Data reporting on structure and dynamics of cellular constituents are growing with increasing pace enabling, as never before, the understanding of fine mechanistic aspects of biological systems and providing the possibility to affect them in controlled ways. Nonetheless, experimental techniques do not yet allow for an arbitrary level of resolution on cellular processes in situ. By consistently integrating a variety of diverse experimental data, molecular modeling is optimally poised to enhance to near-atomistic resolution our understanding of molecular recognition in large assemblies. Within this integrative modeling context, we briefly review in this chapter the recent progresses of molecular simulations at the atomistic and coarse-grained level of resolution to explore protein protein interactions. In particular, we discuss our recent contributions in this field, which aim at providing a robust bridge between novel optimization algorithms and multiscale molecular simulations for a consistent integration of experimental inputs. We expect that, with the ever-growing sampling ability of molecular simulations and the tireless progress of experimental methods, the impact of such dynamic-based approach could only be more effective with time, contributing to provide detailed description of cellular organization.