In-silico Study of Protein Modeling of ADAM33 Variants (SNP) in Asian Populations with Asthma

Asthma is a chronic respiratory disease with a prevalence that continues to increase, influenced by genetic factors and environmental changes. The ADAM33 gene has been consistently associated with susceptibility to asthma, but the functional impact of its variants on the protein remains unclear, especially in diverse Asian populations. This study aims to assess how single nucleotide polymorphisms (SNPs) in the ADAM33 gene affect the structure and function of the resulting protein, as well as their potential contribution to asthma pathogenesis. An in-silico approach was used: the relevant gene sequences were obtained, the ADAM33 catalytic domain was modeled using AlphaFold/ColabFold, and candidate SNPs were identified from UniProt. Protein stability and functional consequences were then analyzed using MuPro and PolyPhen-2. Results showed that all SNPs studied disrupted ADAM33 stability to varying degrees, with some causing significant conformational changes. Specifically, SNP rs41467948 produced the greatest destabilizing effect, while rs41534847 was predicted to be potentially deleterious despite its minimal impact on stability. These findings suggest that SNP-induced changes in ADAM33 may influence airway remodeling and disease mechanisms in asthma. They highlight the value of integrated computational methods for prioritizing specific prominent variants among understudied Asian populations for further functional analysis and therapeutic targeting.