A computational approach to explore the functional missense mutations in the spindle check point protein Mad1

In this work, the most detrimental missense mutations of Mad1 protein that cause various types of cancer were identified computationally and the substrate binding efficiencies of those missense mutations were analyzed. Out of 13 missense mutations, IMutant 2.0, SIFTand PolyPhen programs identified 3 variants that were less stable, deleterious and damaging respectively. Subsequently, modeling of these 3 variants was performed to understand the change in their conformations with respect to the native Mad1 by computing their root mean squared deviation (RMSD). Furthermore, the native protein and the 3 mutants were docked with the binding partner Mad2 to explain the substrate binding efficiencies of those detrimental missense mutations. The docking studies identified that all the 3 mutants caused lower binding affinity for Mad2 than the native protein. Finally, normal mode analysis determined that the loss of binding affinity of these 3 mutants was caused by altered flexibility in the amino acids that bind to Mad2 compared with the native protein. Thus, the present study showed that majority of the substrate binding amino acids in those 3 mutants displayed loss of flexibility, which could be the theoretical explanation of decreased binding affinity between the mutant Mad1 and Mad2.