Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR

Abstract

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

Enhanced Biodegradation of Phthalic Acid Esters’ Derivatives by Plasticizer-Degrading Bacteria (Burkholderia cepacia, Archaeoglobus fulgidus, Pseudomonas aeruginosa) Using a Correction 3D-QSAR Model

“…In this paper, GROMACS 4.6.5 software was used to simulate the molecular dynamics (MD) of the ligand complex structures of DEP and its derivatives in Sybyl-x2.0, docked with phthalate dioxygenase reductase, esterase and acid esterase. The Poisson–Boltzmann surface area (MM-PBSA) method was used to calculate the binding free energy in the molecular dynamics [ 53 ]. Compared with the scoring function of molecular docking, the degree of binding energy characterized the biodegradability of DEP molecules before and after modification ( Table 7 ).…”

Doxorubicin Encapsulation in Carbon Nanotubes Having Haeckelite or Stone–Wales Defects as Drug Carriers: A Molecular Dynamics Approach

“…Its calculation is based on the MM/PBSA and MM/GBSA approaches starting from the equilibrium energy values obtained through molecular dynamics simulation. Although the calculation does not consider the translational entropy (huge computational cost), it has been shown that it does provide adequate values of the relative binding energies, which have been experimentally validated in biological systems [49,50] and it has recently been reported that when the MM/PBSA and MM/GBSA are used together with empirical corrections, they allow better experimental correlations [51].…”

Carbon Nanotubes Having Haeckelite Defects as Potential Drug Carriers. Molecular Dynamics Simulation

“…Calculated binding free energies have an average standard deviation of 2–3 kcal/mol. However, the MM/PBSA and MM/GBSA methods revealed as very useful in predicting a ranking of activity against biological systems and have been successfully validated experimentally [34]. These methods have been used to provide a relatively quick estimate of the nanotube activity ranking for DOX encapsulation with consistent results, comparable to other sources and prove to be quite useful if the actual value of the binding free energy is not required [18].…”

“…The drug (ligand)-nanotube (receptor) binding free energies were determined through the complementary methods MM/PBSA and MM/GBSA implemented in AMBER [36]. In spite that MM/PBSA typically gives too large energies it is recognized as useful in rationalizing experimental and theoretical findings [18,34,41]. These methods were applied on an ensemble of 200 uncorrelated snapshots collected from the equilibrated molecular dynamics simulation and were performed considering ΔG=〈GDOX−CNT−GCNT−GDOX〉DOX−CNT where G DOX-CNT , G CNT , and G DOX correspond to the Gibbs free energy terms for the DOX-CNT complex, the receptor and the ligand, respectively.…”