Surface Binding Energy Landscapes Affect Phosphodiesterase Isoform-Specific Inhibitor Selectivity

Abstract

As human phosphodiesterase (PDE) proteins are attractive drug targets, a large number of selective PDE inhibitors have been developed. However, since the catalytic sites of PDE isoforms are conserved in sequence and structure, it remains unclear how these inhibitors discriminate PDE isoforms in a selective manner. Here we perform long-time scale molecular dynamics (MD) simulations to investigate the spontaneous association processes of a highly selective PDE2A inhibitor (BAY60–7550) with the catalytic pockets of six PDE isoforms. We found that the free-energy landscapes of PDE:BAY60–7550 interactions on the PDE surfaces are very different between various PDE isoforms; and the free-energy landscape of PDE2A forms a favorable low-energy pathway that not only drives BAY60–7550 toward the target binding site, but also guides BAY60–7750 to adopt its native binding conformation known from crystal structure. Thus, this study reveals that the inhibitor interactions with the PDE surface residues play an important role in its high selectivity for PDE2A, and thereby provides new fundamental insights into the PDE isoform-specific inhibitor selectivity.

De novo post-SELEX optimization of a G-quadruplex DNA aptamer binding to marine toxin gonyautoxin 1/4

“…Here, we employed a de novo computational approach to engineer aptamer variants of GO18-T-d with higher affinity for GTX1/4. This approach consists of three steps: first, temperature-dependent molecular dynamics (TdMD) simulations were used to predict the 3D structure of GO18-T-d directly from its sequence; second, spontaneous binding simulations were performed to reveal the stable complex structure of GO18-T-d:GTX1/4; third, binding energy landscapes [25] were constructed to identify the aptamer variants optimal for the GTX1/4 binding. By this approach, a truncated variant of GO18-T-d was engineered; and microscale thermophoresis (MST) [26] experiments verified that the binding affinity of this new aptamer increases by ~ 20 folds.…”

Spontaneous binding of potential COVID-19 drugs (Camostat and Nafamostat) to human serine protease TMPRSS2

“…5 B), indicating that the catalytic center provides the higher-affinity for Nafamostat. To further characterize these, we employed the method in our previous study [40] to construct the binding energy landscapes of two drugs using all the simulation trajectories, as shown in Supplementary Fig. S9 .…”

“…Any drug molecule that effectively inhibits the proteolysis function of TMPRSS2 has to be bound to the catalytic amino-acids and/or the substrate-binding regions. To capture the dynamic association process of a given drug with the protein receptor, atomic-level, unbiased MD simulation is an effective tool [40] , [41] , [50] . To simulate those association processes for Camostat and Nafamostat in an aqueous environment, we used the mentioned TMPRSS2-ECD structure at 200 ns to establish the simulation systems.…”

“…3 . As supported by our previous studies [40] , [41] , this calculation method of binding free-energy is fast and reliable for analyzing large numbers of inhibitor-receptor snapshot complexes in the MD simulations. The calculations for the trajectories in Fig.…”

“…As in our previous studies [40] , [41] , we used AutoDockTools [42] to calculate the free energy of a drug (Camostat or Nafamostat) that bind to TMPRSS2-ECD in the simulation snapshots. AutoDockTools uses the AutoDock 4.1 semi-empirical free energy force field to estimate the free energy of a small-molecular drug binding to a protein receptor based on their drug-protein complex, With the given complex, the binding free energy ( ) equals to the change in the free energy of the drug from the unbound state to the bound state: where the first two terms are the energies of the drug-protein complex in the bound state, consisting of the intermolecular and intramolecular free energies.…”