Subsystem Analysis for the Fragment Molecular Orbital Method and Its Application to Protein-Ligand Binding in Solution

Prediction of Binding Pose and Affinity of Nelfinavir, a SARS-CoV-2 Main Protease Repositioned Drug, by Combining Docking, Molecular Dynamics, and Fragment Molecular Orbital Calculations

A novel in silico drug design procedure is described targeting the Main protease (Mpro) of the SARS-CoV-2 virus. The procedure combines molecular docking, molecular dynamics (MD), and fragment molecular orbital (FMO) calculations. The binding structure and properties of Mpro were predicted for Nelfinavir (NFV), which had been identified as a candidate compound through drug repositioning, targeting Mpro. Several poses of the Mpro and NFV complexes were generated by docking, from which four docking poses were selected by scoring with FMO energy. Then, each pose was subjected to MD simulation, 100 snapshot structures were sampled from each of the generated MD trajectories, and the structures were evaluated by FMO calculations to rank the pose based on binding energy. Several residues were found to be important in ligand recognition, including Glu47, Asp48, Glu166, Asp187, and Gln189, all of which interacted strongly with NFV. Asn142 is presumably regarded to form hydrogen bonds or CH/π interaction with NFV; however, in the present calculation, their interactions were transient. Moreover, the tert-butyl group of NFV had no interaction with Mpro. Identifying such strong and weak interactions provides candidates for maintaining and substituting ligand functional groups and important suggestions for drug discovery using drug repositioning. Besides the interaction between NFV and the amino acid residues of Mpro, the desolvation effect of the binding pocket also affected the ranking order. A similar procedure of drug design was applied to Lopinavir, and the calculated interaction energy and experimental inhibitory activity value trends were consistent. Our approach provides a new guideline for structure-based drug design starting from a candidate compound whose complex crystal structure has not been obtained.

Analysis of Site Energies and Excitonic Couplings: The Role of Symmetry and Polarization

An excitonic coupling model is developed based on an equation-of-motion coupled cluster combined with the fragment molecular orbital method. The effects of polarization and excitonic coupling on the splitting of quasi-degenerate levels in systems containing multiple chromophores are elucidated on dimers of formaldehyde, water, formic acid, hydrogen fluoride, and carbon monoxide. It is shown that the level structure is mainly determined by the mutual polarization of chromophores and to a lesser extent by the excitonic coupling. The role of symmetry in excitonic coupling in dimers is discussed. The excitonic coupling between all residues in the photoactive yellow protein (PDB: 2PHY) is analyzed.

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).

Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals

Polarization and charge transfer strongly characterize the ligand-receptor interaction when metal atoms are present, as for the Au(I)-biscarbene/DNA G-quadruplex complexes. In a previous work (J Comput Aided Mol Des2022, 36, 851-866) we used the ab initio FMO2 method at the RI-MP2/6-31G* level of theory with the PCM [1] solvation approach to calculate the binding energy (ΔEFMO) of two Au(I)-biscarbene derivatives, [Au(9-methylcaffein-8-ylidene)2]+ and [Au(1,3-dimethylbenzimidazole-2-ylidene)2]+, able to interact with DNA G-quadruplex motif. We found that ΔEFMO and ligand-receptor pair interaction energies (EINT) show very large negative values making the direct comparison with experimental data difficult and related this issue to the overestimation of the embedded charge transfer energy between fragments containing metal atoms. In this work, to improve the accuracy of the FMO method for predicting the binding affinity of metal-based ligands interacting with DNA G-quadruplex (Gq), we assess the effect of the following computational features: (i) the electron correlation, considering the Hartree-Fock (HF) and a post-HF method, namely RI-MP2; (ii) the two (FMO2) and three-body (FMO3) approaches; (iii) the basis set size (polarization functions and double-ζ vs. triple-ζ) and (iv) the embedding electrostatic potential (ESP). Moreover, the partial screening method was systematically adopted to simulate the solvent screening effect for each calculation. We found that the use of the ESP computed using the screened point charges for all atoms (ESP-SPTC) has a critical impact on the accuracy of both ΔEFMO and EINT, eliminating the overestimation of charge transfer energy and leading to energy values with magnitude comparable with typical experimental binding energies. With this computational approach, EINT values describe the binding efficiency of metal-based binders to DNA Gq more accurately than ΔEFMO. Therefore, to study the binding process of metal containing systems with the FMO method, the adoption of partial screening solvent method combined with ESP-SPCT should be considered. This computational protocol is suggested for FMO calculations on biological systems containing metals, especially when the adoption of the default ESP treatment leads to questionable results.

How E-, L-, and P-Selectins Bind to sLex and PSGL-1: A Quantification of Critical Residue Interactions

Selectins and their ability to interact with specific ligands are a cornerstone in cell communication. Over the last three decades, a considerable wealth of experimental and molecular modeling insights into their structure and modus operandi were gathered. Nonetheless, explaining the role of individual selectin residues on a quantitative level remained elusive, despite its importance in understanding the structure-function relationship in these molecules and designing their inhibitors. This work explores essential interactions of selectin-ligand binding, employing a multiscale approach that combines molecular dynamics, quantum-chemical calculations, and residue interaction network models. Such an approach successfully reproduces most of the experimental findings. It proves to be helpful, with the potential for becoming an established tool for quantitative predictions of residue contribution to the binding of biomolecular complexes. The results empower us to quantify the importance of particular residues and functional groups in the protein-ligand interface and to pinpoint differences in molecular recognition by the three selectins. We show that mutations in the E-, L-, and P-selectins, e.g., different residues in positions 46, 85, 97, and 107, present a crucial difference in how the ligand is engaged. We assess the role of sulfation of tyrosine residues in PSGL-1 and suggest that TyrSO3- in position 51 interacting with Arg85 in P-selectin is a significant factor in the increased affinity of P-selectin to PSGL-1 compared to E- and L-selectins. We propose an original pharmacophore targeting five essential PSGL-binding sites based on the analysis of the selectin···PSGL-1 interactions.

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.

The FMO2 analysis of the ligand-receptor binding energy: the Biscarbene-Gold(I)/DNA G-Quadruplex case study

In this work, the ab initio fragment molecular orbital (FMO) method was applied to calculate and analyze the binding energy of two biscarbene-Au(I) derivatives, [Au(9-methylcaffein-8-ylidene)₂]⁺ and [Au(1,3-dimethylbenzimidazol-2-ylidene)₂]⁺, to the DNA G-Quadruplex structure. The FMO2 binding energy considers the ligand-receptor complex as well as the isolated forms of energy-minimum state of ligand and receptor, providing a better description of ligand-receptor affinity compared with simple pair interaction energies (PIE). Our results highlight important features of the binding process of biscarbene-Au(I) derivatives to DNA G-Quadruplex, indicating that the total deformation-polarization energy and desolvation penalty of the ligands are the main terms destabilizing the binding. The pair interaction energy decomposition analysis (PIEDA) between ligand and nucleobases suggest that the main interaction terms are electrostatic and charge-transfer energies supporting the hypothesis that Au(I) ion can be involved in π-cation interactions further stabilizing the ligand-receptor complex. Moreover, the presence of polar groups on the carbene ring, as C = O, can improve the charge-transfer interaction with K⁺ ion. These findings can be employed to design new powerful biscarbene-Au(I) DNA-G quadruplex binders as promising anticancer drugs. The procedure described in this work can be applied to investigate any ligand-receptor system and is particularly useful when the binding process is strongly characterized by polarization, charge-transfer and dispersion interactions, properly evaluated by ab initio methods.

The Importance of Charge Transfer and Solvent Screening in the Interactions of Backbones and Functional Groups in Amino Acid Residues and Nucleotides

Quantum mechanical (QM) calculations at the level of density-functional tight-binding are applied to a protein–DNA complex (PDB: 2o8b) consisting of 3763 atoms, averaging 100 snapshots from molecular dynamics simulations. A detailed comparison of QM and force field (Amber) results is presented. It is shown that, when solvent screening is taken into account, the contributions of the backbones are small, and the binding of nucleotides in the double helix is governed by the base–base interactions. On the other hand, the backbones can make a substantial contribution to the binding of amino acid residues to nucleotides and other residues. The effect of charge transfer on the interactions is also analyzed, revealing that the actual charge of nucleotides and amino acid residues can differ by as much as 6 and 8% from the formal integer charge, respectively. The effect of interactions on topological models (protein -residue networks) is elucidated.

Homodimeric complexes of the 90-231 human prion: a multilayered computational study based on FMO/GRID-DRY approach

The molecular interaction properties and aggregation capabilities disclosed by PrP-E200K, a pathogenic mutant of the human prion protein, were investigated in detail using multilayered computational approaches. In a previous work, we reported that the electrostatic complementarity between region1 (negative) and region3 (positive) has been assumed to lead to a head-to tail interaction between 120 and 231 PrP-E200K units and to initiation of the aggregation process. In this work, we extended the PrP-E200K structure by including the unstructured 90–120 segment which was found to assume different conformations. Plausible models of 90–231 PrP-E200K dimers were calculated and analyzed in depth to identify the nature of the involved protein–protein interactions. The unstructured 90–120 segment was found to extend the positively charged region3 involved in the association of PrP-E200K units which resulted to be driven by hydrophobic interactions. The combination of molecular dynamics, protein–protein docking, grid-based mapping, and fragment molecular orbital approaches allowed us to provide a plausible mechanism of the early state of 90–231 PrP-E200K aggregation, considered a preliminary step of amyloid conversion.

Polarization energies in the fragment molecular orbital method

Using isolated and polarized states of fragments, a method for computing the polarization energies in density functional theory (DFT) and density-functional tight-binding (DFTB) is developed in the framework of the fragment molecular orbital method. For DFTB, the method is extended into the use of periodic boundary conditions (PBC), for which a new component, a periodic self-polarization energy, is derived. The couplings of the polarization to other components in the pair interaction energy analysis (PIEDA) are derived for DFT and DFTB, and compared to Hartree-Fock and second-order Møller-Plesset perturbation theory (MP2). The effect of the self-consistent (DFT) and perturbative (MP2) treatment of the electron correlation on the polarization is discussed. The difference in the polarization in the bulk (PBC) and micro (cluster) solvation is elucidated.

Free Energy Decomposition Analysis Based on the Fragment Molecular Orbital Method

A decomposition of the free energy is developed in the many-body expansion framework of the fragment molecular orbital (FMO) method combined with umbrella sampling molecular dynamics (MD). In FMO/MD simulations, performed with density-functional tight-binding and periodic boundary conditions, all atoms are treated quantum mechanically. The free energy is computed and decomposed for a series of S_N2 Menshutkin reactions in water. The barrier lowering by the solvent is attributed to the competition between the solvent polarization and the solute-solvent interactions including charge transfer.

Analysis of Guest Adsorption on Crystal Surfaces Based on the Fragment Molecular Orbital Method

For gaining insights into interactions in periodic systems, an analysis is developed based on the fragment molecular orbital method combined with periodic boundary conditions. The adsorption energy is decomposed into guest and surface polarization and deformation energy, guest-surface and guest-guest interactions, and the vibrational free energy. The analysis is applied to the adsorption of guest molecules to Ih (001) ice surface. The cooperativity effects result in a non-linear change in the adsorption energy with coverage due to many-body effects. The role of dispersion is found to be dominant for guests with long hydrophobic tails. A rule is proposed relating the length of the alkyl tail with the formation of the guest layer. The computed binding enthalpies are in good agreement with experimental values. For high coverage, adsorbed molecules can form an ordered layer known as self-assembled monolayer.

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.

pyProGA-A PyMOL plugin for protein residue network analysis

The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.

Partitioning of the Vibrational Free Energy

Vibrational energies are partitioned into the contributions of molecular parts called segments, for instance, residues in proteins. The fragment molecular orbital method is used to facilitate vibrational calculations of large systems at the DFTB and HF-3c levels. The vibrational analysis is combined with the partitioning of the electronic energy, yielding free-energy contributions of segments to the binding energy, pinpointing hot spots for drug discovery and other studies. The analysis is illustrated on two protein-ligand complexes in solution.

The fragment molecular orbital method combined with density-functional tight-binding and periodic boundary conditions

The density-functional tight-binding (DFTB) formulation of the fragment molecular orbital method is combined with periodic boundary conditions. Long-range electrostatics and dispersion are evaluated with the Ewald summation technique. The first analytic derivatives of the energy with respect to atomic coordinates and lattice parameters are formulated. The accuracy of the method is established in comparison to numerical gradients and DFTB without fragmentation. The largest elementary cell in this work has 1631 atoms. The method is applied to elucidate the polarization, charge transfer, and interactions in the solution.

FMODB: The World's First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method

We developed the world's first web-based public database for the storage, management, and sharing of fragment molecular orbital (FMO) calculation data sets describing the complex interactions between biomacromolecules, named FMO Database (https://drugdesign.riken.jp/FMODB/). Each entry in the database contains relevant background information on how the data was compiled as well as the total energy of each molecular system and interfragment interaction energy (IFIE) and pair interaction energy decomposition analysis (PIEDA) values. Currently, the database contains more than 13 600 FMO calculation data sets, and a comprehensive search function implemented at the front-end. The procedure for selecting target proteins, preprocessing the experimental structures, construction of the database, and details of the database front-end were described. Then, we demonstrated a use of the FMODB by comparing IFIE value distributions of hydrogen bond, ion-pair, and XH/π interactions obtained by FMO method to those by molecular mechanics approach. From the comparison, the statistical analysis of the data provided standard reference values for the three types of interactions that will be useful for determining whether each interaction in a given system is relatively strong or weak compared to the interactions contained within the data in the FMODB. In the final part, we demonstrate the use of the database to examine the contribution of halogen atoms to the binding affinity between human cathepsin L and its inhibitors. We found that the electrostatic term derived by PIEDA greatly correlated with the binding affinities of the halogen containing cathepsin L inhibitors, indicating the importance of QM calculation for quantitative analysis of halogen interactions. Thus, the FMO calculation data in FMODB will be useful for conducting statistical analyses to drug discovery, for conducting molecular recognition studies in structural biology, and for other studies involving quantum mechanics-based interactions.

Computational Methods for Biochemical Simulations Implemented in GAMESS

Computational methods for modeling biochemical processes implemented in GAMESS package are reviewed; in particular, quantum mechanics combined with molecular mechanics (QM/MM), semi-empirical, and fragmentation approaches. A detailed summary of capabilities is provided for the QM/MM implementation in QuanPol program and the fragment molecular orbital (FMO) method. Molecular modeling and visualization packages useful for biochemical simulations with GAMESS are described. GAMESS capabilities with corresponding references are tabulated for reader's convenience.

Partition Analysis for Density-Functional Tight-Binding

High-order charge transfer is incorporated into the fragment molecular orbital (FMO) method using a charge transfer state with fractional charges. This state is used for a partition analysis of properties based on segments that may be different from fragments in FMO. The partition analysis is also formulated for calculations without fragmentation. All development in this work is limited to density-functional tight-binding. The analysis is applied to a water cluster, crambin (PDB: 1CBN), and two complexes of Trp-cage (1L2Y) with ligands. The contributions of functional groups in ligands are obtained, providing useful information for drug discovery.

Measles Virus Hemagglutinin Protein Establishes a Specific Interaction With the Extreme N-Terminal Region of Human Signaling Lymphocytic Activation Molecule to Enhance Infection

Measles virus (MV) is a human pathogen that is classified in the genus Morbillivirus in the family Paramyxoviridae together with several non-human animal morbilliviruses. They cause severe systemic infections by using signaling lymphocytic activation molecule (SLAM) and poliovirus receptor-like 4 expressed on immune and epithelial cells, respectively, as receptors. The viral hemagglutinin (H) protein is responsible for the receptor-binding. Previously determined structures of MV-H and SLAM complexes revealed a major binding interface between the SLAM V domain and MV-H with four binding components (sites 1–4) in the interface. We studied the MV-H and human SLAM (hSLAM) complex structure in further detail by in silico analyses and determined missing regions or residues in the previously determined complex structures. These analyses showed that, in addition to sites 1–4, MV-H establishes a unique interaction with the extreme N-terminal region (ExNTR) of hSLAM. The first principles calculation-based fragment molecular orbital computation method revealed that methionine at position 29 (hSLAM-Met29) is the key residue for the interaction. hSLAM-Met29 was predicted to establish a CH-π interaction with phenylalanine at position 549 of MV-H (MVH-Phe549). A cell-cell fusion assay showed that the hSLAM-Met29 and MVH-Phe549 interaction is important for hSLAM-dependent MV membrane fusion. Furthermore, Jurkat cell lines expressing hSLAM with or without Met29 and recombinant MV possessing the H protein with or without Phe549 showed that the hSLAM-Met29 and MVH-Phe549 interaction enhanced hSLAM-dependent MV infection by ~10-fold. We speculate that in the evolutionary history of morbilliviruses, this interaction may have contributed to MV adaptation to humans because this interaction is unique for MV and only MV uses hSLAM efficiently among morbilliviruses.

Characterization of PD-L1 binding sites by a combined FMO/GRID-DRY approach

The programmed cell death protein 1 (PD-1) and its ligand, PD-L1, constitute an important co-inhibitory immune checkpoint leading to downregulation of immune system. Tumor cells developed a strategy to trigger PD-1/PD-L1 pathway reducing the T cell anticancer activity. Anti-PD-L1 small drugs, generally with improved pharmacokinetic and technological profiles than monoclonal antibodies, became an attractive research topic. Nevertheless, still few works have been published on the chemical features of possible binding sites. In this work, we applied a novel computational protocol based on the combination of the ab initio Fragment Molecular Orbital (FMO) method and a newly developed GRID-DRY approach in order to characterize the PD-L1 binding sites, starting from PD-1/PD-L1 and PD-L1/BMS-ligands (Bristol-Mayers Squibb ligands) complexes. The FMO method allows the calculation of the pair-residues as well as the ligand-residues interactions with ab initio accuracy, whereas the GRID-DRY approach is an effective tool to investigate hydrophobic interactions, not easily detectable by ab initio methods. The present GRID-DRY protocol is able to determine the energy contributions of each ligand atoms to each hydrophobic interaction, both qualitatively and quantitatively. We were also able to identify the three specific hot regions involved in PD-1/PD-L1 protein-protein interaction and in PD-L1/BMS-ligand interactions, in agreement with preceding theoretical/experimental results, and to suggest a specific pharmacophore for PD-L1 inhibitors.

Geometry Optimization, Transition State Search, and Reaction Path Mapping Accomplished with the Fragment Molecular Orbital Method

Recent development of the fragment molecular orbital (FMO) method related to energy gradients, geometry optimization, transition state search, and chemical reaction mapping is summarized. The frozen domain formulation of FMO is introduced in detail, and the structure of related GAMESS input files for FMO is described.

Analyzing Interactions with the Fragment Molecular Orbital Method

Basic concepts in the analysis of binding using the fragment molecular orbital method are discussed at length: polarization, desolvation, and interaction. The components in the pair interaction energy decomposition analysis are introduced, and the analysis is illustrated for a water dimer and a protein-ligand complex.

Characterizing Protein-Protein Interactions with the Fragment Molecular Orbital Method

Proteins are vital components of living systems, serving as building blocks, molecular machines, enzymes, receptors, ion channels, sensors, and transporters. Protein-protein interactions (PPIs) are a key part of their function. There are more than 645,000 reported disease-relevant PPIs in the human interactome, but drugs have been developed for only 2% of these targets. The advances in PPI-focused drug discovery are highly dependent on the availability of structural data and accurate computational tools for analysis of this data. Quantum mechanical approaches are often too expensive computationally, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed and the ability to reveal key interactions that would otherwise be hard to detect. FMO provides essential information for PPI drug discovery, namely, identification of key interactions formed between residues of two proteins, including their strength (in kcal/mol) and their chemical nature (electrostatic or hydrophobic). In this chapter, we have demonstrated how three different FMO-based approaches (pair interaction energy analysis (PIE analysis), subsystem analysis (SA) and analysis of protein residue networks (PRNs)) have been applied to study PPI in three protein-protein complexes.

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.

Solvent Screening in Zwitterions Analyzed with the Fragment Molecular Orbital Method

Based on induced solvent charges, a new model of solvent screening is developed in the framework of the fragment molecular orbital combined with the polarizable continuum model. The developed model is applied to analyze interactions in a prototypical zwitterionic system, sodium chloride in water, and it is shown that the large underestimation of the interaction in the original solvent screening based on local charges is successfully corrected. The model is also applied to a complex of the Trp-cage (PDB: 1L2Y ) miniprotein with an anionic ligand, and the physical factors determined protein-ligand binding in solution are unraveled.

Investigation of Hot Spot Region in XIAP Inhibitor Binding Site by Fragment Molecular Orbital Method

X-linked inhibitor of apoptosis protein (XIAP) is an important regulator of cancer cell survival whose BIR3 domain (XIAP-BIR3) recognizes the Smac N-terminal tetrapeptide sequence (AVPI), making it an attractive protein-protein interaction (PPI) target for cancer therapies. We used the fragment molecular orbital (FMO) method to study the binding modes and affinities between XIAP-BIR3 and a series of its inhibitors (1–8) that mimic the AVPI binding motif; the inhibitors had common interactions with key residues in a hot spot region of XIAP-BIR3 (P1–P4 subpockets) with increased binding affinity mainly attributed to specific interactions with the P1 and P4 subpockets. Based on the structural information from FMO results, we proposed a novel XIAP natural product inhibitor, neoeriocitrin 10, which was derived from our preciously reported XIAP-BIR3 inhibitor 9, can be used as a highly potent candidate for XIAP-BIR3 inhibition. We also performed pair interaction energy decomposition analysis to investigate the binding energies between specific binding residues and individual ligands, showing that the novel natural product neoeriocitrin 10 had a higher binding affinity than epicatechin gallate 9. Molecular docking and dynamics simulations were performed to explore the mode of binding between 10 and XIAP-BIR3, demonstrating that 10 binds more strongly to the P1 and P4 pockets than 9. Overall, we present a novel natural product, neoeriocitrin 10, and demonstrate that the FMO method can be used to identify hot spots in PPIs and design new compounds for XIAP inhibition.

The Fragment Molecular Orbital Method Based on Long-Range Corrected Density-Functional Tight-Binding

The presently available linear scaling approaches to density-functional tight-binding (DFTB) based on the fragment molecular orbital (FMO) method are severely impacted by the problem of artificial charge transfer due to the self-interaction error (SIE), which hampers the simulation of zwitterionic systems such as biopolymers or ionic liquids. Here we report an extension of FMO-DFTB where we included a long-range corrected (LC) functional designed to mitigate the DFTB SIE, called the FMO-LC-DFTB method, resulting in a robust method which succeeds in simulating zwitterionic systems. Both energy and analytic gradient are developed for the gas phase and the polarizable continuum model of solvation. The scaling of FMO-LC-DFTB with system size N is shown to be almost linear, O( N^1.13-1.28), and its numerical accuracy is established for a variety of representative systems including neutral and charged polypeptides. It is shown that pair interaction energies between fragments for two mini-proteins are in excellent agreement with results from long-range corrected density functional theory. The new method was employed in long time scale (1 ns) molecular dynamics simulations of the tryptophan cage protein (PDB: 1L2Y ) in the gas phase for four different protonation states and in stochastic global minimum structure searches for 1-ethyl-3-methylimidazolium nitrate ionic liquid clusters containing up to 2300 atoms.

Simulations of infrared and Raman spectra in solution using the fragment molecular orbital method

Calculation of IR and Raman spectra in solution for large molecular systems made possible with analytic FMO/PCM Hessians.

Fragment Molecular Orbital Calculations with Implicit Solvent Based on the Poisson-Boltzmann Equation: II. Protein and Its Ligand-Binding System Studies

In this study, the electronic properties of bioactive proteins were analyzed using an ab initio fragment molecular orbital (FMO) methodology in solution: coupling with an implicit solvent model based on the Poisson-Boltzmann surface area called as FMO-PBSA. We investigated the solvent effects on practical and heterogeneous targets with uneven exposure to solvents unlike deoxyribonucleic acid analyzed in our recent study. Interfragment interaction energy (IFIE) and its decomposition analyses by FMO-PBSA revealed solvent-screening mechanisms that affect local stability inside ubiquitin protein: the screening suppresses excessiveness in bare charge-charge interactions and enables an intuitive IFIE analysis. The electrostatic character and associated solvation free energy also give consistent results as a whole to previous studies on the explicit solvent model. Moreover, by using the estrogen receptor alpha (ERα) protein bound to ligands, we elucidated the importance of specific interactions that depend on the electric charge and activatability as agonism/antagonism of the ligand while estimating the influences of the implicit solvent on the ligand and helix-12 bindings. The predicted ligand-binding affinities of bioactive compounds to ERα also show a good correlation with their in vitro activities. The FMO-PBSA approach would thus be a promising tool both for biological and pharmaceutical research targeting proteins.

Protein Residue Networks from Energetic and Geometric Data: Are They Identical?

Protein residue networks (PRN) from energetic and geometric data are probably not identical. PRNs constructed from ab initio pair interaction energies are analyzed for the first time and compared to PRN based on center of mass separation. We use modern, previously unused algorithms such as global and local efficiencies to quantitatively confirm that both types of PRNs do exhibit small-world character. The main novelty finding is that interaction energy-based PRNs preserve small-world character even when clustered. A node hierarchy independent of the cutoff energy used for the edge creation is characteristic for them. Efficiency centrality identifies hubs responsible for such behavior. The interaction energy-based PRNs seem to comply with the scale-free network model with respect to efficiency centrality distribution as opposed to distance based PRNs. Community detection is introduced into protein network research as an extension beyond cluster analysis to study tertiary and quaternary structures.

An insight of early PrP-E200K aggregation by combined molecular dynamics/fragment molecular orbital approaches

Unveiling the events leading to the formation of prion particles is a nowadays challenge in the field of neurochemistry. Pathogenic mutants of prion protein (PrP) are characterized by both an intrinsic tendency to aggregation and scrapie conversion propensity. However, the question about a possible correlation between these two events lasts still unanswered. Here, a multilayered computational workflow was employed to investigate structure, stability, and molecular interaction properties of a dimer of PrP^C -E200K, a well-known mutant of the PrP that represents a reduced model of early aggregates of this protein. Based on the combination of molecular dynamics and quantum mechanical approaches, this study provided for an in depth insight of PrP^C -E200K dimer in terms of residue-residue interactions. Assembly hypotheses for the early aggregation of PrP^C -E200K are paved and compared with PrP^Sc models reported in the literature to find a structural link between early and late (scrapie) aggregates of this protein.

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

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.

Comparative Binding Analysis of Dipeptidyl Peptidase IV (DPP-4) with Antidiabetic Drugs - An Ab Initio Fragment Molecular Orbital Study

Dipeptidyl peptidase IV (DPP-4) enzyme is responsible for the degradation of incretins that stimulates insulin secretion and hence inhibition of DPP-4 becomes an established approach for the treatment of type 2 diabetics. We studied the interaction between DPP-4 and its inhibitor drugs (sitagliptin 1, linagliptin 2, alogliptin 3, and teneligliptin 4) quantitatively by using fragment molecular orbital calculations at the RI-MP2/cc-pVDZ level to analyze the inhibitory activities of the drugs. Apart from having common interactions with key residues, inhibitors encompassing the DPP-4 active site extensively interact widely with the hydrophobic pocket by their hydrophobic inhibitor moieties. The cumulative hydrophobic interaction becomes stronger for these inhibitors and hence linagliptin and teneligliptin have larger interaction energies, and consequently higher inhibitory activities, than their alogliptin and sitagliptin counterparts. Though effective interaction for both 2 and 3 is at [Formula: see text] subsite, 2 has a stronger binding to this subsite interacting with Trp629 and Tyr547 than 3 does. The presence of triazolopiperazine and piperazine moiety in 1 and 4, respectively, provides the interaction to the S2 extensive subsite; however, the latter's superior inhibitory activity is not only due to a relatively tighter binding to the S2 extensive subsite, but also due to the interactions to the S1 subsite. The calculated hydrophobic interfragment interaction energies correlate well with the experimental binding affinities (KD) and inhibitory activities (IC50) of the DPP-4 inhibitors.

The fragment molecular orbital method combined with density-functional tight-binding and the polarizable continuum model

The electronic gap in proteins is analyzed in detail, and it is shown that FMO-DFTB/PCM is efficient and accurate in describing the molecular structure of proteins in solution.