In silico screening and analysis of single-nucleotide polymorphic variants of the ABCC2 gene affecting Dubin-Johnson syndrome

Dubin-Johnson syndrome (DJS) is a benevolent genetic disorder of the liver with autosomal inheritance. It is a rare disorder characterized by an increase in conjugated bilirubin and anomaly in coproporphyrin clearance. DJS is caused by deleterious mutations in the ABCC2 gene. A polymorphism in the ABCC2 gene causes malfunctions in its ability to regulate the efflux of different organic anions, such as bilirubin, from hepatocytes to the canaliculi. Multidrug resistance protein 2 (MRP2) encoded by the ABCC2 gene is one of the main regulators of the export of bilirubin to respective sites. ABCC2 gene mutations have widely drawn attention in the pathology of DJS in various populations.

The ABCC2 gene was subjected to the National Center for Biotechnology Information (NCBI) database in 2020, and non-synonymous single-nucleotide polymorphisms (nsSNPs) and variants in untranslated regions were studied using different computational servers. SIFT, Protein variation effect analyzer, and PolyPhen-2 were used to retrieve the damaging Single-nucleotide polymorphisms (SNPs); PhD-SNP, SNPs&GO, and Protein Analysis Through Evolutionary Relationships were used to predict the association of nsSNPs with DJS; Mutation3D illustrated the location of variants in the protein; SNAP2, MutPred2, ELASPIC, and HOPE were used to predict the structural and functional effects of these mutations on MRP2; and I-mutant 3.0 and MuPro were used to determine the effects of polymorphism on the function of MRP2.

In this study, 18,947 SNPs were screened from the NCBI database, followed by a series of refinement of variants using online available servers. We concluded that 41 ABCC2 gene variants are vital etiological candidates for DJS in humans. These 41 variants had highly damaging effects on the MRP2 protein, which may lead to deficient transportation capacity, thereby affecting the efflux of bilirubin across the canalicular membrane.

In silico tools are an alternative approach for predicting the target SNPs. Hence, previously unreported variants can be considered strong etiological candidates for diseases related to MRP2.