and interactions is essential to better understand disease mechanisms and potential therapies. DeepMind’s AlphaFold2, a deep-learning protein structure prediction model, has proven to be remarkably accurate, and it is widely employed in various aspects of diagnostic research, such as the study of disease biomarkers, microorganism pathogenicity, antigen-antibody structures, and missense mutations. Thus, AlphaFold2 serves as an exceptional tool to bridge fundamental protein research with breakthroughs in disease diagnosis, developments in diagnostic strategies, and the design of novel therapeutic approaches and enhancements in precision medicine. This review outlines the architecture, highlights, and limitations of AlphaFold2, placing particular emphasis on its applications within diagnostic research grounded in disciplines such as immunology, biochemistry, molecular biology, and microbiology.

Background: Cystine stones, a rare but recurrent type of kidney stones, primarily result from cystinuria, an inherited disorder caused by mutations in the genes SLC3A1 and SLC7A9 , which encode renal cystine transporters. These mutations impair cystine reabsorption, resulting in elevated urinary cystine concentrations and stone formation. Current diagnostic methods are limited, particularly for detecting molecular-level dysfunctions. We aimed to develop a nonradioactive method for functional assessment of cystine transporters and mutation-specific pathologies. Methods: We designed an innovative diagnostic approach combining a selenocystine-based fluorescence assay with structural predictions using AlphaFold to rapidly and accurately assess cystine transporter function and the molecular impacts of genetic mutations. Results: Our assay demonstrated comparable transport efficiencies of cystine and selenocystine by the SLC3A1/SLC7A9 complex, and effectively differentiated mild, moderate, and severe functional impairments associated with known clinical mutations, including A354T and P482L. Structural modeling further provided mechanistic insights into mutation-induced dysfunctions. Conclusion: This integrated approach—combining a sensitive selenocystine fluorescence assay with AI-powered structural analysis—enables rapid, precise diagnosis of cystinuria variants and delivers mechanistic insights for personalized therapeutic strategies.

Cystine stones account for 1%–2% of adult and up to 10% of pediatric kidney stones. They result from cystinuria, an autosomal recessive disorder caus

Selenium is an essential trace element incorporated into selenoproteins as selenocysteine, yet the intestinal cellular programs associated with selenium utilization remain poorly defined. Here, we performed a large-scale single-cell transcriptomic analysis of 169,068 human enterocytes from 105 donors to systematically profile nine candidate selenium transporter systems and their relationship to selenoprotein expression. Among all transporters examined, the b ⁰⁺ amino acid transporter system (SLC3A1/SLC7A9) showed the strongest and most maturation-independent association with selenoproteins, including SELENOP (Spearman r = 0.489) and GPX4 ( r = 0.392), with enrichment across 21 of 24 detected selenoproteins in b ⁰⁺ -complete versus transporter-negative enterocytes. These associations were robust across individual donors and confirmed by pseudobulk validation, and were only partially explained by enterocyte maturation state, intestinal segment, and sequencing depth after covariate adjustment, indicating both differentiation-dependent and differentiation-independent components. Furthermore, enterocytes carrying the b ⁰⁺ complex expressed a non-canonical LRP repertoire (LRP1, LRP5 and LRP6) rather than the canonical SELENOP receptors LRP2 and LRP8; this co-expression was maturation-dependent, nominating these LRPs as candidate intestinal SELENOP-handling receptors. Together, these single-cell data identify b ⁰⁺ transporter expression as a marker of a selenoprotein-enriched enterocyte state in the human intestine.