Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors

Toward Post-Hartree-Fock Accuracy for Protein-Ligand Affinities Using the Molecules-in-Molecules Fragmentation-Based Method

The complexity and size of large molecular systems, such as protein-ligand complexes, pose computational challenges for accurate post-Hartree-Fock calculations. This study delivers a thorough benchmarking of the Molecules-in-Molecules (MIM) method, presenting a clear and accessible strategy for layer/theory selections in post-Hartree-Fock computations on substantial molecular systems, notably protein-ligand complexes. An approach is articulated, enabling augmented computational efficiency by strategically canceling out common subsystem energy terms between complexes and proteins within the supermolecular equation. Employing DLPNO-based post-Hartree-Fock methods in conjunction with the three-layer MIM method (MIM3), this study demonstrates the achievement of protein-ligand binding energies with remarkable accuracy (errors <1 kcal mol-1), while significantly reducing computational costs. Furthermore, noteworthy correlations between theoretically computed interaction energies and their experimental equivalents were observed, with R2 values of approximately 0.90 and 0.78 for CDK2 and BZT-ITK sets, respectively, thus validating the efficacy of the MIM method in calculating binding energies. By highlighting the crucial role of diffuse or small Pople-style basis sets in the middle layer for reducing energy errors, this work provides valuable insights and practical methodologies for interaction energy computations in large molecular complexes and opens avenues for their application across a diverse range of molecular systems.

Binding Free Energy Calculation Based on the Fragment Molecular Orbital Method and Its Application in Designing Novel SHP-2 Allosteric Inhibitors

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).

Parametrized quantum-mechanical approaches combined with the fragment molecular orbital method

Fast parameterized methods such as density-functional tight-binding (DFTB) facilitate realistic calculations of large molecular systems, which can be accelerated by the fragment molecular orbital (FMO) method. Fragmentation facilitates interaction analyses between functional parts of molecular systems. In addition to DFTB, other parameterized methods combined with FMO are also described. Applications of FMO methods to biochemical and inorganic systems are reviewed.

Actinide Decorporation: A Review on Chelation Chemistry and Nanocarriers for Pulmonary Administration

Chelation is considered the best method for detoxification by promoting excretion of actinides (Am, Np, Pu, Th, U) from the human body after internal contamination. Chemical agents that possess carboxylic acid or hydroxypyridinonate groups play a vital role in actinide decorporation. In this review article, we provide considerable background details on the chelation chemistry of actinides with an aim to formulate better decorporation agents. Nanocarriers for pulmonary delivery represent an exciting prospect in the development of novel therapies for actinide decorporation that both reduce toxic side effects of the agent and improve its retention in the body. Recent studies have demonstrated the benefits of using a nebulizer or an inhaler to administer chelating agents for the decorporation of actinides. Effective chelation therapy with large groups of internally contaminated people can be a challenge unless both the agent and the nanocarrier are readily available from strategic national stockpiles for radiological or nuclear emergencies. Sunflower lecithin is particularly adept at alleviating the burden of administration when used to form liposomes as a nanocarrier for pulmonary delivery of diethylenetriamine-pentaacetic acid (DTPA) or hydroxypyridinone (HOPO). Better physiologically-based pharmacokinetic models must be developed for each agent in order to minimize the frequency of multiple doses that can overload the emergency response operations.

Fragment molecular orbital calculations for biomolecules

Exploring biomolecule behavior, such as proteins and nucleic acids, using quantum mechanical theory can identify many life science phenomena from first principles. Fragment molecular orbital (FMO) calculations of whole single particles of biomolecules can determine the electronic state of the interior and surface of molecules and explore molecular recognition mechanisms based on intermolecular and intramolecular interactions. In this review, we summarized the current state of FMO calculations in drug discovery, virology, and structural biology, as well as recent developments from data science.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Quantum Mechanics Helps Uncover Atypical Recognition Features in the Flavin Mononucleotide Riboswitch

Estimating the binding energies of small molecules to RNA could help uncover their molecular recognition characteristics and be used to rationally design RNA-targeting chemical probes. Here, we leveraged the ability of the fragment molecular orbital (FMO) method to provide detailed pairwise energetic information to examine the interactions between the aptamer domain of the flavin mononucleotide (FMN)-responsive riboswitch and small-molecule ligands. After developing an efficient protocol for executing high-level FMO calculations on RNA-ligand complexes, we applied our protocol to nine FMN-aptamer-ligand complexes. We then used the results to identify "hot-spots" within the aptamer and decomposed pairwise interactions between the hot-spot residues and the ligands. Interestingly, we found that several of these hot-spot residues interact with the ligands via atypical CH···O hydrogen bonds and anion-π contacts, as well as (face-to-edge) T-shaped π-π interactions. We envision that our results should pave the way for the wider and more prominent use of FMO calculations to study structure-energy relationships in diverse RNA-ligand systems, which in turn may provide a basis for dissecting the molecular recognition characteristics of RNAs.

Molecular Dynamics Study of Conformational Changes of Tankyrase 2 Binding Subsites upon Ligand Binding

The interactions between proteins and ligands are involved in various biological functions. While experimental structures provide key static structural information of ligand-unbound and ligand-bound proteins, dynamic information is often insufficient for understanding the detailed mechanism of protein-ligand binding. Here, we studied the conformational changes of the tankyrase 2 binding pocket upon ligand binding using molecular dynamics simulations of the ligand-unbound and ligand-bound proteins. The ligand-binding pocket has two subsites: the nicotinamide and adenosine subsite. Comparative analysis of these molecular dynamics trajectories revealed that the conformational change of the ligand-binding pocket was characterized by four distinct conformations of the ligand-binding pocket. Two of the four conformations were observed only in molecular dynamics simulations. We found that the pocket conformational change on ligand binding was based on the connection between the nicotinamide and adenosine subsites that are located adjacently in the pocket. From the analysis, we proposed the protein-ligand binding mechanism of tankyrase 2. Finally, we discussed the computational prediction of the ligand binding pose using the tankyrase 2 structures obtained from the molecular dynamics simulations.

Taking Water into Account with the Fragment Molecular Orbital Method

This chapter describes the current status of development of the fragment molecular orbital (FMO) method for analyzing the electronic state and intermolecular interactions of biomolecular systems in solvent. The orbital energies and the inter-fragment interaction energies (IFIEs) for a specific molecular structure can be obtained directly by performing FMO calculations by exposing water molecules and counterions around biomolecular systems. Then, it is necessary to pay attention to the thickness of the water shell surrounding the biomolecules. The single-point calculation for snapshots from MD trajectory does not incorporate the effects of temperature and configurational fluctuation, but the SCIFIE (statistically corrected IFIE) method is proposed as a many-body correlated method that partially compensates for this deficiency. Furthermore, implicit continuous dielectric models have been developed as effective approaches to incorporating the screening effect of the solvent in thermal equilibrium, and we illustrate their usefulness for theoretical evaluation of IFIEs and ligand-binding free energy on the basis of the FMO-PBSA (Poisson-Boltzmann surface area) method and other computational methods.