Comparative modeling of methylentetrahydrofolate reductase (MTHFR) enzyme and its mutational assessment: in silico approach

DNA-synthesis, DNA-repair, and DNA imprinting processes require efficient conversion of homocysteine to methionine. This methylation is catalyzed by methylentetrahydrofolate reductase through reduction of 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate. Normal DNA synthesis is considered critical for physiological functions of body. The enzyme is coded by the gene with the symbol MTHFR on chromosome 1 location p36.3 in humans. At least 24 mutations in the MTHFR gene have been identified in people with homocystinuria. There is DNA sequence variants (genetic polymorphisms) associated with this gene. Two of the most investigated are C677T (rs1801133) and A1298C (rs1801131) single nucleotide polymorphisms (SNP). Mutations at C677T and A1298C which confer amino acid substitution Ala222Val and Glu429Ala respectively with a considerable reduced activity. This polymorphism and mild hyperhomocysteinemia are associated with neural tube defects in offspring, arterial and venous thrombosis, and cardiovascular disease. 677TT individuals are at a decreased risk for certain leukemia and colon cancer. The MTHFR gene could be one of the factors of overall schizophrenia risk. In silico analysis now has added important and wide range applications to proteomics from structure modeling to its functional levels. Several algorithms have been suggested from many authors to bring an accurate modeling at its best but ultimately every protein has its own variant features to be treated by the same algorithm. Studies in proteomics through computational techniques need complements between critical requirement for a protein and features available in an algorithm. Comparative modeling is now bridging the gap between available sequences and structures modeled with accuracy. Effective refinement techniques made it capable of driving models toward native structure. Structure of MTHFR can assist the study of involvement of this enzyme in the disorders and can provide better level of understanding about structural aspects of it. We have modeled wild type and mutated type MTHFR using comparative modeling and structure validation has given appreciable values. This work can further account for the structure based drug design community in the search of MTHFR inhibitors. Keywords - MTHFR, Comparative modeling, PDB, Mutation, Toxicity