Despite this long history of methods development, new techniques for accelerating docking while considering the ligand-induced conformational changes in the receptor are still needed to improve the predictive power of SBVS. The ultimate goal of this work is to build a method that can be used to run dynamics in a joint chemical-conformational space that is entirely continuous. This would allow for searching through chemical databases while using molecular dynamics (MD) to model ligand-induced conformational changes in the receptor as well as water molecules' effects on ligand-receptor interactions. Such a method would have the potential for dramatic gains in efficiency. To illustrate this, it is helpful to consider the example of a protein searching its confor-mational landscape to find its folded state. Levinthal's paradox states that there are an enormous number of possible protein conformations (10 300 ) and if all the conformations of protein are sampled one by one at a rate of 1 conformation per millisecond, then it would take the universe's age to find its folded conformation. However, in nature, protein folding does not require sampling all of the high-energy conformations; the protein is automatically drawn towards low-energy conformations due to the funnel-shaped nature of the energy landscape. The same reasoning is valid for a coupled chemical-conformational landscape approach as its search space will also be funnelshaped with the lowest energy target molecules at its bottom. In this way, we can simply avoid the sampling all of the high-energy ligands and conformations and be gradually drawn towards the best chemicals and structures with each simulation step.