Free energy calculations on the binding of novel thiolactomycin derivatives to E. coli fatty acid synthase I

In Silico Modeling and Scoring of PROTAC-Mediated Ternary Complex Poses

Proteolysis targeting chimeras (PROTACs) are molecules that induce protein degradation via formation of ternary complexes between an E3 ubiquitin ligase and a target protein. The rational design of PROTACs requires accurate knowledge of the native configuration of the PROTAC-induced ternary complex. This study demonstrates that native and non-native ternary complex poses can be distinguished based on the pose occupancy time in MD, where native poses exhibit longer occupancy times at both room and higher temperatures. Candidate poses are generated by MD sampling and pre-ranked by classic MM/GBSA. A specific heating scheme is then applied to accelerate ternary pose departure, with the pose occupancy time and fraction being measured. This scoring identifies the native pose in all systems tested. Its success is partially attributed to the dynamic nature of pose departure analyses, which accounts for entropic effects typically neglected in the faster static scoring methods, while entropy plays a greater role in protein-protein than in protein-ligand systems.

Relative Binding Free Energies of Adenine and Guanine to Damaged and Undamaged DNA in Human DNA Polymerase η: Clues for Fidelity and Overall Efficiency

Human DNA polymerase η (Pol η) plays an essential protective role against skin cancer caused by cyclobutane thymine-thymine dimers (TTDs), a frequent form of DNA damage arising from exposure to the sun. This enzyme rescues stalled replication forks at the TTDs by inserting bases opposite these DNA defects. Herein we calculate binding free energies for a free deoxyribose nucleotide triphosphate, dATP or dGTP, to Pol η complexed with undamaged or damaged DNA. The calculations indicate that the binding of dATP to the enzyme-DNA complex is thermodynamically favored for TTD-containing DNA over undamaged DNA, most likely because of more extensive hydrogen-bonding interactions between the TTD and the enzyme that hold the TTD more rigidly in place. The calculations also illustrate that dATP binding is thermodynamically favored over dGTP binding at both thymine positions of the TTD, most likely due to more persistent and stable hydrogen-bonding interactions between the TTD and dATP than between the TTD and dGTP. This free energy difference is slightly greater for binding at the 5' thymine position than at the 3' thymine position, presumably because of stabilization arising from the A:T base pair formed at the 3' position of the TTD in the previous step of Pol η function. All of these trends in binding free energies are consistent with experimental measurements of binding strength, fidelity, processivity, and overall efficiency. The insights gained from this analysis have implications for drug design efforts aimed at modifying the binding properties of this enzyme for improving cancer chemotherapy treatments.

Molecular recognition in a diverse set of protein-ligand interactions studied with molecular dynamics simulations and end-point free energy calculations

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein-ligand interactions. The binding free energy can be used to rank-order protein-ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal·mol(-1) highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman ρ of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (ρ = 0.91 for ε = 10), but larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the nonpolar and entropy components, rather than a better representation of the electrostatics. The SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 0.81). Calculations of the configurational entropy using normal-mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo, and ligand (MM-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by prescoring protein-ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from ρ = 0.40 to ρ = 0.81. Finally, the nonpolar components of MM-GBSA and MM-PBSA, but not the electrostatic components, showed strong correlation to the ITC free energy; the computed entropies did not correlate with the ITC entropy.