Molecular Environment-Specific Atomic Charges Improve Binding Affinity Predictions of SAMPL5 Host-Guest Systems

Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Binding Affinity Predictions of the T4-Lysozyme Double Mutant

The use of computer simulation for binding affinity prediction is growing in drug discovery. However, its wider use is constrained by the accuracy of the free energy calculations. The key sources of error are the force fields used to depict molecular interactions and insufficient sampling of the configurational space. To improve the quality of the force field, we developed a Python-based computational workflow. The workflow described here uses the minimal basis iterative stockholder (MBIS) method to determine atomic charges and Lennard-Jones parameters from the polarized molecular density. This is done by performing electronic structure calculations on various configurations of the ligand when it is both bound and unbound. In addition, we validated a simulation procedure that accounts for the protein and ligand degrees of freedom to precisely calculate binding free energies. This was achieved by comparing the self-adjusted mixture sampling and nonequilibrium thermodynamic integration methods using various protein and ligand conformations. The accuracy of predicting binding affinity is improved by using MBIS-derived force field parameters and a validated simulation procedure. This improvement surpasses the chemical precision for the eight aromatic ligands, reaching a root-mean-square error of 0.7 kcal/mol.

Nonbonded Force Field Parameters from Minimal Basis Iterative Stockholder Partitioning of the Molecular Electron Density Improve CB7 Host-Guest Affinity Predictions

Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with an aromatic or adamantane core and the CB7 host using molecular electron density derived nonbonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the Minimal Basis Iterative Stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound states. The resulting nonbonded force field parameters improve binding affinity prediction, especially for guests with an adamantane core in which repulsive exchange and dispersion interactions to the host dominate.

Does Hamiltonian Replica Exchange via Lambda-Hopping Enhance the Sampling in Alchemical Free Energy Calculations?

In the context of computational drug design, we examine the effectiveness of the enhanced sampling techniques in state-of-the-art free energy calculations based on alchemical molecular dynamics simulations. In a paradigmatic molecule with competition between conformationally restrained E and Z isomers whose probability ratio is strongly affected by the coupling with the environment, we compare the so-called λ-hopping technique to the Hamiltonian replica exchange methods assessing their convergence behavior as a function of the enhanced sampling protocols (number of replicas, scaling factors, simulation times). We found that the pure λ-hopping, commonly used in solvation and binding free energy calculations via alchemical free energy perturbation techniques, is ineffective in enhancing the sampling of the isomeric states, exhibiting a pathological dependence on the initial conditions. Correct sampling can be restored in λ-hopping simulation by the addition of a “hot-zone” scaling factor to the λ-stratification (FEP⁺ approach), provided that the additive hot-zone scaling factors are tuned and optimized using preliminary ordinary replica-exchange simulation of the end-states.

DFT-D4 Insight into the Inclusion of Amphetamine and Methamphetamine in Cucurbit[7]uril: Energetic, Structural and Biosensing Properties

The host-guest interactions of cucurbit[7]uril (CB[7]) as host and amphetamine (AMP), methamphetamine (MET) and their enantiomeric forms (S-form and R-form) as guests were computationally investigated using density functional theory calculations with the recent D4 atomic-charge dependent dispersion corrections. The analysis of energetic, structural and electronic properties with the aid of frontier molecular orbital analysis, charge decomposition analysis (CDA), extended charge decomposition analysis (ECDA) and independent gradient model (IGM) approach allowed to characterize the host-guest interactions in the studied systems. Energetic results indicate the formation of stable non-covalent complexes where R-AMP@CB[7] and S-AMP@CB[7] are more stable thermodynamically than R-MET@CB[7] and S-MET@CB[7] in gas phase while the reverse is true in water solvent. Based on structural analysis, a recognition mechanism is proposed, which suggests that the synergistic effect of van der Waals forces, ion-dipole interactions, intermolecular charge transfer interactions and intermolecular hydrogen bonding is responsible for the stabilization of the complexes. The geometries of the complexes obtained theoretically are in good agreement with the X-ray experimental structures and indicate that the phenyl ring of amphetamine and methamphetamine is deeply buried into the cavity of CB[7] through hydrophobic interactions while the ammonium group remains outside the cavity to establish hydrogen bonds with the portal oxygen atoms of CB[7].