Search Results (14)

The Variational Quantum Eigensolver (VQE) is a quantum algorithm for estimating ground-state energies, with promising applications in material science, drug discovery, and battery research. A key challenge is the limited number of qubits available on current quantum devices, which restricts the size of molecular systems that can be studied. To address this limitation, we apply the Fragment Molecular Orbital (FMO) method in combination with VQE, referred to as FMO-VQE. This approach divides a system into smaller fragments, making the quantum calculations more tractable. While earlier studies demonstrated this method only for hydrogen clusters, we extend the application to lithium cobalt oxide, a widely used cathode material in lithium-ion batteries. Using FMO-VQE, we estimate the ground-state energy of this complex system while reducing the number of required qubits from 24 to 14, without significant loss of accuracy compared to classical methods. This reduction highlights the potential of FMO-VQE to overcome hardware limitations and make quantum simulations of larger molecules feasible. The results suggest a practical path for applying near-term quantum computers to real-world challenges, opening opportunities for advancements in the battery industry and drug design. Full article

Quantum mechanics (QM) revolutionizes drug discovery by providing precise molecular insights unattainable with classical methods. This review explores QM’s role in computational drug design, detailing key methods like density functional theory (DFT), Hartree–Fock (HF), quantum mechanics/molecular mechanics (QM/MM), and fragment molecular orbital (FMO). These methods model electronic structures, binding affinities, and reaction mechanisms, enhancing structure-based and fragment-based drug design. This article highlights the applicability of QM to various drug classes, including small-molecule kinase inhibitors, metalloenzyme inhibitors, covalent inhibitors, and fragment-based leads. Quantum computing’s potential to accelerate quantum mechanical (QM) calculations is discussed alongside novel applications in biological drugs (e.g., gene therapies, monoclonal antibodies, biosimilars), protein–receptor dynamics, and new therapeutic indications. A molecular dynamics (MD) simulation exercise is included to teach QM/MM applications. Future projections for 2030–2035 emphasize QM’s transformative impact on personalized medicine and undruggable targets. The qualifications and tools required for researchers, including advanced degrees, programming skills, and software such as Gaussian and Qiskit, are outlined, along with sources for training and resources. Specific publications on quantum mechanics (QM) in drug discovery relevant to QM and molecular dynamics (MD) studies are incorporated. Challenges, such as computational cost and expertise requirements, are addressed, offering a roadmap for educators and researchers to leverage quantum mechanics (QM) and molecular dynamics (MD) in drug discovery. Full article

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. Full article

The Hippo pathway controls organ size and homeostasis and is linked to numerous diseases, including cancer. The transcriptional enhanced associate domain (TEAD) family of transcription factors acts as a receptor for downstream effectors, namely yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), which binds to various transcription factors and is essential for stimulated gene transcription. YAP/TAZ-TEAD facilitates the upregulation of multiple genes involved in evolutionary cell proliferation and survival. TEAD1–4 overexpression has been observed in different cancers in various tissues, making TEAD an attractive target for drug development. The central drug-accessible pocket of TEAD is crucial because it undergoes a post-translational modification called auto-palmitoylation. Crystal structures of the C-terminal TEAD complex with small molecules are available in the Protein Data Bank, aiding structure-based drug design. In this study, we utilized the fragment molecular orbital (FMO) method, molecular dynamics (MD) simulations, shape-based screening, and molecular mechanics–generalized Born surface area (MM-GBSA) calculations for virtual screening, and we identified a novel non-covalent inhibitor—BC-001—with IC₅₀ = 3.7 μM in a reporter assay. Subsequently, we optimized several analogs of BC-001 and found that the optimized compound BC-011 exhibited an IC₅₀ of 72.43 nM. These findings can be used to design effective TEAD modulators with anticancer therapeutic implications. Full article

The dopamine D4 receptor (D4R) is a promising therapeutic target in widespread diseases, and the search for novel agonists and antagonists appears to be clinically relevant. The mechanism of binding to the receptor (R) for antagonists and agonists varies. In the present study, we conducted an in-depth computational study, teasing out key similarities and differences in binding modes, complex dynamics, and binding energies for D4R agonists and antagonists. The dynamic network method was applied to investigate the communication paths between the ligand (L) and G-protein binding site (GBS) of human D4R. Finally, the fragment molecular orbitals with pair interaction energy decomposition analysis (FMO/PIEDA) scheme was used to estimate the binding energies of L–R complexes. We found that a strong salt bridge with D3.32 initiates the inhibition of the dopamine D4 receptor. This interaction also occurs in the binding of agonists, but the change in the receptor conformation to the active state starts with interaction with cysteine C3.36. Such a mechanism may arise in the case of agonists unable to form a hydrogen bond with the serine S5.46, considered, so far, to be crucial in the activation of GPCRs. The energy calculations using the FMO/PIEDA method indicate that antagonists show higher residue occupancy of the receptor binding site than agonists, suggesting they could form relatively more stable complexes. Additionally, antagonists were characterized by repulsive interactions with S5.46 distinguishing them from agonists. Full article

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). Full article

Alzheimer’s disease (AD) is a neurological disease, and its signs and symptoms appear slowly over time. Although current Alzheimer’s disease treatments can alleviate symptoms, they cannot prevent the disease from progressing. To accurately diagnose and treat Alzheimer’s disease, it is therefore necessary to establish effective methods for diagnosis. Apolipoprotein E4 (ApoE4), the most frequent genetic risk factor for AD, is expressed in more than half of patients with AD, making it an attractive target for AD therapy. We used molecular docking simulations, classical molecular mechanics optimizations, and ab initio fragment molecular orbital (FMO) calculations to investigate the specific interactions between ApoE4 and the naturally occurring compounds found in the plant Moringa Oleifera. According to the FMO calculations, quercetin had the highest binding affinity to ApoE4 among the sixteen compounds because its hydroxyl groups generated strong hydrogen bonds with the ApoE4 residues Trp11, Asp12, Arg15, and Asp130. As a result, we proposed various quercetin derivatives by introducing a hydroxyl group into quercetin and studied their ApoE4 binding properties. The FMO data clearly showed that adding a hydroxyl group to quercetin improved its binding capacity to ApoE4. Furthermore, ApoE4 Trp11, Asp12, Arg15, and Asp130 residues were discovered to be required for significant interactions between ApoE4 and quercetin derivatives. They had a higher ApoE4 binding affinity than our previously proposed epicatechin derivatives. Accordingly, the current results evaluated using the ab initio FMO method will be useful for designing potent ApoE4 inhibitors that can be used as a candidate agent for AD treatment. Full article

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. Full article

New N-containing xanthone analogs of α-mangostin were synthesized via one-pot Smiles rearrangement. Using cesium carbonate in the presence of 2-chloroacetamide and catalytic potassium iodide, α-mangostin (1) was subsequently transformed in three steps to provide ether 2, amide 3, and amine 4 in good yields at an optimum ratio of 1:3:3, respectively. The evaluation of the biological activities of α-mangostin and analogs 2–4 was described. Amine 4 showed promising cytotoxicity against the non-small-cell lung cancer H460 cell line fourfold more potent than that of cisplatin. Both compounds 3 and 4 possessed antitrypanosomal properties against Trypanosoma brucei rhodesiense at a potency threefold stronger than that of α-mangostin. Furthermore, ether 2 gave potent SARS-CoV-2 main protease inhibition by suppressing 3-chymotrypsinlike protease (3CL^pro) activity approximately threefold better than that of 1. Fragment molecular orbital method (FMO–RIMP2/PCM) indicated the improved binding interaction of 2 in the 3CL^pro active site regarding an additional ether moiety. Thus, the series of N-containing α-mangostin analogs prospectively enhance druglike properties based on isosteric replacement and would be further studied as potential biotically active chemical entries, particularly for anti-lung-cancer, antitrypanosomal, and anti-SARS-CoV-2 main protease applications. Full article

Ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) functions as the initial enzyme in the dark reactions of photosynthesis, catalyzing reactions that extract CO₂ from the atmosphere and fix CO₂ into organic compounds. RuBisCO is classified into four types (isoforms I–IV) according to sequence-based phylogenetic trees. Given its size, the computational cost of accurate quantum-chemical calculations for functional analysis of RuBisCO is high; however, recent advances in hardware performance and the use of the fragment molecular orbital (FMO) method have enabled the ab initio analyses of RuBisCO. Here, we performed FMO calculations on multiple structural datasets for various complexes with the 2′-carboxylarabinitol 1,5-bisphosphate (2CABP) ligand as a substrate analog and investigated whether phylogenetic relationships based on sequence information are physicochemically relevant as well as whether novel information unobtainable from sequence information can be revealed. We extracted features similar to the phylogenetic relationships found in sequence analysis, and in terms of singular value decomposition, we identified residues that strongly interacted with the ligand and the characteristics of the isoforms for each principal component. These results identified a strong correlation between phylogenetic relationships obtained by sequence analysis and residue interaction energies with the ligand. Notably, some important residues were located far from the ligand, making comparisons among species using only residues proximal to the ligand insufficient. Full article

Matrix metalloproteinases (MMPs) are calcium-dependent zinc-containing endopeptidases involved in multiple cellular processes. Among the MMP isoforms, MMP-9 regulates cancer invasion, rheumatoid arthritis, and osteoarthritis by degrading extracellular matrix proteins present in the tumor microenvironment and cartilage and promoting angiogenesis. Here, we identified two potent natural product inhibitors of the non-catalytic hemopexin domain of MMP-9 using a novel quantum mechanical fragment molecular orbital (FMO)-based virtual screening workflow. The workflow integrates qualitative pharmacophore modeling, quantitative binding affinity prediction, and a raw material search of natural product inhibitors with the BMDMS-NP library. In binding affinity prediction, we made a scoring function with the FMO method and applied the function to two protein targets (acetylcholinesterase and fibroblast growth factor 1 receptor) from DUD-E benchmark sets. In the two targets, the FMO method outperformed the Glide docking score and MM/PBSA methods. By applying this workflow to MMP-9, we proposed two potent natural product inhibitors (laetanine 9 and genkwanin 10) that interact with hotspot residues of the hemopexin domain of MMP-9. Laetanine 9 and genkwanin 10 bind to MMP-9 with a dissociation constant (K_D) of 21.6 and 0.614 μM, respectively. Overall, we present laetanine 9 and genkwanin 10 for MMP-9 and demonstrate that the novel FMO-based workflow with a quantum mechanical approach is promising to discover potent natural product inhibitors of MMP-9, satisfying the pharmacophore model and good binding affinity. Full article

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. Full article

The Hippo pathway is an important signaling pathway modulating growth control and cancer cell proliferation. Dysregulation of the Hippo pathway is a common feature of several types of cancer cells. The modulation of the interaction between yes-associated protein (YAP) and transcriptional enhancer associated domain (TEAD) in the Hippo pathway is considered an attractive target for cancer therapeutic development, although the inhibition of PPI is a challenging task. In order to investigate the hot spots of the YAP and TEAD1 interacting complex, an ab initio Fragment Molecular Orbital (FMO) method was introduced. With the hot spots, pharmacophores for the inhibitor design were constructed, then virtual screening was performed to an in-house library. Next, we performed molecular docking simulations and FMO calculations for screening results to study the binding modes and affinities between PPI inhibitors and TEAD1. As a result of the virtual screening, three compounds were selected as virtual hit compounds. In order to confirm their biological activities, cellular (luciferase activity, proximity ligation assay and wound healing assay in A375 cells, qRT-PCR in HEK 293T cells) and biophysical assays (surface plasmon resonance assays) were performed. Based on the findings of the study, we propose a novel PPI inhibitor BY03 and demonstrate a profitable strategy to analyze YAP–TEAD PPI and discover novel PPI inhibitors. Full article

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. Full article