Coarse grained modelling highlights the binding differences in the two different allosteric sites of the Human Kinesin EG5 and its implications in inhibitor design. (August 2022) - Alexandar, Soundarya Priya; Yennamalli, Ragothaman M.; Ulaganathan, Venkatasubramanian
Abstract: Kinesins involved in mitotic cell division have gained prominence as promising chemotherapy targets. One such kinesin, EG5, a motor protein responsible for cell division, is a validated chemotherapy target with several compounds at various stages of clinical trials. EG5 has an active site and two different allosteric sites that are known to have ligand specificity. Upon ligand binding, EG5's motor domain will no longer undergo nucleotide-dependent conformational changes required to complete the catalytic cycle. However, there is a lack of in-depth knowledge on the mechanism of inhibitor binding to the two different allosteric sites. To understand the EG5's inhibition mechanism and interactions at allosteric sites and other functionally important regions, we generated two coarse-grained models, Gaussian Network Model (GNM) and Anisotropic Network Model (ANM), to identify the dynamics and its correlation to EG5's function. The first three slowest modes of GNM showed marked differences between the various models of EG5. In the first mode, when the inhibitor is bound at allosteric site 1, there is a presence of a hinge region around residue 166, which is not found when the inhibitor is bound at allosteric site 2 or allosteric sites 1 and 2. The third slowest mode showed a distinctive positively correlated region when the inhibitor is bound at allosteric site 2. These differences indicated that the mechanism of binding at allosteric site 1 and allosteric site 2 are unique. Further, it was observed that the simultaneous ligand binding at allosteric sites 1 and 2 shares structural dynamics and interactions that were found while ligand binds at allosteric sites 1 and 2 independently, leading to a new mechanism. Taken together, our observations suggest that there are different mechanisms at play in each inhibitor bound system considered. Graphical Abstract: ga1 Highlights: First in class study with six extensive models (native and inhibitor bound) to study and compare the EG5 motor domain. Understanding the binding mechanism might help in designing better inhibitors against this critical drug target. Elastic network models (ENM) were used to derive functional motions from the structure. The models used have the ability to predict collective participation of entire domains with limited computational power.