We consider convex constrained optimization problems with a special separable structure. We propose a class of alternating directions methods (ADM) where their subproblems are regularized with a general interior proximal metric which covers double regularization proposed by Silva and Eckstain. Under standard assumptions, global convergence of the primal-dual sequences produced by the algorithm is established.