TY  - JOUR
AU  - Rani, Aishwarya
AU  - Gangwar, Shalesh
AU  - Sharma, Neha
AU  - Raza, Khalid
AU  - Gupta, Sameer
AU  - Toor, Devinder
PY  - 2026
DA  - 2026/10/05
TI  - In Silico Screening of AHSG Missense Variants and Exploring Their Interaction with BMP-10 in Cardiovascular Diseases
JO  - OBM Genetics
SP  - 361
VL  - 10
IS  - 04
AB  - Fetuin-A, encoded by the AHSG gene, is a hepatokine that regulates metabolism, ectopic calcification, and cardiovascular homeostasis. Beyond mineral sequestration, it binds Bone Morphogenetic Protein (BMP) ligands, modulating their extracellular availability. BMP-10 supports endothelial integrity, vascular remodeling, and signaling through BMP receptor type 2 (BMPR2). Impaired BMP-10 signaling is linked to cardiovascular diseases (CVDs). Non-synonymous single-nucleotide polymorphisms (nsSNPs) in AHSG can alter fetuin-A structure and potentially disrupt its interaction with BMP-10. A total of 398 missense nsSNPs were analyzed using PredictSNP (functional impact), DUET, I-Mutant 2.0, and DynaMut2 (stability), ConSurf (conservation), and Project HOPE (structural effects). Further, the selected variants underwent 100-ns molecular dynamics simulations, and molecular docking was performed with BMP-10-BMPR2. Using the computational framework, seven high-confidence deleterious variants- I48T, I80S, I82T, E86G, R103S, V142G, F125S- plus two clinically relevant variants (M248T, S256T) from reported GWAS literature were identified. MD simulations showed significant deviations: S256T displayed the greatest conformational shift from wild type, while E86G increased solvent exposure and flexibility. Docking investigations predicted a stable interaction between wild-type fetuin-A and the BMP-10-BMPR2 complex. Most variants showed reduced predicted binding interactions relative to wild type. These computational findings provide hypothesis-generating evidence of a structural basis for how AHSG variants may impair BMP-10 regulation, potentially contributing to cardiovascular dysregulation. The proposed framework may help prioritize variants for targeted experimental and genotype-phenotype studies to determine their functional and clinical relevance.
SN  - 2577-5790
UR  - https://doi.org/10.21926/obm.genet.2604361
DO  - 10.21926/obm.genet.2604361
ID  - Rani2026
ER  -