Integral membrane proteins are ubiquitous in biological cellular and subcellular membranes. Despite their significance to cell function, isolation of membrane proteins from their hydrophobic lipid environment and further characterization remains a challenge. To obtain insights into membrane proteins, computational approaches such as docking or self-assembly simulations have been used; however, the promise of these approaches has been limited due to the computational cost. Here we present a new approach called Protein AssociatioN Energy Landscape (PANEL) that provides an extensive and converged data set for all possible conformations of membrane protein associations using a combination of stochastic sampling and equilibration simulations. The PANEL method samples the rotational space around both interacting proteins to obtain the comprehensive interaction energy landscape. We demonstrate the versatility of the PANEL method using two distinct applications: (a) dimerization of claudin-5 tight junction proteins in phospholipid bilayer membrane and (b) dimer and trimer formation of the Outer membrane protein F (OmpF) in the lipopolysaccharide-rich bacterial outer membrane. Both applications required only a fraction of simulation cost compared to self-assembly simulations. The method is robust as it can capture changes in protein-protein conformations caused by point mutations. Moreover, the method is versatile and independent of the molecular resolution (atomistic or coarse grain) or the choice of force field employed to compute the pair-interaction energies. The PANEL method is implemented in easy-to-use scripts that are available for download for general use by the scientific community to characterize any pair of interacting integral membrane proteins.