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 ofhomocysteine to methionine. This methylation is catalyzed by methylentetrahydrofolate reductase throughreduction of 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate. Normal DNA synthesis isconsidered critical for physiological functions of body. The enzyme is coded by the gene with the symbolMTHFR on chromosome 1 location p36.3 in humans. At least 24 mutations in the MTHFR gene have beenidentified 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 acidsubstitution Ala222Val and Glu429Ala respectively with a considerable reduced activity. This polymorphismand mild hyperhomocysteinemia are associated with neural tube defects in offspring, arterial and venousthrombosis, and cardiovascular disease. 677TT individuals are at a decreased risk for certain leukemia andcolon cancer. The MTHFR gene could be one of the factors of overall schizophrenia risk. In silico analysisnow has added important and wide range applications to proteomics from structure modeling to its functionallevels. Several algorithms have been suggested from many authors to bring an accurate modeling at its bestbut ultimately every protein has its own variant features to be treated by the same algorithm. Studies inproteomics through computational techniques need complements between critical requirement for a proteinand features available in an algorithm. Comparative modeling is now bridging the gap between availablesequences and structures modeled with accuracy. Effective refinement techniques made it capable ofdriving models toward native structure. Structure of MTHFR can assist the study of involvement of thisenzyme in the disorders and can provide better level of understanding about structural aspects of it. Wehave modeled wild type and mutated type MTHFR using comparative modeling and structure validation hasgiven appreciable values. This work can further account for the structure based drug design community inthe search of MTHFR inhibitors.