The effect of MM polarization on the QM/MM transition state stabilization: application to chorismate mutase

Computational Investigation of a Series of Small Molecules as Potential Compounds for Lysyl Hydroxylase-2 (LH2) Inhibition

The catalytic function of lysyl hydroxylase-2 (LH2), a member of the Fe(II)/αKG-dependent oxygenase superfamily, is to catalyze the hydroxylation of lysine to hydroxylysine in collagen, resulting in stable hydroxylysine aldehyde-derived collagen cross-links (HLCCs). Reports show that high amounts of LH2 lead to the accumulation of HLCCs, causing fibrosis and specific types of cancer metastasis. Some members of the Fe(II)/αKG-dependent family have also been reported to have intramolecular O2 tunnels, which aid in transporting one of the required cosubstrates into the active site. While LH2 can be a promising target to combat these diseases, efficacious inhibitors are still lacking. We have used computational simulations to investigate a series of 44 small molecules as lead compounds for LH2 inhibition. Tunneling analyses indicate the existence of several intramolecular tunnels. The lengths of the calculated O2-transporting tunnels in holoenzymes are relatively longer than those in the apoenzyme, suggesting that the ligands may affect the enzyme's structure and possibly block (at least partially) the tunnels. The sequence alignment analysis between LH enzymes from different organisms shows that all of the amino acid residues with the highest occurrence rate in the oxygen tunnels are conserved. Our results suggest that the enolate form of diketone compounds establishes stronger interactions with the Fe(II) in the active site. Branching the enolate compounds with functional groups such as phenyl and pyridinyl enhances the interaction with various residues around the active site. Our results provide information about possible leads for further LH2 inhibition design and development.

A Many-Body, Fully Polarizable Approach to QM/MM Simulations

We present a new development in quantum mechanics/molecular mechanics (QM/MM) methods by replacing conventional MM models with data-driven many-body (MB) representations rigorously derived from high-level QM calculations. The new QM/MM approach builds on top of mutually polarizable QM/MM schemes developed for polarizable force fields with inducible dipoles and uses permutationally invariant polynomials to effectively account for quantum-mechanical contributions (e.g., exchange-repulsion and charge transfer and penetration) that are difficult to describe by classical expressions adopted by conventional MM models. Using the many-body MB-pol and MB-DFT potential energy functions for water, which include explicit two-body and three-body terms fitted to reproduce the corresponding CCSD(T) and PBE0 two-body and three-body energies for water, we demonstrate a smooth energetic transition as molecules are transferred between QM and MM regions, without the need of a transition layer. By effectively elevating the accuracy of both the MM region and the QM/MM interface to that of the QM region, the new QM/MB-MM approach achieves an accuracy comparable to that obtained with a fully QM treatment of the entire system.

Polarizable ab initio QM/MM Study of the Reaction Mechanism of N-tert-Butyloxycarbonylation of Aniline in [EMIm][BF₄]

N-t e r t-butoxycarbonylation of amines in solution (water, organic solvents, or ionic liquids) is a common reaction for the preparation of drug molecules. To understand the reaction mechanism and the role of the solvent, quantum mechanical/molecular mechanical simulations using a polarizable multipolar force field with long⁻range electrostatic corrections were used to optimize the minimum energy paths (MEPs) associated with various possible reaction mechanisms employing the nudged elastic band (NEB) and the quadratic string method (QSM). The calculated reaction energies and energy barriers were compared with the corresponding gas-phase and dichloromethane results. Complementary Electron Localization Function (ELF)/NCI analyses provide insights on the critical structures along the MEP. The calculated results suggest the most likely path involves a sequential mechanism with the rate⁻limiting step corresponding to the nucleophilic attack of the aniline, followed by proton transfer and the release of CO 2 without the direct involvement of imidazolium cations as catalysts.

Accounting for non-optimal interactions in molecular recognition: a study of ion-π complexes using a QM/MM model with a dipole-polarisable MM region

For a quantitative understanding of molecular structure, interaction and dynamics, accurate modelling of the energetics of both near-equilibrium and less optimal contacts is important. In this work, we explore the potential energy surfaces of representative ion-π complexes. We examine the performance of a semi-empirical QM/MM approach and the corresponding QM/MMpol model, where inducible point dipoles are additionally employed in the MM region. The predicted potential energy surfaces of cation-benzene complexes are improved by inclusion of explicit MM polarisation of the π-molecule. For cation-formamide complexes, inducible dipoles appreciably improve energetic estimates at geometries forming non-optimal interactions. Energetic component analysis suggests that the implicit MM polarisation of the fixed charge QM/MM model mirrors the behaviour of the QM/MMpol dipole model for the energetics of near-equilibrium conformations. However, for complexes at less optimal orientations, the QM/MM model exhibits higher errors than the QM/MMpol approach, being unable to capture orientation-dependent variations in polarisation energy.

Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method

BACKGROUND

The reliable and robust estimation of ligand binding affinity continues to be a challenge in drug design. Many current methods rely on molecular mechanics (MM) calculations which do not fully explain complex molecular interactions. Full quantum mechanical (QM) computation of the electronic state of protein-ligand complexes has recently become possible by the latest advances in the development of linear-scaling QM methods such as the ab initio fragment molecular orbital (FMO) method. This approximate molecular orbital method is sufficiently fast that it can be incorporated into the development cycle during structure-based drug design for the reliable estimation of ligand binding affinity. Additionally, the FMO method can be combined with approximations for entropy and solvation to make it applicable for binding affinity prediction for a broad range of target and chemotypes.

RESULTS

We applied this method to examine the binding affinity for a series of published cyclin-dependent kinase 2 (CDK2) inhibitors. We calculated the binding affinity for 28 CDK2 inhibitors using the ab initio FMO method based on a number of X-ray crystal structures. The sum of the pair interaction energies (PIE) was calculated and used to explain the gas-phase enthalpic contribution to binding. The correlation of the ligand potencies to the protein-ligand interaction energies gained from FMO was examined and was seen to give a good correlation which outperformed three MM force field based scoring functions used to appoximate the free energy of binding. Although the FMO calculation allows for the enthalpic component of binding interactions to be understood at the quantum level, as it is an in vacuo single point calculation, the entropic component and solvation terms are neglected. For this reason a more accurate and predictive estimate for binding free energy was desired. Therefore, additional terms used to describe the protein-ligand interactions were then calculated to improve the correlation of the FMO derived values to experimental free energies of binding. These terms were used to account for the polar and non-polar solvation of the molecule estimated by the Poisson-Boltzmann equation and the solvent accessible surface area (SASA), respectively, as well as a correction term for ligand entropy. A quantitative structure-activity relationship (QSAR) model obtained by Partial Least Squares projection to latent structures (PLS) analysis of the ligand potencies and the calculated terms showed a strong correlation (r2 = 0.939, q2 = 0.896) for the 14 molecule test set which had a Pearson rank order correlation of 0.97. A training set of a further 14 molecules was well predicted (r2 = 0.842), and could be used to obtain meaningful estimations of the binding free energy.

CONCLUSIONS

Our results show that binding energies calculated with the FMO method correlate well with published data. Analysis of the terms used to derive the FMO energies adds greater understanding to the binding interactions than can be gained by MM methods. Combining this information with additional terms and creating a scaled model to describe the data results in more accurate predictions of ligand potencies than the absolute values obtained by FMO alone.

A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity

Computational methods for predicting protein-ligand binding free energy continue to be popular as a potential cost-cutting method in the drug discovery process. However, accurate predictions are often difficult to make as estimates must be made for certain electronic and entropic terms in conventional force field based scoring functions. Mixed quantum mechanics/molecular mechanics (QM/MM) methods allow electronic effects for a small region of the protein to be calculated, treating the remaining atoms as a fixed charge background for the active site. Such a semi-empirical QM/MM scoring function has been implemented in AMBER using DivCon and tested on a set of 23 metalloprotein-ligand complexes, where QM/MM methods provide a particular advantage in the modeling of the metal ion. The binding affinity of this set of proteins can be calculated with an R(2) of 0.64 and a standard deviation of 1.88 kcal/mol without fitting and 0.71 and a standard deviation of 1.69 kcal/mol with fitted weighting of the individual scoring terms. In this study we explore using various methods to calculate terms in the binding free energy equation, including entropy estimates and minimization standards. From these studies we found that using the rotational bond estimate to ligand entropy results in a reasonable R(2) of 0.63 without fitting. We also found that using the ESCF energy of the proteins without minimization resulted in an R(2) of 0.57, when using the rotatable bond entropy estimate.

Many-body effects and simulations of potassium channels

The electronic polarizability of an ion or a molecule is a measure of the relative tendency of its electron cloud to be distorted from its normal shape by an electric field. On the molecular scale, in a condensed phase, any species sits in an electric field due to its neighbours, and the resulting polarization is an important contribution to the total interaction energy. Electrostatic interactions are crucial for determining the majority of chemical–physical properties of the system and electronic polarization is a fundamental component of these interactions. Thus, polarization effects should be taken into account if accurate descriptions are desired. In classical computer simulations, the forces required to drive the system are typically based on interatomic interaction potentials derived in part from electronic structure calculations or from experimental data. Owing to the difficulties in including polarization effects in classical force fields, most of them are based just on pairwise additive interaction potentials. At present, major efforts are underway to develop polarizable interaction potentials for biomolecular simulations. In this review, various ways of introducing explicit polarizability into biomolecular models and force fields are reviewed, and the progress that might be achieved in applying such methods to study potassium channels is described.