The interface of any given ligand and protein—normally considered a macromolecule—of a known or predicted/modeled structure can be computed by determining each potential ligand position, resulting in an array of possibilities which are finally expressed in numerical energy values based on their thermodynamic affinity. Over the past few decades, this premier approach technique has proved to be crucial as an automated method in drug design and discovery, as well as in other fields. Data are retrieved from contour surface calculations for each ligand probe and can be analyzed to delineate regions of attraction on the basis of energy levels. Negative energy levels from contours are used to infer protein-ligand affinity clefts and are therefore relevant to drug design. Accordingly, molecular docking, framed as the “new microscope,” is part of a group of in silico computational techniques that enable the behavior of molecular chemistry to be analyzed and predicted in an inexpensive manner. From the starting point of framing the key terms in the binomial macromolecule-ligand docking approach, this chapter presents an introductory description of the progress made in this field of research over the past several years, in addition to present and future perspectives. This chapter presents a broad plethora of possibilities arising from the old docking alternatives to the current software technology and critically dissects and discusses the emerging trends. Despite the emergence of more degrees of freedom, a number of flexible conglomerates have not been well developed, and there are still computational limitations to solve, including several features in the focused technique. The present goals, such as molecular flexibility, binding entropy, and the presence of ions and solute conditions, are revisited with the purpose of anticipating the challenges, goals, and achievements in this field over the next few years or decades.
Part of the book: Drug Discovery and Development