Interaction energy analysis on specific binding of influenza virus hemagglutinin to avian and human sialosaccharide receptors: Importance of mutation-induced structural change

Protein-Protein Interaction Modelling with the Fragment Molecular Orbital Method

Fragment molecular orbital (FMO) method enables ab initio quantum-chemical calculations for biomolecular systems with high accuracy and moderate computational cost. Through this analysis we can evaluate the inter-fragment interaction energies (IFIEs) that provide useful measures for effective interactions between the fragments representing amino-acid residues and ligand molecules. Here I describe how to prepare the input structures and perform the FMO calculations for protein-protein complex system. In addition to the pre-processing, some useful tools for the post-processing analysis are also illustrated.

Hotspot Identification and Drug Design of Protein-Protein Interaction Modulators Using the Fragment Molecular Orbital Method

Protein-protein interactions (PPIs) are essential for the function of many proteins. Aberrant PPIs have the potential to lead to disease, making PPIs promising targets for drug discovery. There are over 64,000 PPIs in the human interactome reference database; however, to date, very few PPI modulators have been approved for clinical use. Further development of PPI-specific therapeutics is highly dependent on the availability of structural data and the existence of reliable computational tools to explore the interface between two interacting proteins. The fragment molecular orbital (FMO) quantum mechanics method offers comprehensive and computationally inexpensive means of identifying the strength (in kcal/mol) and the chemical nature (electrostatic or hydrophobic) of the molecular interactions taking place at the protein-protein interface. We have integrated FMO and PPI exploration (FMO-PPI) to identify the residues that are critical for protein-protein binding (hotspots). To validate this approach, we have applied FMO-PPI to a dataset of protein-protein complexes representing several different protein subfamilies and obtained FMO-PPI results that are in agreement with published mutagenesis data. We observed that critical PPIs can be divided into three major categories: interactions between residues of two proteins (intermolecular), interactions between residues within the same protein (intramolecular), and interactions between residues of two proteins that are mediated by water molecules (water bridges). We extended our findings by demonstrating how this information obtained by FMO-PPI can be utilized to support the structure-based drug design of PPI modulators (SBDD-PPI).

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.

Interaction analyses of SARS-CoV-2 spike protein based on fragment molecular orbital calculations

At the stage of SARS-CoV-2 infection in human cells, the spike protein consisting of three chains, A, B, and C, with a total of 3300 residues plays a key role, and thus its structural properties and the binding nature of receptor proteins to host human cells or neutralizing antibodies has attracted considerable interest. Here, we report on interaction analyses of the spike protein in both closed (PDB-ID: 6VXX) and open (6VYB) structures, based on large-scale fragment molecular orbital (FMO) calculations at the level of up to the fourth-order Møller–Plesset perturbation with singles, doubles, and quadruples (MP4(SDQ)). Inter-chain interaction energies were evaluated for both structures, and a mutual comparison indicated considerable losses of stabilization energies in the open structure, especially in the receptor binding domain (RBD) of chain-B. The role of charged residues in inter-chain interactions was illuminated as well. By two separate calculations for the RBD complexes with angiotensin-converting enzyme 2 (ACE2) (6M0J) and B38 Fab antibody (7BZ5), it was found that the binding with ACE2 or antibody partially compensated for this stabilization loss of RBD.

Visualized IFIE results seen from chain-B of spike protein.

Identification of correlated inter-residue interactions in protein complex based on the fragment molecular orbital method

A theoretical scheme to systematically describe correlated (network-like) interactions between molecular fragments is proposed within the framework of the fragment molecular orbital (FMO) method. The method is mathematically based on the singular value decomposition (SVD) of the inter-fragment interaction energy (IFIE) matrix obtained by the FMO calculation, and can be applied to a comprehensive description of protein-protein interactions in the context of molecular recognition. In the present study we apply the proposed method to a complex of measles virus hemagglutinin and human SLAM receptor, thus finding a usefulness for efficiently eliciting the correlated interactions among the amino-acid residues involved in the two proteins. Additionally, collective interaction networks by amino-acid residues important for mutation experiments can be clearly visualized.

Fragment Molecular Orbital Based Interaction Analyses on COVID-19 Main Protease - Inhibitor N3 Complex (PDB ID: 6LU7)

The worldwide spread of COVID-19 (new coronavirus found in 2019) is an emergent issue to be tackled. In fact, a great amount of works in various fields have been made in a rather short period. Here, we report a fragment molecular orbital (FMO) based interaction analysis on a complex between the SARS-CoV-2 main protease (Mpro) and its peptide-like inhibitor N3 (PDB ID: 6LU7). The target inhibitor molecule was segmented into five fragments in order to capture site specific interactions with amino acid residues of the protease. The interaction energies were decomposed into several contributions, and then the characteristics of hydrogen bonding and dispersion stabilization were made clear. Furthermore, the hydration effect was incorporated by the Poisson-Boltzmann (PB) scheme. From the present FMO study, His41, His163, His164, and Glu166 were found to be the most important amino acid residues of Mpro in interacting with the inhibitor, mainly due to hydrogen bonding. A guideline for optimizations of the inhibitor molecule was suggested as well based on the FMO analysis.

Systematic Interaction Analysis of Anti-Human Immunodeficiency Virus Type-1 Neutralizing Antibodies with High Mannose Glycans Using Fragment Molecular Orbital and Molecular Dynamics Methods

A series of broadly neutralizing antibodies called PGT have been shown to be bound directly to human immunodeficiency virus type-1 via high mannose glycans on glycoprotein gp120. Despite the sequence similarities of amino acids of the antibodies, their affinities to the glycan differ. Glycan-antibody interactions among these antibodies are systematically compared with quantum chemical fragment molecular orbital calculations and molecular dynamics simulations. The differences among structural stability of the glycan in the active site of the complexes and total interaction energies as well as binding free energies between the glycan and antibodies agree well with the experimentally shown affinities of the glycan to the antibodies. The terminal saccharide, Man D3, is structurally stable and responsible for the glycan-antibody binding through electrostatic and dispersion interactions. The structural stability of nonterminal saccharides such as Man 4 or Man C plays substantial roles in the interaction via direct hydrogen bonds. © 2019 Wiley Periodicals, Inc.

Towards good correlation between fragment molecular orbital interaction energies and experimental IC50 for ligand binding: A case study of p38 MAP kinase

We describe several procedures for the preprocessing of fragment molecular orbital (FMO) calculations on p38 mitogen-activated protein (MAP) kinase and discuss the influence of the procedures on the protein–ligand interaction energies represented by inter-fragment interaction energies (IFIEs). The correlation between the summation of IFIEs for a ligand and amino acid residues of protein (IFIE-sum) and experimental affinity values (IC₅₀) was poor when considered for the whole set of protein–ligand complexes. To improve the correlation for prediction of ligand binding affinity, we carefully classified data set by the ligand charge, the DFG-loop state (DFG-in/out loop), which is characteristic of kinase, and the scaffold of ligand. The correlation between IFIE-sums and the activity values was examined using the classified data set. As a result, it was confirmed that there was a selected data set that showed good correlation between IFIE-sum and activity value by appropriate classification. In addition, we found that the differences in protonation and hydrogen orientation caused by subtle differences in preprocessing led to a relatively large difference in IFIE values. Further, we also examined the effect of structure optimization with different force fields. It was confirmed that the difference in the force field had no significant effect on IFIE-sum. From the viewpoint of drug design using FMO calculations, various investigations on IFIE-sum in this research, such as those regarding several classifications of data set and the different procedures of structural preparation, would be expected to provide useful knowledge for improvement of prediction ability about the ligand binding affinity.

Computational Analysis of the Interaction Energies between Amino Acid Residues of the Measles Virus Hemagglutinin and Its Receptors

Measles virus (MV) causes an acute and highly devastating contagious disease in humans. Employing the crystal structures of three human receptors, signaling lymphocyte-activation molecule (SLAM), CD46, and Nectin-4, in complex with the measles virus hemagglutinin (MVH), we elucidated computationally the details of binding energies between the amino acid residues of MVH and those of the receptors with an ab initio fragment molecular orbital (FMO) method. The calculated inter-fragment interaction energies (IFIEs) revealed a number of significantly interacting amino acid residues of MVH that played essential roles in binding to the receptors. As predicted from previously reported experiments, some important amino-acid residues of MVH were shown to be common but others were specific to interactions with the three receptors. Particularly, some of the (non-polar) hydrophobic residues of MVH were found to be attractively interacting with multiple receptors, thus indicating the importance of the hydrophobic pocket for intermolecular interactions (especially in the case of Nectin-4). In contrast, the electrostatic interactions tended to be used for specific molecular recognition. Furthermore, we carried out FMO calculations for in silico experiments of amino acid mutations, finding reasonable agreements with virological experiments concerning the substitution effect of residues. Thus, the present study demonstrates that the electron-correlated FMO method is a powerful tool to search exhaustively for amino acid residues that contribute to interactions with receptor molecules. It is also applicable for designing inhibitors of MVH and engineered MVs for cancer therapy.

The role of conserved QXG and binding affinity of S23G & S26G receptors on avian H5, swine H1 and human H1 of influenza A virus hemagglutinin

Outbreaks of avian, human and swine influenza are a serious concern for public health. In the reproductive cycle of the influenza virus, hemagglutinin (HA) is the primary protein responsible for binding to glycan receptor sites on the host cell surface. MD simulations of avian H5, swine H1 and human H1 complexed with S23G and S26G receptors were performed to study the role of key residues on the receptor conformational behaviors, hydrogen bond formation, binding free energy and residue-wise energy contribution. The obtained results indicated that the relative energies of swH1_S23G and swH1_S26G were found to be close to each other (3.1 kcal/mol) while the relative energies of AvH5 and HuH1 were found to be significantly different (11.1 ± 6.8 and 29.0 ± 8.2 kcal/mol for AvH5 and HuH1, respectively).

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.