TargetSNPdb: A Database of Preliminary Analysis Data of the Impact of nsSNPs on Drug Targets, Drug-metabolizing Enzymes, and Disease-associated Genes in Humans

Aims: Non-synonymous single nucleotide polymorphisms (nsSNPs) are variations in DNA that can affect protein structure and function and are known to cause various diseases, such as heart disease, diabetes, and cancer. For instance, changing glutamic acid to valine in the hemoglobin beta gene leads to sickle cell anemia. nsSNPs found in genes associated with drug targets or drug-metabolizing enzymes can influence how individuals respond to drugs and their susceptibility to certain diseases. Understanding nsSNPs is essential for comprehending how genetic variations impact protein functionality and contribute to disease onset, which is crucial for accurate diagnosis and treatment decisions. Using computational tools to analyse protein sequence and structure data significantly increases the prediction efficiency of the impact caused by these nsSNPs.

Methods: The analysis results obtained from several computational tools (such as SIFT, PolyPhen, AutoDock, and GROMACS) relevant to the study of the impact of amino acid residue substitutions were integrated into existent information records from the literature and genetic association databases. These tools enable the combination of results from a variety of different approaches to evaluate the potential impact of nsSNPs on protein function.

Results: We have developed TargetSNPdb, a comprehensive database that contains computational predictions of the structural and functional impact of nsSNPs in human protein-coding genes, including drug target and drug-metabolizing enzyme-encoding genes.

Conclusion: TargetSNPdb provides nsSNP data, disease associations, and drug information. Molecular modeling helps understand genetic variations, drug responses, and diseases. Potential applications of TargetSNPdb include prioritising nsSNPs for association and experimental studies.