We present the extended Branch and Cut algorithm implemented in the software package LaGO for the solution of block-separable nonconvex mixed-integer nonlinear programs. The algorithm reformulates every function into a block-separable form and computes convex underestimators for each term separately. For that purpose, nonquadratic functions are first replaced by quadratic underestimators using a powerful heuristic. Nonconvex quadratic functions are then replaced by exakt convex underestimators. Finally, a linear outer approximation is constructed by linearization of the convex relaxation and the generation of mixed-integer rounding cuts and linearized interval gradient cuts. The efficiency of the method is improved by the application of a simple constraint propagation technique based on interval arithmetic.