Correlation Analyses on Binding Affinity of Sialic Acid Analogues and Anti-Influenza Drugs with Human Neuraminidase Using ab Initio MO Calculations on Their Complex Structures – LERE-QSAR Analysis (IV)

Leveraging the Fragment Molecular Orbital Method to Explore the PLK1 Kinase Binding Site and Polo-Box Domain for Potent Small-Molecule Drug Design

Polo-like kinase 1 (PLK1) plays a pivotal role in cell division regulation and emerges as a promising therapeutic target for cancer treatment. Consequently, the development of small-molecule inhibitors targeting PLK1 has become a focal point in contemporary research. The adenosine triphosphate (ATP)-binding site and the polo-box domain in PLK1 present crucial interaction sites for these inhibitors, aiming to disrupt the protein's function. However, designing potent and selective small-molecule inhibitors can be challenging, requiring a deep understanding of protein-ligand interaction mechanisms at these binding sites. In this context, our study leverages the fragment molecular orbital (FMO) method to explore these site-specific interactions in depth. Using the FMO approach, we used the FMO method to elucidate the molecular mechanisms of small-molecule drugs binding to these sites to design PLK1 inhibitors that are both potent and selective. Our investigation further entailed a comparative analysis of various PLK1 inhibitors, each characterized by distinct structural attributes, helping us gain a better understanding of the relationship between molecular structure and biological activity. The FMO method was particularly effective in identifying key binding features and predicting binding modes for small-molecule ligands. Our research also highlighted specific "hot spot" residues that played a critical role in the selective and robust binding of PLK1. These findings provide valuable insights that can be used to design new and effective PLK1 inhibitors, which can have significant implications for developing anticancer therapeutics.

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.

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.

Quantum chemical calculations investigated molecular recognition of SARS-CoV-2 spike glycoproteins including its N501Y variant for ACE2 and antibody. Hot spot and epitope analyses revealed key residues to design drugs and antibodies against COVID-19.

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.

Energetic Mechanism of Cytochrome c-Cytochrome c Oxidase Electron Transfer Complex Formation under Turnover Conditions Revealed by Mutational Effects and Docking Simulation

Based on the mutational effects on the steady-state kinetics of the electron transfer reaction and our NMR analysis of the interaction site (Sakamoto, K., Kamiya, M., Imai, M., Shinzawa-Itoh, K., Uchida, T., Kawano, K., Yoshikawa, S., and Ishimori, K. (2011) Proc. Natl. Acad. Sci. U.S.A. 108, 12271-12276), we determined the structure of the electron transfer complex between cytochrome c (Cyt c) and cytochrome c oxidase (CcO) under turnover conditions and energetically characterized the interactions essential for complex formation. The complex structures predicted by the protein docking simulation were computationally selected and validated by the experimental kinetic data for mutant Cyt c in the electron transfer reaction to CcO. The interaction analysis using the selected Cyt c-CcO complex structure revealed the electrostatic and hydrophobic contributions of each amino acid residue to the free energy required for complex formation. Several charged residues showed large unfavorable (desolvation) electrostatic interactions that were almost cancelled out by large favorable (Columbic) electrostatic interactions but resulted in the destabilization of the complex. The residual destabilizing free energy is compensated by the van der Waals interactions mediated by hydrophobic amino acid residues to give the stabilized complex. Thus, hydrophobic interactions are the primary factors that promote complex formation between Cyt c and CcO under turnover conditions, whereas the change in the electrostatic destabilization free energy provides the variance of the binding free energy in the mutants. The distribution of favorable and unfavorable electrostatic interactions in the interaction site determines the orientation of the binding of Cyt c on CcO.

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

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

Novel pH-dependent regulation of human cytosolic sialidase 2 (NEU2) activities by siastatin B and structural prediction of NEU2/siastatin B complex

Human cytosolic sialidase (Neuraminidase 2, NEU2) catalyzes the removal of terminal sialic acid residues from glycoconjugates. The effect of siastatin B, known as a sialidase inhibitor, has not been evaluated toward human NEU2 yet. We studied the regulation of NEU2 activity by siastatin B in vitro and predicted the interaction in silico. Inhibitory and stabilizing effects of siastatin B were analyzed in comparison with DANA (2-deoxy-2,3-dehydro-N-acetylneuraminic acid) toward 4-umbelliferyl N-acetylneuraminic acid (4-MU-NANA)- and α2,3-sialyllactose-degrading activities of recombinant NEU2 produced by E. coli GST-fusion gene expression. Siastatin B exhibited to have higher competitive inhibitory activity toward NEU2 than DANA at pH 4.0. We also revealed the stabilizing effect of siastatin B toward NEU2 activity at acidic pH. Docking model was constructed on the basis of the crystal structure of NEU2/DANA complex (PDB code: 1VCU). Molecular docking predicted that electrostatic neutralization of E111 and E218 residues of the active pocket should not prevent siastatin B from binding at pH 4.0. The imino group (¹NH) of siastatin B can also interact with D46, neutralized at pH 4.0. Siastatin B was suggested to have higher affinity to the active pocket of NEU2 than DANA, although it has no C7-9 fragment corresponding to that of DANA. We demonstrated here the pH-dependent affinity of siastatin B toward NEU2 to exhibit potent inhibitory and stabilizing activities. Molecular interaction between siastatin B and NEU2 will be utilized to develop specific inhibitors and stabilizers (chemical chaperones) not only for NEU2 but also the other human sialidases, including NEU1, NEU3 and NEU4, based on homology modeling.

Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems

Recent developments in the fragment molecular orbital (FMO) method for theoretical formulation, implementation, and application to nano and biomolecular systems are reviewed. The FMO method has enabled ab initio quantum-mechanical calculations for large molecular systems such as protein-ligand complexes at a reasonable computational cost in a parallelized way. There have been a wealth of application outcomes from the FMO method in the fields of biochemistry, medicinal chemistry and nanotechnology, in which the electron correlation effects play vital roles. With the aid of the advances in high-performance computing, the FMO method promises larger, faster, and more accurate simulations of biomolecular and related systems, including the descriptions of dynamical behaviors in solvent environments. The current status and future prospects of the FMO scheme are addressed in these contexts.

A QSAR study on the inhibition mechanism of matrix metalloproteinase-12 by arylsulfone analogs based on molecular orbital calculations

The inhibition mechanism of matrix metalloproteinase-12 by arylsulfone analogs is revealed using a comprehensive computational approach including docking simulations, molecular orbital calculations, and QSAR.

Connecting Classical QSAR and LERE Analyses Using Modern Molecular Calculations, LERE-QSAR (VI): Hydrolysis of Substituted Hippuric Acid Phenyl Esters by Trypsin

The reaction mechanism of trypsin was studied by applying DFT and ab initio molecular orbital (MO) calculations to complexes of trypsin with a congeneric series of eight para-substituted hippuric acid phenyl esters, for which a previous quantitative structureactivity relationship (QSAR) study revealed nice linearity of Hammett substitution constant σ(-) with logarithmic values of the MichaelisMenten and catalytic rate constants. Based on the LERE procedure, we performed QSAR analyses on each elementary reaction step during the acylation process. The present calculations showed that the rate-determining step during the acylation process is the transition state (TS) between the enzymesubstrate complex (ES) and tetrahedral intermediate (TET), and that the proton transfer occurs from Ser195 to His57, not between His57 and Asp102. The LERE-QSAR analysis statistically suggested that the variation of overall free-energy changes leading to formation of TS is governed mostly by that of activation energies required to form TS from ES. In spite of a very limited number of congeneric ligands in the current work, it is critically essential to clarify and verify physicochemical meanings of a typical QSAR/Chemoinformatics parameter, Hammett σ(-) based on quantum chemical calculations on the proteinligand kinetics; how Hammett σ(-) behaves in terms of proteinligand interaction energies.

Inhibitors of the human neuraminidase enzymes

A review of known small molecule inhibitors and substrates of the human neuraminidase enzymes.

Structural, functional and molecular docking study to characterize GMI1 from Arabidopsis thaliana

γ-irradiation and Mitomycin C Induced 1 (GMI1), is a member of the SMC-hinge domain-containing protein family that takes part in double stranded break repair mechanism in eukaryotic cells. In this study we hypothesize a small molecule-Adenosine Tri Phosphate (ATP) binding region of novel SMC like GM1 protein in model organism Arabidopsis thaliana using in silico modeling. Initially, analyzing sequence information for the protein indicated presence of motifs - 'Walker A nucleotide-binding domain' that are required to interact with nucleotides along with 'Walker B' motif and ABC signature sequences. This was further proven through GMI1-ATP docking experiment and results were verified by comparing the values with controls. In negative control, no binding was seen in the same binding region of GMI1 structure for small molecules randomly selected form PubChem database, whereas in positive control binding affinity of other known proteins with ATP binding potential resembled GMI1-ATP binding affinity of -5.4 kcal/mol. Furthermore we also docked small molecules that shares structural similarity with ATP to GMI1 and found that Purine Mononucleotide bound the region with the best affinity, which implies that the compound may bind the protein with strong binding and can work as a potential agonist/antagonist to GMI1. We believe that the study would shed more light into the GM1 mechanism of action. Although the computational predictions made here are based on concrete confidence, it should be mentioned that in vitro experimentation does not fall into the scopes of this study and thus the results found here have to be further validated in vitro.

Three- and four-body corrected fragment molecular orbital calculations with a novel subdividing fragmentation method applicable to structure-based drug design

We develop an inter-fragment interaction energy (IFIE) analysis based on the three- and four-body corrected fragment molecular orbital (FMO3 and FMO4) method to evaluate the interactions of functional group units in structure-based drug design context. The novel subdividing fragmentation method for a ligand (in units of their functional groups) and amino acid residues (in units of their main and side chains) enables us to understand the ligand-binding mechanism in more detail without sacrificing chemical accuracy of the total energy and IFIEs by using the FMO4 method. We perform FMO4 calculations with the second order Møller-Plesset perturbation theory for an estrogen receptor (ER) and the 17β-estradiol (EST) complex using the proposed fragmentation method and assess the interaction for each ligand-binding site by the FMO4-IFIE analysis. When the steroidal EST is divided into two functional units including "A ring" and "D ring", respectively, the FMO4-IFIE analysis reveals their binding affinity with surrounding fragments of the amino acid residues; the "A ring" of EST has polarization interaction with the main chain of Thr347 and two hydrogen bonds with the side chains of Glu353 and Arg394; the "D ring" of EST has a hydrogen bond with the side chain of His524. In particular, the CH/π interactions of the "A ring" of EST with the side chains of Leu387 and Phe404 are easily identified in cooperation with the CHPI program. The FMO4-IFIE analysis using our novel subdividing fragmentation method, which provides higher resolution than the conventional IFIE analysis in units of ligand and each amino acid reside in the framework of two-body approximation, is a useful tool for revealing ligand-binding mechanism and would be applicable to rational drug design such as structure-based drug design and fragment-based drug design.

Combined QM/MM (ONIOM) and QSAR approach to the study of complex formation of matrix metalloproteinase‑9 with a series of biphenylsulfonamides−LERE-QSAR analysis (V)

We previously proposed a novel QSAR (quantitative structure-activity relationship) procedure called LERE (linear expression by representative energy terms)-QSAR involving molecular calculations such as an ab initio fragment molecular orbital ones. In the present work, we applied LERE-QSAR to complex formation of matrix metalloproteinase-9 (MMP-9) with a series of substituted biphenylsulfonamides. The results shows that the overall free-energy change accompanying complex formation is due to predominantly the contribution from the electrostatic interaction with the zinc atom in the active site of MMP-9. Carbonic anhydrase (CA) belongs to the zinc-containing protease family. In contrast to the current case of MMP-9, the overall free-energy change during complex formation of CA with a series of benzenesulfonamides is due to the contributions from the solvation and dissociation free-energy changes, as previously reported. Comparison of the two sets of results indicates quantitative differences in the relative contributions of free-energy components to the overall free-energy change between the two data sets, corresponding with those in the respective classical QSAR equations. The LERE-QSAR procedure was demonstrated to quantitatively reveal differences in the binding mechanisms between the two cases involving similar but different zinc-containing proteins at the electronic and atomic levels.

Reassessment of Hammett σ as an effective parameter representing intermolecular interaction energy-links between traditional and modern QSAR approaches

The Hammett σ constant has for a long time been known to be one of most important linear free-energy related parameters that correlate with biological activity. It is a conventionally used electronic parameter in studies of enzymatic quantitative structure-activity relationships (QSAR). However, it is not necessarily obvious why σ represents variations in the free-energy change associated with the complex formation between a congeneric series of ligands with their target protein. So far, several powerful molecular calculations, such as the ab initio fragment molecular orbital (FMO) one, that are directly applicable to ligand-protein complexes have emerged. In this study, we comprehensively reevaluate experimentally derived parameter σ confirming it represents intermolecular interaction energy terms, by applying molecular orbital (MO) calculations to a simple ligand-protein complex model. The current results provide a rational and quantitative basis for bridging the gap between the traditional QSAR approach and 'the modern QSAR one', which involves the molecular calculations to evaluate the overall free-energy change for complex formation.