P. G. Department of Genetics, Ashok and Rita Patel Institute of Integrated Study and Research in Biotechnology and Allied Science (ARIBAS), New Vallabh Vidyanagar, Affiliated to Sardar Patel University, India.
Comput Biol Chem. 2018 Jun;74:20-30. doi: 10.1016/j.compbiolchem.2018.02.022. Epub 2018 Feb 27.
Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme involved in folate metabolism and plays a central role in DNA methylation and biosynthesis. MTHFR mutations may alter the cellular folate supply which in turn affects nucleic acid synthesis, DNA methylation and chromosomal damage. The identification of number of SNPs in the human genome growing nowadays and hence, the evaluation of functional & structural consequences of these SNPs is very laborious by means of experimental analysis. Therefore, in the present study, recently developed various computational algorithms have been used which can predict the functional and structural consequences of the SNPs. Various computational tools like SIFT, PolyPhen2, PROVEAN, SNAP2, nsSNPAnalyzer, SNPs&GO, PhD-SNP, PMut, I-Mutant, iPTREE-STAB and MUpro were used to predict most deleterious SNPs. Additionally, ConSurf was used to find amino acids conservation and NCBI conserved domain search tool to find conserved domains in MTHFR. Post translational modification sites were predicted using ModPred. SPARKS-X was used to generate 3D structure of the native and mutant MTHFR protein, ModRefiner for further refinement, Varify3D and RAMPAGE to validate structure. Ligand binding sites were predicted using FTsite, RaptorX binding and COACH. Three SNPs i.e. R157Q, L323P and W500C predicted the most deleterious in all the tools used for functional and stability analysis. Moreover, both residues R157, L323 and W500 were predicted highly conserved, buried and structural residues by ConSurf. Post translational modification sites were also predicted at R157 and W500. The ligand binding sites were predicted at R157, L323 and W500.
亚甲基四氢叶酸还原酶（MTHFR）是参与叶酸代谢的关键酶，在 DNA 甲基化和生物合成中起核心作用。MTHFR 突变可能改变细胞内叶酸供应，进而影响核酸合成、DNA 甲基化和染色体损伤。如今，人类基因组中 SNP 数量不断增加，因此，通过实验分析来评估这些 SNP 的功能和结构后果非常繁琐。因此，在本研究中，使用了最近开发的各种计算算法，这些算法可以预测 SNP 的功能和结构后果。使用了各种计算工具，如 SIFT、PolyPhen2、PROVEAN、SNAP2、nsSNPAnalyzer、SNPs&GO、PhD-SNP、PMut、I-Mutant、iPTREE-STAB 和 MUpro，来预测最具破坏性的 SNP。此外，还使用 ConSurf 寻找氨基酸保守性，使用 NCBI 保守域搜索工具寻找 MTHFR 中的保守域。使用 ModPred 预测翻译后修饰位点。使用 SPARKS-X 生成天然和突变 MTHFR 蛋白的 3D 结构，使用 ModRefiner 进行进一步细化，使用 Varify3D 和 RAMPAGE 验证结构。使用 FTsite 预测配体结合位点，使用 RaptorX 结合和 COACH 预测配体结合位点。在用于功能和稳定性分析的所有工具中，R157Q、L323P 和 W500C 这三个 SNP 被预测为最具破坏性的 SNP。此外，R157、L323 和 W500 这三个残基都被 ConSurf 预测为高度保守、埋藏和结构残基。还预测了 R157 和 W500 的翻译后修饰位点。预测了 R157、L323 和 W500 的配体结合位点。
