While there are over 100 marketed macrocyclic drugs derived from natural sources, they are for the vast majority either the actual natural compounds, or their modifications. Between 2014 and 2021, nineteen of the FDA approved drugs are macrocycles, which represents roughly 1 in 20 FDA approvals. Macrolide antibiotics such as actinomycin and polyene antifungal compounds are among the most prominent classes of compounds. However, in the past decade there has been an increasing interest in de novo designed macrocycles, often starting from small molecule templates. The cyclization process is a very effective way to improve physio-chemical properties of molecules, improving pharmacological properties while retaining relatively low molecular weights. For example, cyclization of peptides has been used by synthetic chemists, and in natural systems through post-translational modification and non-ribosomal peptide synthesis, to confer metabolic stability as well as to restrict the conformational space to improve affinity and cell permeability. In particular, the cyclization can be used to reduce the entropic cost of binding by reducing conformational degrees of freedom, and ultimately shift the thermodynamics of binding favoring the formation of a complex. Cyclization can also be used to increase cell permeability by exploiting the switching between solvent-dependent conformational states. Modeling of macrocycles presents a number of challenges for docking algorithms due to the complexity of their constrained molecular structures. On one hand, many of the internal degrees of freedom are partially restrained by the cyclic structure, which limits the amplitude of bond torsional variability. On the other hand, the remaining intra-cyclic degrees of freedom are hard to sample because of their correlated and concerted motions. Therefore, several methods have been proposed to describe and sample these constrained degrees of freedom during molecular docking. These methods can be categorized into two main approaches. The first is a two-step process consisting in the enumeration of a possibly large number of macrocycle conformers followed by rigid docking of each conformer. The second, which is the topic of the present work, is flexible docking of the cyclic structures is simpler because it consists of a single step and allows for the sampling of cyclic conformations during docking, while taking into account the target structure. Both approaches were used successfully by participants of the D3R Grand Challenge 4, which included the prediction of the binding mode of nineteen macrocycles. In 2007 we reported the first AutoDock method for docking macrocycles flexibly. Macrocycles are challenging because AutoDock samples bond rotations independently from each other, but cyclic molecules introduce a dependence between multiple rotatable bonds to preserve their cyclic structure. The method reported in 2007 consisted in breaking the cyclic structures by removing one bond, to allow independent sampling of each rotatable bond, and use of a modified Lennard-Jones-like potential between two previously bonded atoms (which we refer to as "glue" atoms) to restore the cyclic structure. The original closure potential was isotropic because it did not depend on the relative orientation of the glue atoms. Consequently, this potential is inappropriate for chiral carbons, and can produce non-physical valence angles.