We compare established docking programs, AutoDock Vina and Schrödinger’s Glide, to the recently published NNScore scoring functions. As expected, the best protocol to use in a virtual-screening project is highly dependent on the target receptor being studied. However, the mean screening performance obtained when candidate ligands are docked with Vina and rescored with NNScore 1.0 is not statistically different than the mean performance obtained when docking and scoring with Glide. We further demonstrate that the Vina and NNScore docking scores both correlate with chemical properties like small-molecule size and polarizability. Compensating for these potential biases leads to improvements in virtual screen performance. Composite NNScore-based scoring functions suited to a specific receptor further improve performance. We are hopeful that the current study will prove useful for those interested in computer-aided drug design.

We use thermodynamic integration (TI) and explicit solvent molecular dynamics (MD) simulation to estimate the absolute free energy of host–guest binding. In the unbound state, water molecules visit all of the internally accessible volume of the host, which is fully hydrated on all sides. Upon binding of an apolar guest, the toroidal host cavity is fully dehydrated; thus, during the intermediate λ stages along the integration, the hydration of the host fluctuates between hydrated and dehydrated states. Estimating free energies by TI can be especially challenging when there is a considerable difference in hydration between the two states of interest. We investigate these aspects using the popular TIP3P and TIP4P water models. TI free energy estimates through MD largely depend on water-related interactions, and water dynamics significantly affect the convergence of binding free energy calculations. Our results indicate that wetting/dewetting transitions play a major role in slowing the convergence of free energy estimation. We employ two alternative approaches—one analytical and the other empirically based on actual MD sampling—to correct for the standard state free energy. This correction is sizable (up to 4 kcal/mol), and the two approaches provide corrections that differ by about 1 kcal/mol. For the system considered here, the TIP4P water model combined with an analytical correction for the standard state free energy provides higher overall accuracy. This observation might be transferable to other systems in which water-related contributions dominate the binding process.

The protozoan parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, affects millions of individuals and continues to be an important global health concern. The poor efficacy and unfavorable side effects of current treatments necessitate novel therapeutics. Cruzain, the major cysteine protease of T. cruzi, is one potential novel target. Recent advances in a class of vinyl-sulfone inhibitors are encouraging; however, as most potential therapeutics fail in clinical trials and both disease progression and resistance call for combination therapy with several drugs, the identification of additional classes of inhibitory molecules is essential. Using an exhaustive virtual-screening and experimental-validation approach, we identify several additional small-molecule cruzain inhibitors. Further optimization of these chemical scaffolds could lead to the development of novel drugs useful in the treatment of Chagas’ disease.

The synthetic host cucurbit[7]uril (CB[7]) binds aromatic guests or metal complexes with ultrahigh affinity compared with that typically displayed in protein–ligand binding. Due to its small size, CB[7] serves as an ideal receptor–ligand system for developing computational methods for molecular recognition. Here, we apply the recently developed variational implicit-solvent model (VISM), numerically evaluated by the level-set method, to study hydration effects in the high-affinity binding of the B2 bicyclo[2.2.2]octane derivative to CB[7]. For the unbound host, we find that the host cavity favors the hydrated state over the dry state due to electrostatic effects. For the guest binding, we find reasonable agreement to experimental binding affinities. Dissection of the individual VISM free-energy contributions shows that the major driving forces are water-mediated hydrophobic interactions and the intrinsic (vacuum) host–guest van der Waals interactions. These findings are in line with recent experiments and molecular dynamics simulations with explicit solvent. It is expected that the level-set VISM, with further refinement on the electrostatic descriptions, can efficiently predict molecular binding and recognition in a wide range of future applications.