In the absence of any crystallographic data the accurate prediction of a ligand's binding mode can be critical for success in structure-based drug discovery. Likewise, structure based virtual screening methods which are widely used for the identification of chemical starting points, rely heavily on accurate pose prediction and scoring. There is widespread application of proteinligand docking algorithms in molecular design, yet they possess significant drawbacks. To enable docking at speed a variety of approximations are made to derive a scoring function which albeit renders the scores almost qualitative. The scoring system rarely accounts for the conformational flexibility of either the protein or the ligand associated with induced-fit or conformational-selection binding events. Consequently, water and or ion solvation together with the entopic changes associated on ligand binding are poorly handled. Hence, small changes in the binding site conformation or entropic solvation can lead to drastically different docking results. To address these limitations, molecular mechanics with Poisson-Boltzmann and surface area (MM-PBSA) or molecular mechanics with generalized Born and surface area (MM-GBSA) approaches were introduced to estimate the binding energies, combining molecular