A Role for Both Conformational Selection and Induced Fit in Ligand Binding by the LAO Protein

Molecular recognition is determined by the structure and dynamics of both a protein and its ligand, but it is difficult to directly assess the role of each of these players. In this study, we use Markov State Models (MSMs) built from atomistic simulations to elucidate the mechanism by which the Lysine-, Arginine-, Ornithine-binding (LAO) protein binds to its ligand. We show that our model can predict the bound state, binding free energy, and association rate with reasonable accuracy and then use the model to dissect the binding mechanism. In the past, this binding event has often been assumed to occur via an induced fit mechanism because the protein's binding site is completely closed in the bound state, making it impossible for the ligand to enter the binding site after the protein has adopted the closed conformation. More complex mechanisms have also been hypothesized, but these have remained controversial. Here, we are able to directly observe roles for both the conformational selection and induced fit mechanisms in LAO binding. First, the LAO protein tends to form a partially closed encounter complex via conformational selection (that is, the apo protein can sample this state), though the induced fit mechanism can also play a role here. Then, interactions with the ligand can induce a transition to the bound state. Based on these results, we propose that MSMs built from atomistic simulations may be a powerful way of dissecting ligand-binding mechanisms and may eventually facilitate a deeper understanding of allostery as well as the prediction of new protein-ligand interactions, an important step in drug discovery

Bisindolylmaleimides New Ligands of CaM Protein

In the present study, we reported the interactions at the molecular level of a series of compounds called Bisindolylmaleimide, as potential inhibitors of the calmodulin protein. Bisindolylmaleimide compounds are drug prototypes derived from Staurosporine, an alkaloid with activity for cancer treatment. Bisindolylmaleimide compounds II, IV, VII, X, and XI, are proposed and reported as possible inhibitors of calmodulin protein for the first time. For the above, a biotechnological device was used (fluorescent biosensor hCaM M124C-mBBr) to directly determine binding parameters experimentally (Kd and stoichiometry) of these compounds, and molecular modeling tools (Docking, Molecular Dynamics, and Chemoinformatic Analysis) to carry out the theoretical studies and complement the experimental data. The results indicate that this compound binds to calmodulin with a Kd between 193–248 nM, an order of magnitude lower than most classic inhibitors. On the other hand, the theoretical studies support the experimental results, obtaining an acceptable correlation between the ΔGExperimental and ΔGTheoretical (r2 = 0.703) and providing us with complementary molecular details of the interaction between the calmodulin protein and the Bisindolylmaleimide series. Chemoinformatic analyzes bring certainty to Bisindolylmaleimide compounds to address clinical steps in drug development. Thus, these results make these compounds attractive to be considered as possible prototypes of new calmodulin protein inhibitors

Application of a Fluorescent Biosensor in Determining the Binding of 5-HT to Calmodulin

Here, we show the utility of the fluorescent biosensor hCaM-M124C-mBBr in detecting and determining the affinity of serotonin (5-HT). We obtained a Kd of 5-HT (0.71 μm) for the first time, the same order of magnitude as most anti-CaM drugs. This data can contribute to understanding the direct and indirect modulation of CaM on its binding proteins when the 5-HT concentration varies in different tissues or explain some of the side effects of anti-CaM drugs. On the other hand, molecular modeling tools help the rational design of biosensors and adequately complement the experimental results. For example, the docking study indicates that 5-HT binds at the same site as chlorpromazine (site 1) with a theoretical Ki of 2.84 μM; while the molecular dynamics simulations indicate a stability of the CaM–5-HT complex with a theoretical ΔG of −4.85 kcal mol−1, where the enthalpy contribution is greater. Thus, the combination of biotechnology and bioinformatics helps in the design and construction of more robust biosensors