Mapping the Energy Landscape of PROTAC-Mediated Protein-protein Interactions
One of the principal difficulties in computational modeling of macromolecules is the vast conformational space that arises out of large numbers of atomic degrees of freedom. This problem is a familiar issue in the area of protein-protein docking, where models of protein complexes are generated from the monomeric subunits. Although restriction of molecular flexibility is a commonly used approximation that decreases the dimensionality of the problem, the seemingly endless number of possible ways two binding partners can interact generally necessitates the use of further approximations to explore the search space. Recently, growing interest in using computational tools to build predictive models of PROTAC-mediated complexes has led to the application of state-of-the-art protein-protein docking techniques to tackle this problem. Additionally, the atomic degrees of freedom introduced by flexibility of linkers used in the construction of PROTACs further expands the configurational search space, a problem that can be tackled with conformational sampling tools. However, repurposing existing tools to carry out protein-protein docking and linker conformer generation independently results in extensive sampling of structures incompatible with PROTAC-mediated complex formation. Here we show that it is possible to restrict the search to the space of protein-protein conformations that can be bridged by a PROTAC molecule with a given linker composition by using a cyclic coordinate descent algorithm to position PROTACs into complex-bound configurations. We use this methodology to construct a picture of the energy landscape of PROTAC-mediated interactions in a model test case, and show that the global minimum lies in the space of native-like conformations.