The Fragment Molecular Orbital Method Reveals New Insight into the Chemical Nature of GPCR–Ligand Interactions

Abstract

Our interpretation of ligand-protein interactions is often informed by high-resolution structures, which represent the cornerstone of structure-based drug design. However, visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum Mechanics approaches are often too computationally expensive, but one method, Fragment Molecular Orbital (FMO), offers an excellent compromise and has the potential to reveal key interactions that would otherwise be hard to detect. To illustrate this, we have applied the FMO method to 18 Class A GPCR-ligand crystal structures, representing different branches of the GPCR genome. Our work reveals key interactions that are often omitted from structure-based descriptions, including hydrophobic interactions, nonclassical hydrogen bonds, and the involvement of backbone atoms. This approach provides a more comprehensive picture of receptor-ligand interactions than is currently used and should prove useful for evaluation of the chemical nature of ligand binding and to support structure-based drug design.

Using the fragment molecular orbital method to investigate agonist–orexin-2 receptor interactions

“…We demonstrate that the FMO approach can be successfully applied to explore interactions in GPCR–ligand models rather than just crystallographic structures as previously reported [15,16,28,29,36,37]. …”

“…FMO is a general QM method that can be applied to any set of atoms, no matter if it is a soluble or membrane protein as described previously for exploration of the role of none-classical CH/π hydrogen bond in ligand recognition of β2-adrenergic GPCR receptor [15], for analysis of the GPCR–ligand crystal structures [29], for potency calculations on a novel Hsp90 fragment-linked inhibitor [39] and others. The FMO method can give a breakdown of the interaction energy between any two fragments and is consists of a sum of four pairwise interaction energy (PIE) terms: electrostatics, exchange-repulsion, charge transfer and dispersion (Figure 1).…”

“…The van-der-Waals forces, despite being generally well parameterized on average, are not capable of detecting the directional nature of the dispersion terms involving halogens [27]. Reported examples [28] comparing FMO and MM, have shown that the FMO method clearly outperformed FF-based scoring functions and demonstrated a high correlation with experimentally measured values of protein–ligand affinity [28,29]. In our recent report [29] we described how FMO has been applied for the analysis of 18 GPCR–ligand crystal structures representing different branches of the GPCR genome.…”

“…Reported examples [28] comparing FMO and MM, have shown that the FMO method clearly outperformed FF-based scoring functions and demonstrated a high correlation with experimentally measured values of protein–ligand affinity [28,29]. In our recent report [29] we described how FMO has been applied for the analysis of 18 GPCR–ligand crystal structures representing different branches of the GPCR genome. This work revealed key and consensus interactions that are involved in receptor–ligand binding and were previously omitted from structure-based descriptions, including hydrophobic interactions, non-classical hydrogen bonds and the involvement of backbone atoms.…”

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design

“…31 Exceptions to this include use of the fragment molecular orbital (FMO) framework [39][40][41] in schemes such as the PIEDA. 42 Recently, work has been published 43 investigating 18 class A GPCR-ligand crystal structures using the FMO-MP2 (second order Møller-Plesset perturbation theory) 44 PIEDA method with the 6-31G* basis set, demonstrating the components of the interactions and hence the high suitability of EDA to the field of drug design especially in the case of large drug-protein systems. With the developments made in the field of linear-scaling density functional theory (DFT) methods 45,46 a new opportunity to remove this size limitation arises.…”