Similarly, configurational stereoisomers (around a double bond) usually require remarkably high energy for interconversion, and thus are easy to model computationally. On the one hand, for organic chemists, having conformational isomers may not be a major concern since 2D representation is mostly sufficient to show what is synthesized. Likewise, experimental procedures for synthesis and characterization are mostly performed at the macroscopic level, so all the accessible conformational isomers are already reflected on the measurements as an equilibrated mixture at the experimental condition (room/physiological temperature, solution phase, etc.). On the other hand, for computer-aided drug design studies (CADD), conformational stereoisomers (conformers) around a single rotatable bond (i.e., torsion point) can become cumbersome due to their vast number of energetically accessible rearrangements and that the true 3D representation of a molecule becomes vital. Indeed, most drug-like organic compounds contain multiple rotatable bonds, creating a conformational space regarding their 3D structures to be included in computations. The energy change in response to the change of the dihedral angle around the four adjacent atoms in a single (rotatable) bond can be too small to accurately predict by computational methods. Even if the dihedral angle is predicted accurately, it only represents one of the many possible conformers (local minima) and finding the true 3D structure with the lowest energy of all conformers (global minimum) requires the energies of all minima to be calculated accurately. As a further complication in computer aided drug design, all conformers need to be evaluated at their biological target since the most stable complex between a biotarget molecule such as proteins and a drug-like molecule (i.e. the bound state) may not necessarily correspond to the global minimum of the drug-like compound in the free (unbound) state . Moreover, the structural strain on the bioactive compound, which is rather small on the torsion points, can be easily outweighed by the possible strong interactions with the biotarget compound, leading to drug-like compounds' bound state conformation to possess non-equilibrium structure. For this reason, most computational tools like molecular docking allows the free rotation around these torsion points and uses the ligand strain energy in the binding affinity calculations as a compromise to the gain of the energy between the bound and the unbound states. Indeed, there is a whole field in computational chemistry for accurate and fast prediction of binding free energy (BFE) change upon a ligand binding to its biological target compound . Thus, besides finding the low energy conformers of a drug-like compound, it is also necessary to find the relative energies among the conformers and potential energy surface (PES) connecting these conformations. There have been numerous strategies besides the screening of conformers using molecular docking including but not limited to induced-fit docking, ensemble docking, molecular dynamics (MD) and Monte Carlo (MC) simulations, all of which are involved at some level in the conformational space of the ligand in BFE calculations.