Energy Decomposition Analysis in Solution Based on the Fragment Molecular Orbital Method

Unprecedented carbonic anhydrase inhibition mechanism: Targeting histidine 64 side chain through a halogen bond

2,2'-Thio-bis(4,6-dichlorophenol), namely bithionol, is a small molecule endowed with a multifaceted bioactivity. Its peculiar polychlorinated phenolic structure makes it a suitable candidate to explore its potentialities in establishing interaction patterns with enzymes of MedChem interest, such as the human carbonic anhydrase (hCA) metalloenzymes. Herein, bithionol was tested on a panel of specific hCAs through the stopped-flow technique, showing a promising micromolar inhibitory activity for the hCA II isoform. X-ray crystallographic studies revealed an unprecedented halogen-bond interaction between one chlorine of bithionol and the N3(ε) atom of the hCA II catalytically active histidine residue, His64. Then, quantum mechanics calculations based on the fragment molecular orbital method allowed us to estimate the strength of this bond (~2.9 kcal/mol) and highlighted the contribution of a rich hydrophobic interaction network within the isoenzyme. Interestingly, the compound inactivity against the hCA III isoform, characterized by His64Lys and Leu198Phe mutations, supported the key role played by halogen bonding in the enzyme affinity. This finding might pave the way for the development of a new class of hCA inhibitors characterized by such chemical features, with the halogen bond being a key ligand-receptor interaction.

Importance of Charge Balance for the Embedding of Zwitterionic Solutes in the Fragment Molecular Orbital Method

Three new schemes of induced solvent charges for the auxiliary polarization formulation of the fragment molecular orbital method are proposed and compared to the original approach. It is found that the charge balance of the solute and solvent embeddings is crucial for maintaining a proper gap between occupied and virtual orbitals of fragments for zwitterionic systems in solution. The original instability is eliminated with the new scheme of fragment-specific solvent charges. The developed stable embedding method is applied to perform MP2/aug-cc-pVTZ calculations of a protein-ligand complex containing 1102 amino acid residues.

Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand-Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors

Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.

Partition analysis of dipole moments in solution applied to functional groups in polypeptide motifs

A partition analysis based on segments is developed for density functional theory defining solute dipole moments of functional groups, and the corresponding induced solvent dipoles representing solvent screening. The accuracy of dipoles from the fragment molecular orbital method is evaluated in comparison to unfragmented values. The analysis is applied to evaluate dipole moments of side chains, amino and carbonyl groups in common polypeptide motifs, α-helixes, β-turns, and random coils in solution. The membrane domain of the ATP synthase (1B9U) is analyzed, revealing the effect of the bend splitting of the α-helix into two pieces.

A computational insight on the aromatic amino acids conjugation with [Cp*Rh(H2O)3]2+ by using the meta-dynamics/FMO3 approach

CONTEXT

Rh(III) complexes demonstrated to exert promising pharmacological effects with potential applications as anti-cancer, anti-bacterial, and antimicrobial agents. One important Rh(III)-ligand is the pentamethylcyclopentadienyl (Cp*) group forming in water the [Cp*Rh(H2O)3]2+ complex. Among of its attractive chemical properties is the ability to react specifically with Tyr amino acid side chain of G-protein-coupled receptor (GPCR) peptides by means of highly chemoselective bioconjugation reaction, at room temperature and at pH 5-6. In this computational work, in order to deepen the mechanism of this chemoselective conjugation, we study the ligand exchange reaction between [Cp*Rh(H2O)3]2+ and three small molecules, namely p-cresol, 3-methylimidazole, and toluene, selected as mimetic of aromatic side chains of tyrosine (Tyr), tryptophan (Trp) and phenylalanine (Phe), respectively. Our outcomes suggest that the high selectivity for Tyr side chain might be related to OH group able to affect both thermodynamic and kinetic of ligand exchange reaction, due to its ability to act as both H bond acceptor and donor. These mechanistic aspects can be used to design new metal drugs containing the [Cp*Rh]2+ scaffold targeting specifically Tyr residues involved in biological/pathological processes such as phosphorylation by means of Tyr-kinase enzyme and protein-protein interactions.

METHODS

The geometry of three encounter complexes and product adducts were optimized at the B3LYP//CPCM/ωB97X-D level of theory, adopting the 6-311+G(d,p) basis set for all non-metal atoms and the LANL2DZ pseudopotential for the Rh atom. Meta-dynamics RMSD (MTD(RMSD)) calculations at GFN2-xTB level of theory were performed in NVT conditions at 298.15 K to investigate the bioconjugation reactions (simulation time: 100 ps; integration step 2.0; implicit solvent model: GBSA). The MTD(RMSD) simulation was performed in two replicates for each encounter complex. Final representative subsets of 100 structures for each run were gained with a sampling rate of 1 ps and analyzed by performing single point calculations using the FMO3 method at RI-MP2/6-311G//PCM[1] level of theory, adopting the MCP-TZP core potential for Rh atom.

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.

Probing RNA-Small Molecule Interactions Using Biophysical and Computational Approaches

Interest in small molecules that target RNA is flourishing, and the expectation set on them to treat diseases with unmet medical needs is high. However, several challenges remain, including difficulties in selecting suitable tools and establishing workflows for their discovery. In this context, we optimized experimental and computational approaches that were previously employed for the protein targets. Here, we demonstrate that a fluorescence-based assay can be effectively used to screen small molecule libraries for their ability to bind and stabilize an RNA stem-loop. Our screen identified several fluoroquinolones that bind to the target stem-loop. We further probed their interactions with the target using biolayer interferometry, isothermal titration calorimetry (ITC), and nuclear magnetic resonance spectroscopy. The results of these biophysical assays suggest that the fluoroquinolones bind the target in a similar manner. Armed with this knowledge, we built models for the complexes of the fluoroquinolones and the RNA target. Then, we performed fragment molecular orbital (FMO) calculations to dissect the interactions between the fluoroquinolones and the RNA. We found that the binding free energies obtained from the ITC experiments correlated strongly with the interaction energies calculated by FMO. Finally, we designed fluoroquinolone analogues and performed FMO calculations to predict their binding free energies. Taken together, the results of this study support the importance of conducting orthogonal assays in binding confirmation and compound selection and demonstrate the usefulness of FMO calculations in the rational design of RNA-targeted small molecules.

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.

Structural basis of transcription regulation by CNC family transcription factor, Nrf2

Several basic leucine zipper (bZIP) transcription factors have accessory motifs in their DNA-binding domains, such as the CNC motif of CNC family or the EHR motif of small Maf (sMaf) proteins. CNC family proteins heterodimerize with sMaf proteins to recognize CNC-sMaf binding DNA elements (CsMBEs) in competition with sMaf homodimers, but the functional role of the CNC motif remains elusive. In this study, we report the crystal structures of Nrf2/NFE2L2, a CNC family protein regulating anti-stress transcriptional responses, in a complex with MafG and CsMBE. The CNC motif restricts the conformations of crucial Arg residues in the basic region, which form extensive contact with the DNA backbone phosphates. Accordingly, the Nrf2-MafG heterodimer has approximately a 200-fold stronger affinity for CsMBE than canonical bZIP proteins, such as AP-1 proteins. The high DNA affinity of the CNC-sMaf heterodimer may allow it to compete with the sMaf homodimer on target genes without being perturbed by other low-affinity bZIP proteins with similar sequence specificity.

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.

Interaction between the Human OX2 Orexin Receptor and Suvorexant and Some of Its Analogues: SAPT (DFT) Interaction Energy Decomposition Analysis

In this study, the interaction energy (E_int) of suvorexant (as an orexin receptor antagonist) and some of its analogues with the important residues of the human OX2 orexin receptor, determined by molecular docking, is calculated using the symmetry-adapted perturbation theory-density functional theory (SAPT (DFT)) method. Also, the important residues with the dominant interaction with each ligand are determined based on the obtained SAPT (DFT) interaction energies. To analyze the interaction of the receptor with each ligand, the decomposition of E_int to its constituent components including electrostatic (E_ele), exchange (E_ex), induction (E_ind), and exchange-induction (E_ex-ind), dispersion (E_disp), and exchange-dispersion (E_ex-disp) is performed. The change of interaction energy components with the replacement of the benzoxazole part of suvorexant by pyrimidine containing different functional groups, thieno pyrimidine, and furo pyrimidine is also investigated, separately. It is found that the change in E_int, due to these replacements, is controlled more by the variation of the electrostatic interaction energy component of E_int than by the other interaction energy components. A linear correlation (R² = 0.91) is found for the variation of E_int versus experimental ligand-binding affinities. Also, the existence of the linear correlation for the variation of the interaction energy components with experimental ligand-binding affinities is investigated. The variation of the electrostatic component versus experimental ligand-binding affinities shows a more linear correlation compared to the other interaction energy components.

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.

A Study on the Effect of the Substituent against PAK4 Inhibition Using In Silico Methods

The intrinsic inductive properties of atoms or functional groups depend on the chemical properties of either electron-withdrawing groups (EWGs) or electron-donating groups (EDGs). This study aimed to evaluate in silico methods to determine whether changes in chemical properties of the compound by single atomic substitution affect the biological activity of target proteins and whether the results depend on the properties of the functional groups. We found an imidazo[4,5-b]pyridine-based PAK4 inhibitor, compound 1, as an initial hit compound with the well-defined binding mode for PAK4. In this study, we used both experimental and in silico methods to investigate the effect of atomic substitution on biological activity to optimize the initial hit compound. In biological assays, in the case of EWG, as the size of the halogen atom became smaller and the electronegativity increased, the biological activity IC₅₀ value ranged from 5150 nM to inactive; in the case of EDG, biological activity was inactive. Furthermore, we analyzed the interactions of PAK4 with compounds, focusing on the hinge region residues, L398 and E399, and gatekeeper residues, M395 and K350, of the PAK4 protein using molecular docking studies and fragment molecular orbital (FMO) methods to determine the differences between the effect of EWG and EDG on the activity of target proteins. These results of the docking score and binding energy did not explain the differences in biological activity. However, the pair-interaction energy obtained from the results of the FMO method indicated that there was a difference in the interaction energy between the EWG and EDG in the hinge region residues, L398 and E399, as well as in M395 and K350. The two groups with different properties exhibited opposite electrostatic energy and charge transfer energy between L398 and E399. Additionally, we investigated the electron distribution of the parts interacting with the hinge region by visualizing the molecular electrostatic potential (MEP) surface of the compounds. In conclusion, we described the properties of functional groups that affect biological activity using an in silico method, FMO.

Designing boron and metal complexes for fluoride recognition: a computational perspective

Fluoride anions (F^-) may have beneficial or harmful effects on the environment depending on their concentration. Here, we shed light on F^- recognition by compounds containing boron, tellurium and antimony, which were experimentally demonstrated to be capable of interacting with the F^- ion in a partially aqueous medium. Boron and metal complexes recognize F^- anions primarily using electrostatic energy along with important contributions from orbital interaction energy. The natural orbitals for chemical valence (NOCV) methodology indicates that the main orbital interactions behind fluoride recognition are σ bonds between the receptors and the F^- anions. The charged receptors, which provide (i) two B atoms, (ii) one B atom and one Sb atom, or (iii) one B atom and one Te atom to directly interact with the F^- ions, appear to be some of the best structures for the recognition of F^- anions. This is supported by the combination of favorable electrostatic and σ bond interactions. Overall, the presence of electron donor groups, such as -CH₃ and -OH, in the receptor structure destabilizes the fluoride recognition because it decreases the attractive electrostatic energy and increases the Pauli repulsion energy in the receptor⋯F^- bonds. Notably, electron acceptor groups, for example, -CN and -NO₂, in the receptor structure favor the interaction with the F^- ions, due to the improvement of the electrostatic and σ bond interactions. This study opens the way to find the main features of a receptor for F^- recognition.

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.

Intermolecular Interaction Analyses on SARS-CoV-2 Spike Protein Receptor Binding Domain and Human Angiotensin-Converting Enzyme 2 Receptor-Blocking Antibody/Peptide Using Fragment Molecular Orbital Calculation

The spike glycoprotein (S-protein) mediates SARS-CoV-2 entry via intermolecular interaction with human angiotensin-converting enzyme 2. The receptor binding domain (RBD) of the S-protein has been considered critical for this interaction and acts as the target of numerous neutralizing antibodies and antiviral peptides. This study used the fragment molecular orbital method to analyze the interactions between the RBD and antibodies/peptides and extracted crucial residues that can be used as epitopes. The interactions evaluated as interfragment interaction energy values between the RBD and 12 antibodies/peptides showed a fairly good correlation with the experimental activity pIC50 (R2 = 0.540). Nine residues (T415, K417, Y421, F456, A475, F486, N487, N501, and Y505) were confirmed as being crucial. Pair interaction energy decomposition analyses showed that hydrogen bonds, electrostatic interactions, and π-orbital interactions are important. Our results provide essential information for understanding SARS-CoV-2-antibody/peptide binding and may play roles in future antibody/antiviral drug design.

Molecular recognition of SARS-CoV-2 spike glycoprotein: quantum chemical hot spot and epitope analyses

Due to the COVID-19 pandemic, researchers have attempted to identify complex structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein (S-protein) with angiotensin-converting enzyme 2 (ACE2) or a blocking antibody. However, the molecular recognition mechanism-critical information for drug and antibody design-has not been fully clarified at the amino acid residue level. Elucidating such a microscopic mechanism in detail requires a more accurate molecular interpretation that includes quantum mechanics to quantitatively evaluate hydrogen bonds, XH/π interactions (X = N, O, and C), and salt bridges. In this study, we applied the fragment molecular orbital (FMO) method to characterize the SARS-CoV-2 S-protein binding interactions with not only ACE2 but also the B38 Fab antibody involved in ACE2-inhibitory binding. By analyzing FMO-based interaction energies along a wide range of binding interfaces carefully, we identified amino acid residues critical for molecular recognition between S-protein and ACE2 or B38 Fab antibody. Importantly, hydrophobic residues that are involved in weak interactions such as CH-O hydrogen bond and XH/π interactions, as well as polar residues that construct conspicuous hydrogen bonds, play important roles in molecular recognition and binding ability. Moreover, through these FMO-based analyses, we also clarified novel hot spots and epitopes that had been overlooked in previous studies by structural and molecular mechanical approaches. Altogether, these hot spots/epitopes identified between S-protein and ACE2/B38 Fab antibody may provide useful information for future antibody design, evaluation of the binding property of the SARS-CoV-2 variants including its N501Y, and small or medium drug design against the SARS-CoV-2.

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.

Guiding Medicinal Chemistry with Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between a protein and a small molecule plays a key role in the rationalization of potency and selectivity and in design of new ideas. However, even when a target of interest is structurally enabled, visual inspection and force field-based molecular mechanics calculations cannot always explain the full complexity of the molecular interactions that are critical in drug design. Quantum mechanical methods have the potential to address this shortcoming, but traditionally, computational expense has made the application of these calculations impractical. The fragment molecular orbital (FMO) method offers a solution that combines accuracy, speed, and the ability to characterize important interactions (i.e. its strength in kcal/mol and chemical nature: hydrophobic, electrostatic, etc) that would otherwise be hard to detect. In this chapter, we describe the FMO method and illustrate its application in the discovery of the benzothiazole (BZT) series as novel tyrosine kinase ITK inhibitors for treatment of allergic asthma.

Analyzing GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

G-protein-coupled receptors (GPCRs) have enormous physiological and biomedical importance, and therefore it is not surprising that they are the targets of many prescribed drugs. Further progress in GPCR drug discovery is highly dependent on the availability of protein structural information. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanics (QM) approaches are often too computationally expensive to be of practical use in time-sensitive situations, 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. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule toward ligand binding, including an analysis of their chemical nature. Such information is essential for an efficient structure-based drug design (SBDD) process. In this chapter, we describe how to use FMO in the characterization of GPCR-ligand interactions.

Consistent inclusion of continuum solvation in energy decomposition analysis: theory and application to molecular CO2 reduction catalysts

To facilitate computational investigation of intermolecular interactions in the solution phase, we report the development of ALMO-EDA(solv), a scheme that allows the application of continuum solvent models within the framework of energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs). In this scheme, all the quantum mechanical states involved in the variational EDA procedure are computed with the presence of solvent environment so that solvation effects are incorporated in the evaluation of all its energy components. After validation on several model complexes, we employ ALMO-EDA(solv) to investigate substituent effects on two classes of complexes that are related to molecular CO2 reduction catalysis. For [FeTPP(CO2-κC)]2- (TPP = tetraphenylporphyrin), we reveal that two ortho substituents which yield most favorable CO2 binding, -N(CH3)3 + (TMA) and -OH, stabilize the complex via through-structure and through-space mechanisms, respectively. The coulombic interaction between the positively charged TMA group and activated CO2 is found to be largely attenuated by the polar solvent. Furthermore, we also provide computational support for the design strategy of utilizing bulky, flexible ligands to stabilize activated CO2 via long-range Coulomb interactions, which creates biomimetic solvent-inaccessible "pockets" in that electrostatics is unscreened. For the reactant and product complexes associated with the electron transfer from the p-terphenyl radical anion to CO2, we demonstrate that the double terminal substitution of p-terphenyl by electron-withdrawing groups considerably strengthens the binding in the product state while moderately weakens that in the reactant state, which are both dominated by the substituent tuning of the electrostatics component. These applications illustrate that this new extension of ALMO-EDA provides a valuable means to unravel the nature of intermolecular interactions and quantify their impacts on chemical reactivity in solution.

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.

Characterizing Interhelical Interactions of G-Protein Coupled Receptors with the Fragment Molecular Orbital Method

G-protein coupled receptors (GPCRs) are the largest superfamily of membrane proteins, regulating almost every aspect of cellular activity and serving as key targets for drug discovery. We have identified an accurate and reliable computational method to characterize the strength and chemical nature of the interhelical interactions between the residues of transmembrane (TM) domains during different receptor activation states, something that cannot be characterized solely by visual inspection of structural information. Using the fragment molecular orbital (FMO) quantum mechanics method to analyze 35 crystal structures representing different branches of the class A GPCR family, we have identified 69 topologically equivalent TM residues that form a consensus network of 51 inter-TM interactions, providing novel results that are consistent with and help to rationalize experimental data. This discovery establishes a comprehensive picture of how defined molecular forces govern specific interhelical interactions which, in turn, support the structural stability, ligand binding, and activation of GPCRs.

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.

Characterising GPCR-ligand interactions using a fragment molecular orbital-based approach

There has been fantastic progress in solving GPCR crystal structures. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanical approaches (QM) are often too computationally expensive, 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. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule towards ligand binding, including an analysis of their chemical nature.

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.

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.

Intramolecular Natural Energy Decomposition Analysis: Applications to the Rational Design of Foldamers

We describe an intramolecular version of the natural energy decomposition analysis (NEDA), with the aim of evaluating interactions between molecular fragments across covalent bonds. The electronic energy in intramolecular natural energy decomposition analysis (INEDA) is divided into electrical, core, and charge transfer components. The INEDA method describes the fragments using the nonfragmented electronic density, and, therefore, there are no limitations in how to choose the boundary orbital. We used INEDA to evaluate the interaction energies that give origin to barriers of rotation around C_amide C_aromatic (C_am C_ar ) and N_amide C_aromtaic (N_am C_ar ) bonds in arylamide-foldamer building blocks. We found that differences of barrier height between models with different ortho-aryl substituents stem from charge transfer and core interactions. In three-center hydrogen-bond (H-bond) models with an NH proton donor H-bound to two electronegative ortho-aryl substituents, the interaction energy of the three-center system is larger than in either of the two-center H-bond subsystem alone, indicating an increase of overall rigidity. The combination of INEDA and NEDA allows the evaluation of intermolecular and intramolecular interactions using a consistent theoretical framework. © 2018 Wiley Periodicals, Inc.

Perspective: Found in translation: Quantum chemical tools for grasping non-covalent interactions

Today's quantum chemistry methods are extremely powerful but rely upon complex quantities such as the massively multidimensional wavefunction or even the simpler electron density. Consequently, chemical insight and a chemist's intuition are often lost in this complexity leaving the results obtained difficult to rationalize. To handle this overabundance of information, computational chemists have developed tools and methodologies that assist in composing a more intuitive picture that permits better understanding of the intricacies of chemical behavior. In particular, the fundamental comprehension of phenomena governed by non-covalent interactions is not easily achieved in terms of either the total wavefunction or the total electron density, but can be accomplished using more informative quantities. This perspective provides an overview of these tools and methods that have been specifically developed or used to analyze, identify, quantify, and visualize non-covalent interactions. These include the quantitative energy decomposition analysis schemes and the more qualitative class of approaches such as the Non-covalent Interaction index, the Density Overlap Region Indicator, or quantum theory of atoms in molecules. Aside from the enhanced knowledge gained from these schemes, their strengths, limitations, as well as a roadmap for expanding their capabilities are emphasized.

Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity. It is essential for an efficient structure-based drug design (SBDD) process. FMO enables ab initio approaches to be applied to systems that conventional quantum-mechanical (QM) methods would find challenging. The key advantage of the Fragment Molecular Orbital Method (FMO) is that it can reveal atomistic details about the individual contributions and chemical nature of each residue and water molecule toward ligand binding which would otherwise be difficult to detect without using QM methods. In this chapter, we demonstrate the typical use of FMO to analyze 19 crystal structures of β1 and β2 adrenergic receptors with their corresponding agonists and antagonists.

Theoretical Analysis of Activity Cliffs among Benzofuranone-Class Pim1 Inhibitors Using the Fragment Molecular Orbital Method with Molecular Mechanics Poisson-Boltzmann Surface Area (FMO+MM-PBSA) Approach

Significant activity changes due to small structural changes (i.e., activity cliffs) of serine/threonine kinase Pim1 inhibitors were studied theoretically using the fragment molecular orbital method with molecular mechanics Poisson-Boltzmann surface area (FMO+MM-PBSA) approach. This methodology enables quantum-chemical calculations for large biomolecules with solvation. In the course of drug discovery targeting Pim1, six benzofuranone-class inhibitors were found to differ only in the position of the indole-ring nitrogen atom. By comparing the various qualities of complex structures based on X-ray, classical molecular mechanics (MM)-optimized, and quantum/molecular mechanics (QM/MM)-optimized structures, we found that the QM/MM-optimized structures provided the best correlation (R² = 0.85) between pIC₅₀ and the calculated FMO+MM-PBSA binding energy. Combining the classical solvation energy with the QM binding energy was important to increase the correlation. In addition, decomposition of the interaction energy into various physicochemical components by pair interaction energy decomposition analysis suggested that CH-π and electrostatic interactions mainly caused the activity differences.