In this paper, we study how to integrate multiple functional networks for accurate protein function prediction and propose a method called MNet. MNet unifies the optimization of a composite network and the optimization of a predictor on the composite network in a single objective. An extensive empirical study shows that MNet can predict protein functions more accurately than related competitive methods, and it's also less affected by the parameter selection issue.