The accurate calculation of protein/nucleic acid–ligand interactions or condensed phase properties by force field-based methods require a precise description of the energetics of intermolecular interactions. Despite the progress made in force fields, small molecule parameterization remains an open problem due to the magnitude of the chemical space; the most critical issue is the estimation of a balanced set of atomic charges with the ability to reproduce experimental properties. The LigParGen web server provides an intuitive interface for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the formats of commonly used molecular dynamics and Monte Carlo simulation packages. This server has high value for researchers interested in studying any phenomena based on intermolecular interactions with ligands via molecular mechanics simulations. It is free and open to all at jorgensenresearch.com/ligpargen, and has no login requirements.

The quality of the 1.14*CM1A and 1.20*CM5 charge models was evaluated for calculations of free energies of hydration. For a set of 426 neutral molecules, 1.14*CM1A and 1.20*CM5 yield MADs of 1.26 and 1.20 kcal/mol, respectively. The 1.14*CM1A charges, which can be readily obtained for large systems, exhibit large deviations only for a subset of functional groups. The results for these cases were systematically improved using Localized Bond Charge Corrections (LBCC) by which off-setting adjustments are made to the partial charges for atoms in specified bond types. Only 19 LBCCs were needed to yield 1.14*CM1A-LBCC charges that reduce the errors for the 426 ΔGhyd values to only 0.61 kcal/mol. The modified charge method was also tested in computation of heats of vaporization and densities for pure organic liquids, yielding average errors of 1.40 kcal/mol and 0.024 g/cm3, similar to those for 1.14*CM1A.

Modern molecular mechanics force fields are widely used for modeling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. However, for molecules outside the training set, the parameters are potentially inaccurate and it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines bond, angle, torsion, charge, and Lennard-Jones parameter derivation methodologies alongside a method for deriving the positions and charges of off-center virtual sites from the partitioned quantum mechanical electron density. As a proof of concept, we have rederived a complete set of parameters for 109 small organic molecules and assessed the accuracy by comparing computed liquid properties with experiments. QUBEKit gives competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol, and 1.17 kcal/mol for the liquid density, heat of vaporization, and free energy of hydration, respectively. This indicates that the derived parameters are suitable for molecular modeling applications, including computer-aided drug design.

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

Partial atomic charges for neutral molecules from quantum mechanical calculations are typically scaled for use in molecular modeling of liquid-phase systems. Optimal scale factors of 1.14 for CM1A and 1.27 for CM5 charges were previously determined for minimizing errors in free energies of hydration. The adequacy of the 1.14*CM1A and 1.27*CM5 models are evaluated here in pure liquid simulations in combination with the OPLS-AA force field. For 22 organic liquids, the 1.14*CM1A and 1.27*CM5 models yield mean unsigned errors (MUEs) of ca. 1.40 kcal/mol for heats of vaporization. Not surprisingly, this reflects overpolarization with the scale factors derived for aqueous media. Prediction of pure liquid properties using CM5 charges is optimized using a scale factor of 1.14, which reduces the MUE for heats of vaporization to 0.89 kcal/mol. However, due to the impracticality of using different scale factors in different explicit-solvent condensed-phase simulations, a universal scale factor of 1.20 emerged for CM5 charges. This provides a balance between errors in computed pure liquid properties and free energies of hydration. Computation of free energies of hydration by the GB/SA method further found that 1.20 is equally suited for use in explicit or implicit treatments of aqueous solvation. With 1.20*CM5 charges, a variety of condensed-phase simulations can be pursued while maintaining average errors of 1.0 kcal/mol in key thermodynamic properties.

Non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs), which bind to an allosteric site 10 −15Å from the polymerase active site, play a central role in anti-HIV chemotherapy. Though NNRTIs have been known for 30 years, the pathways by which they bind and unbind from HIV-RT have not been characterized. In crystal structures for complexes, three channels are found to extend from the NNRTI binding site to the exterior of the protein, while added mystery comes from the fact that the binding site is collapsed in the unliganded protein. To address this issue, metadynamics simulations have been performed to elucidate the unbinding of four NNRTIs from HIV-RT. A general and transferable collective variable (CV) defined by the distance between the center-of-mass (COM) of the binding pocket and COM of the ligand is used to follow the dynamics while minimizing the bias. The metadynamics also allows computation of the barriers to unbinding, which are compared with the observed potencies of the compounds in an antiviral assay.

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

Study of the dynamics of H2CO confined within graphene sheets and sensing of H2CO by graphene require an analytic representation of the intermolecular potential between H2CO and graphene. To develop an intermolecular potential for H2CO interacting with graphene, ab initio calculations were performed at the MP2/MG3S, B97-D/MG3S and LPNO-CEPA/1/CBS levels of theory using H2CO-pyrene as a model. The intermolecular interactions were computed for three different orientations of formaldehyde approaching pyrene for a complete description of the interaction. The interaction energy obtained from the MP2, B97-D and LPNO-CEPA/1 methods were compared with the CCSD(T) method. The LPNO-CEPA/1/CBS method gives the best interaction energies compared to the CCSD(T)/CBS method. The LPNO-CEPA/1/CBS data obtained is fitted to an analytical potential energy function written as the sum of two-body interactions between the C atoms of pyrene and the C, H, O atoms of formaldehyde. The fitted potential energy function represents the ab initio data in excellent agreement for all the orientations considered. The analytical potential was also found to represent very well the interactions for two new orientations not considered in fitting, emphasizing the global nature of the analytic potential. The new potential is also compared with the van der Waals AMBER model.