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Application of the fragment molecular orbital method to discover novel natural products for prion disease.

ABSTRACT: Conformational conversion of the normal cellular isoform of the prion protein PrPC into an infectious isoform PrPSc causes pathogenesis in prion diseases. To date, numerous antiprion compounds have been developed to block this conversion and to detect the molecular mechanisms of prion inhibition using several computational studies. Thus far, no suitable drug has been identified for clinical use. For these reasons, more accurate and predictive approaches to identify novel compounds with antiprion effects are required. Here, we have applied an in silico approach that integrates our previously described pharmacophore model and fragment molecular orbital (FMO) calculations, enabling the ab initio calculation of protein-ligand complexes. The FMO-based virtual screening suggested that two natural products with antiprion activity exhibited good binding interactions, with hotspot residues within the PrPC binding site, and effectively reduced PrPSc levels in a standard scrapie cell assay. Overall, the outcome of this study will be used as a promising strategy to discover antiprion compounds. Furthermore, the SAR-by-FMO approach can provide extremely powerful tools in quickly establishing virtual SAR to prioritise compounds for synthesis in further studies.

SUBMITTER: Choi J

PROVIDER: S-EPMC6117342 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Application of the fragment molecular orbital method to discover novel natural products for prion disease.

Choi Jiwon J Kim Hyo-Jin HJ Jin Xuemei X Lim Hocheol H Kim Songmi S Roh In-Soon IS Kang Hae-Eun HE No Kyoung Tai KT Sohn Hyun-Joo HJ

Scientific reports 20180830 1

Conformational conversion of the normal cellular isoform of the prion protein PrP<sup>C</sup> into an infectious isoform PrP<sup>Sc</sup> causes pathogenesis in prion diseases. To date, numerous antiprion compounds have been developed to block this conversion and to detect the molecular mechanisms of prion inhibition using several computational studies. Thus far, no suitable drug has been identified for clinical use. For these reasons, more accurate and predictive approaches to identify novel co ...[more]

PMID: 30166585

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Project description:The accurate prediction of binding free energy is a major challenge in structure-based drug design. Quantum mechanics (QM)-based approaches show promising potential in predicting ligand-protein binding affinity by accurately describing the behavior and structure of electrons. However, traditional QM calculations face computational limitations, hindering their practical application in drug design. Nevertheless, the fragment molecular orbital (FMO) method has gained widespread application in drug design due to its ability to reduce computational costs and achieve efficient ab initio QM calculations. Although the FMO method has demonstrated its reliability in calculating the gas phase potential energy, the binding of proteins and ligands also involves other contributing energy terms, such as solvent effects, the 'deformation energy' of a ligand's bioactive conformations, and entropy. Particularly in cases involving ionized fragments, the calculation of solvation free energy becomes particularly crucial. We conducted an evaluation of some previously reported implicit solvent methods on the same data set to assess their potential for improving the performance of the FMO method. Herein, we develop a new QM-based binding free energy calculation method called FMOScore, which enhances the performance of the FMO method. The FMOScore method incorporates linear fitting of various terms, including gas-phase potential energy, deformation energy, and solvation free energy. Compared to other widely used traditional prediction methods such as FEP+, MM/PBSA, MM/GBSA, and Autodock vina, FMOScore showed good performance in prediction accuracies. By constructing a retrospective case study, it was observed that incorporating calculations for solvation free energy and deformation energy can further enhance the precision of FMO predictions for binding affinity. Furthermore, using FMOScore-guided lead optimization against Src homology-2-containing protein tyrosine phosphatase 2 (SHP-2), we discovered a novel and potent allosteric SHP-2 inhibitor (compound 8).

Project description:BackgroundThe 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.ResultsWe 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.ConclusionsOur 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.

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Application of the fragment molecular orbital method to discover novel natural products for prion disease.

Publications

Application of the fragment molecular orbital method to discover novel natural products for prion disease.

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