Abstract Let R∈ R n× n and S∈ R n× n be nontrivial involutions, ie, R= R− 1≠±I and S= S− 1≠±I. A matrix A∈ R n× n is called (R, S)-symmetric if R A S= A. This paper presents a (R, S)-symmetric matrix solution to the inverse eigenproblem with a leading principal submatrix constraint. The solvability condition of the constrained inverse eigenproblem is also derived. The existence, the uniqueness and the expression of the (R, S)-symmetric matrix solution to the best approximation problem of the constrained inverse eigenproblem are achieved, respectively. An algorithm is presented to compute the (R, S)-symmetric matrix solution to the best approximation problem. Two numerical examples are given to illustrate the effectiveness of our results.