A bioinformatics approach to the identification of novel deleterious mutations of human TPMT through validated screening and molecular dynamics

Abstract

Polymorphisms of Thiopurine S-methyltransferase (TPMT) are known to be associated with leukemia, inflammatory bowel diseases, and more. The objective of the present study was to identify novel deleterious missense SNPs of TPMT through a comprehensive in silico protocol. The initial SNP screening protocol used to identify deleterious SNPs from the pool of all TPMT SNPs in the dbSNP database yielded an accuracy of 83.33% in identifying extremely dangerous variants. Five novel deleterious missense SNPs (W33G, W78R, V89E, W150G, and L182P) of TPMT were identified through the aforementioned screening protocol. These 5 SNPs were then subjected to conservation analysis, interaction analysis, oncogenic and phenotypic analysis, structural analysis, PTM analysis, and molecular dynamics simulations (MDS) analysis to further assess and analyze their deleterious nature. Oncogenic analysis revealed that all five SNPs are oncogenic. MDS analysis revealed that all SNPs are deleterious due to the alterations they cause in the binding energy of the wild-type protein. Plasticity-induced instability caused by most of the mutations as indicated by the MDS results has been hypothesized to be the reason for this alteration. While in vivo or in vitro protocols are more conclusive, they are often more challenging and expensive. Hence, future research endeavors targeted at TPMT polymorphisms and/or their consequences in relevant disease progressions or treatments, through in vitro or in vivo means can give a higher priority to these SNPs rather than considering the massive pool of all SNPs of TPMT.

Population-Specific Distribution of TPMT Deficiency Variants and Ancestry Proportions in Ecuadorian Ethnic Groups: Towards Personalized Medicine

“…While approximately 10,300 SNVs are described for TPMT , most of these variants are in non-coding regions (83.55% in the intronic region and 11.5% in the 5’ and 3’ untranslated regions). Given that only 3.06% of the variants described for TPMT occur in the CDS (2.07% nonsynonymous and 0.69% synonymous), 56 the low rate of SNVs in the CDS found in the studied population aligns with the molecular variability reported for this gene.…”

Nonsynonymous mutations in VEGF receptor binding domain alter the efficacy of bevacizumab treatment

“…The mutated RBDs have shown stability in 50 ns simulation. MD simulation experiments simulate the dynamics of different atoms in a protein within a time frame on the basis of the classical equations of motion controlling interatomic interactions and also helps to predict the impact of particular mutations on protein folding, ligand binding, and conformational alterations 40 . Hence, MD simulation was performed in this study to assess the stability of the nsSNP containing VEGF RBD and compared with the wild type.…”

“…MD simulation experiments simulate the dynamics of different atoms in a protein within a time frame on the basis of the classical equations of motion controlling interatomic interactions and also helps to predict the impact of particular mutations on protein folding, ligand binding, and conformational alterations. 40 Hence, MD simulation was performed in this study to assess the stability of the nsSNP containing VEGF RBD and compared with the wild type. Molecular docking and visualization of docked structures between the altered VEGF RBDs and bevacizumab are important to predict whether the selected nsSNPs affect the drug efficacy, compared to the wild type VEGF RBD.…”

Unraveling the function and structure impact of deleterious missense SNPs in the human OX1R receptor by computational analysis

“…Nonsynonymous SNPs (nsSNPs) in protein-coding regions, which result in alterations to amino acid sequences and the potential creation of mutated proteins with new structural and functional properties, have garnered significant interest. Deleterious nsSNPs at the genomic and/or proteome levels can induce detrimental functions by destabilizing protein tertiary structures, altering the physicochemical characteristics of proteins, and modifying protein–protein interactions, ultimately posing threats to cellular structural integrity 41 , 42 .…”

“…One significant aim in identifying deleterious nsSNPs is to conduct functional and structural evaluations. A comprehensive understanding of the conformational changes experienced by a protein can provide valuable insights into the underlying mechanisms of disease phenotypes and facilitate the identification of potential therapeutic agents capable of modulating protein function 42 , 43 .…”