A Computational Approach to Identify the Biophysical and Structural Aspects of Methylenetetrahydrofolate Reductase (MTHFR) Mutations (A222V, E429A, and R594Q) Leading to Schizophrenia.

Abstract

The association between depression and methylenetetrahydrofolate reductase (MTHFR) has been continually demonstrated in clinical studies, yet there are sparse resources available to build a relationship between the mutations associated with MTHFR and depression. The common mutations found to be associated with schizophrenia and MTHFR are A222V, E429A, and R594Q. Although abundant research on structural and functional effects caused by A222V mutation is available, very less amount of studies have been done on the other two mutants (E429A and R594Q). Hence in this study, a comparative analysis was carried out between the most common A222V mutation, a prevalent E429A mutation, and a less prevalent and less deleterious R594Q mutation. To predict structural rearrangements upon mutation, we proposed a computational pipeline using in silico prediction tools, molecular docking, and molecular dynamics simulation analysis. Since the association of flavin adenine dinucleotide (FAD) is important for the functioning of the protein, binding analysis between protein and the coenzyme was performed. This would enable us to understand the interference level of each mutation over FAD-binding activity. Consequently, we found that two mutations (A222V and E429A) showed lesser binding activity and structural deviations when compared to the native molecule and mutant R594Q. Comparatively, higher structural changes were observed with A222V mutant complex in comparison to other mutant complexes. Computational studies like this could render better insights into the structural changes in the protein and their relationship with the disease condition.