Mutational landscape screening of methylene tetrahydrofolate reductase to predict homocystinuria associated variants: An integrative computational approach

Abstract

Methylene tetrahydrofolate reductase (MTHFR) is a flavoprotein, involved in one-carbon pathway and is responsible for folate and homocysteine metabolism. Regulation of MTHFR is pivotal for maintaining the cellular concentrations of methionine and SAM (S-adenosyl methionine) which are essential for the synthesis of nucleotides and amino acids, respectively. Therefore, mutations in MTHFR leads to its dysfunction resulting in conditions like homocystinuria, cardiovascular diseases, and neural tube defects in infants. Among these conditions, homocystinuria has been highly explored, as it manifests ocular disorders, cognitive disorders and skeletal abnormalities. Hence, in this study, we intend to explore the mutational landscape of human MTHFR isoform-1 (h.MTHFR-1) to decipher the most pathogenic variants pertaining to homocystinuria. Thus, a multilevel stringent prioritization of non-synonymous mutations in h.MTHFR-1 by integrative machine learning approaches was implemented to delineate highly deleterious variants based on its pathogenicity, impact on structural stability and functionality. Subsequently, extended molecular dynamics simulations and molecular docking studies were also integrated in order to prioritize the mutations that perturbs structural stability and functionality of h.MTHFR-1. In addition, displacement of Loop (Arg157-Tyr174) and helix α9 (His263-Ser272) involved in open/closed conformation of substrate binding domain were also probed to confirm the functional loss. On juxtaposed analysis, it was inferred that among 126 missense mutations screened, along with known pathogenic mutations (H127 T, A222 V, T227 M, F257 V and G387D) predicted that W500C, P254S and D585 N variants could be potentially driving homocystinuria. Thus, uncovering the prospects for inclusion of these mutations in diagnostic panels based on further experimental validations.