De novo molecular design with deep molecular generative models for PPI inhibitors.

We construct a protein-protein interaction (PPI) targeted drug-likeness dataset and propose a deep molecular generative framework to generate novel drug-likeness molecules from the features of the seed compounds. This framework gains inspiration from published molecular generative models, uses the key features associated with PPI inhibitors as input and develops deep molecular generative models for de novo molecular design of PPI inhibitors. For the first time, quantitative estimation index for compounds targeting PPI was applied to the evaluation of the molecular generation model for de novo design of PPI-targeted compounds. Our results estimated that the generated molecules had better PPI-targeted drug-likeness and drug-likeness. Additionally, our model also exhibits comparable performance to other several state-of-the-art molecule generation models. The generated molecules share chemical space with iPPI-DB inhibitors as demonstrated by chemical space analysis. The peptide characterization-oriented design of PPI inhibitors and the ligand-based design of PPI inhibitors are explored. Finally, we recommend that this framework will be an important step forward for the de novo design of PPI-targeted therapeutics.

Transformer-Based Molecular Generative Model for Antiviral Drug Design.

Since the Simplified Molecular Input Line Entry System (SMILES) is oriented to the atomic-level representation of molecules and is not friendly in terms of human readability and editable, however, IUPAC is the closest to natural language and is very friendly in terms of human-oriented readability and performing molecular editing, we can manipulate IUPAC to generate corresponding new molecules and produce programming-friendly molecular forms of SMILES. In addition, antiviral drug design, especially analogue-based drug design, is also more appropriate to edit and design directly from the functional group level of IUPAC than from the atomic level of SMILES, since designing analogues involves altering the R group only, which is closer to the knowledge-based molecular design of a chemist. Herein, we present a novel data-driven self-supervised pretraining generative model called "TransAntivirus" to make select-and-replace edits and convert organic molecules into the desired properties for design of antiviral candidate analogues. The results indicated that TransAntivirus is significantly superior to the control models in terms of novelty, validity, uniqueness, and diversity. TransAntivirus showed excellent performance in the design and optimization of nucleoside and non-nucleoside analogues by chemical space analysis and property prediction analysis. Furthermore, to validate the applicability of TransAntivirus in the design of antiviral drugs, we conducted two case studies on the design of nucleoside analogues and non-nucleoside analogues and screened four candidate lead compounds against anticoronavirus disease (COVID-19). Finally, we recommend this framework for accelerating antiviral drug discovery.

Leveraging the Fragment Molecular Orbital and MM-GBSA Methods in Virtual Screening for the Discovery of Novel Non-Covalent Inhibitors Targeting the TEAD Lipid Binding Pocket.

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.

PhyloSophos: a high-throughput scientific name mapping algorithm augmented with explicit consideration of taxonomic science, and its application on natural product (NP) occurrence database processing.

BACKGROUND: The standardization of biological data using unique identifiers is vital for seamless data integration, comprehensive interpretation, and reproducibility of research findings, contributing to advancements in bioinformatics and systems biology. Despite being widely accepted as a universal identifier, scientific names for biological species have inherent limitations, including lack of stability, uniqueness, and convertibility, hindering their effective use as identifiers in databases, particularly in natural product (NP) occurrence databases, posing a substantial obstacle to utilizing this valuable data for large-scale research applications. RESULT: To address these challenges and facilitate high-throughput analysis of biological data involving scientific names, we developed PhyloSophos, a Python package that considers the properties of scientific names and taxonomic systems to accurately map name inputs to entries within a chosen reference database. We illustrate the importance of assessing multiple taxonomic databases and considering taxonomic syntax-based pre-processing using NP occurrence databases as an example, with the ultimate goal of integrating heterogeneous information into a single, unified dataset. CONCLUSIONS: We anticipate PhyloSophos to significantly aid in the systematic processing of poorly digitized and curated biological data, such as biodiversity information and ethnopharmacological resources, enabling full-scale bioinformatics analysis using these valuable data resources.

Targeting FLT3-TAZ signaling to suppress drug resistance in blast phase chronic myeloid leukemia.

BACKGROUND: Although the development of BCR::ABL1 tyrosine kinase inhibitors (TKIs) rendered chronic myeloid leukemia (CML) a manageable condition, acquisition of drug resistance during blast phase (BP) progression remains a critical challenge. Here, we reposition FLT3, one of the most frequently mutated drivers of acute myeloid leukemia (AML), as a prognostic marker and therapeutic target of BP-CML. METHODS: We generated FLT3 expressing BCR::ABL1 TKI-resistant CML cells and enrolled phase-specific CML patient cohort to obtain unpaired and paired serial specimens and verify the role of FLT3 signaling in BP-CML patients. We performed multi-omics approaches in animal and patient studies to demonstrate the clinical feasibility of FLT3 as a viable target of BP-CML by establishing the (1) molecular mechanisms of FLT3-driven drug resistance, (2) diagnostic methods of FLT3 protein expression and localization, (3) association between FLT3 signaling and CML prognosis, and (4) therapeutic strategies to tackle FLT3+ CML patients. RESULTS: We reposition the significance of FLT3 in the acquisition of drug resistance in BP-CML, thereby, newly classify a FLT3+ BP-CML subgroup. Mechanistically, FLT3 expression in CML cells activated the FLT3-JAK-STAT3-TAZ-TEAD-CD36 signaling pathway, which conferred resistance to a wide range of BCR::ABL1 TKIs that was independent of recurrent BCR::ABL1 mutations. Notably, FLT3+ BP-CML patients had significantly less favorable prognosis than FLT3- patients. Remarkably, we demonstrate that repurposing FLT3 inhibitors combined with BCR::ABL1 targeted therapies or the single treatment with ponatinib alone can overcome drug resistance and promote BP-CML cell death in patient-derived FLT3+ BCR::ABL1 cells and mouse xenograft models. CONCLUSION: Here, we reposition FLT3 as a critical determinant of CML progression via FLT3-JAK-STAT3-TAZ-TEAD-CD36 signaling pathway that promotes TKI resistance and predicts worse prognosis in BP-CML patients. Our findings open novel therapeutic opportunities that exploit the undescribed link between distinct types of malignancies.

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.

Prediction of polyreactive and nonspecific single-chain fragment variables through structural biochemical features and protein language-based descriptors.

BACKGROUND: Monoclonal antibodies (mAbs) have been used as therapeutic agents, which must overcome many developability issues after the discovery from in vitro display libraries. Especially, polyreactive mAbs can strongly bind to a specific target and weakly bind to off-target proteins, which leads to poor antibody pharmacokinetics in clinical development. Although early assessment of polyreactive mAbs is important in the early discovery stage, experimental assessments are usually time-consuming and expensive. Therefore, computational approaches for predicting the polyreactivity of single-chain fragment variables (scFvs) in the early discovery stage would be promising for reducing experimental efforts. RESULTS: Here, we made prediction models for the polyreactivity of scFvs with the known polyreactive antibody features and natural language model descriptors. We predicted 19,426 protein structures of scFvs with trRosetta to calculate the polyreactive antibody features and investigated the classifying performance of each factor for polyreactivity. In the known polyreactive features, the net charge of the CDR2 loop, the tryptophan and glycine residues in CDR-H3, and the lengths of the CDR1 and CDR2 loops, importantly contributed to the performance of the models. Additionally, the hydrodynamic features, such as partial specific volume, gyration radius, and isoelectric points of CDR loops and scFvs, were newly added to improve model performance. Finally, we made the prediction model with a robust performance ([Formula: see text]) with an ensemble learning of the top 3 best models. CONCLUSION: The prediction models for polyreactivity would help assess polyreactive scFvs in the early discovery stage and our approaches would be promising to develop machine learning models with quantitative data from high throughput assays for antibody screening.

Identification of Novel Natural Product Inhibitors against Matrix Metalloproteinase 9 Using Quantum Mechanical Fragment Molecular Orbital-Based Virtual Screening Methods.

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 (KD) 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.

Isolindleyin exerts anti-melanogenic effects in human epidermal melanocytes via direct binding to tyrosinase.

To overcome dermatological concerns causing abnormally excessive melanin synthesis, highly effective and safe skin depigmentation compounds have been identified in the cosmetic and pharmaceutical industries. Among several methods used to achieve skin depigmentation, inhibition of tyrosinase is one of the most effective, since tyrosinase is a crucial enzyme in melanogenesis. Herein, isolindleyin, a novel inhibitor of human tyrosinase, was introduced and evaluated for its anti-melanogenic effects in human epidermal melanocytes. The results revealed that isolindleyin was directly bound to tyrosinase and it suppressed melanin synthesis. The binding mode between isolindleyin and the active sites of human tyrosinase was investigated using computational molecular docking at the atomic level. Isolindleyin binding was found to be stabilized by hydrophobic interactions between His 367 and Val 377 and by hydrogen bonds between Ser 380 and Asn 364. The results of this study revealed the anti-melanogenic effects of isolindleyin that could contribute toward overcoming dermatological concerns that cause abnormally excessive melanin synthesis.

Identification and characterization of saikosaponins as antagonists of transient receptor potential A1 channel.

Neuropathic pain is associated with an increased sensitivity to painful stimuli or abnormal sensitivity to otherwise innocuous stimuli. However, in addition to adverse effects, currently available drugs have shown limited response in patients with neuropathic pain, which provides a rationale to explore new drug classes acting on novel targets and with better efficacy and safety profiles. Here, we found that saikosaponins potently inhibit agonist-induced activation of the transient receptor potential A1 (TRPA1) channel, which has been reported to mediate neuropathic pain by sensing a variety of chemical irritants. Molecular docking and site-directed mutagenesis analyses suggested that saikosaponins bind to the hydrophobic pocket in TRPA1 near the Asn855 residue, which, when mutated to Ser, was previously associated with enhanced pain perception in humans. In support of these findings, saikosaponin D significantly attenuated agonist-induced nociceptive responses and vincristine-induced mechanical hypersensitivity in mice. These results indicate that saikosaponins are TRPA1 antagonists and provide a basis for further elaboration of saikosaponin derivatives for the development of new therapeutics for neuropathic pain.

Tyrosinase-Targeting Gallacetophenone Inhibits Melanogenesis in Melanocytes and Human Skin-Equivalents.

Demands for safe depigmentation compounds are constantly increasing in the pharmaceutical and cosmetic industry, since the numerous relevant compounds reported to date have shown undesirable side effects or low anti-melanogenic effects. In this study, we reported three novel inhibitors of tyrosinase, which is the key enzyme in melanogenesis, identified using docking-based high throughput virtual screening of an in-house natural compound library followed by mushroom tyrosinase inhibition assay. Of the three compounds, gallacetophenone showed high anti-melanogenic effect in both human epidermal melanocytes and a 3D human skin model, MelanoDerm. The inhibitory effect of gallacetophenone on tyrosinase was elucidated by computational molecular modeling at the atomic level. Binding of gallacetophenone to the active site of tyrosinase was found to be stabilized by hydrophobic interactions with His367, Ile368, and Val377; hydrogen bonding with Ser380 and a water molecule bridging the copper ions. Thus, our results strongly suggested gallacetophenone as an anti-melanogenic ingredient that inhibits tyrosinase.

Incorporation of Hydrogen Bond Angle Dependency into the Generalized Solvation Free Energy Density Model.

To describe the physically realistic solvation free energy surface of a molecule in a solvent, a generalized version of the solvation free energy density (G-SFED) calculation method has been developed. In the G-SFED model, the contribution from the hydrogen bond (HB) between a solute and a solvent to the solvation free energy was calculated as the product of the acidity of the donor and the basicity of the acceptor of an HB pair. The acidity and basicity parameters of a solute were derived using the summation of acidities and basicities of the respective acidic and basic functional groups of the solute, and that of the solvent was experimentally determined. Although the contribution of HBs to the solvation free energy could be evenly distributed to grid points on the surface of a molecule, the G-SFED model was still inadequate to describe the angle dependency of the HB of a solute with a polarizable continuum solvent. To overcome this shortcoming of the G-SFED model, the contribution of HBs was formulated using the geometric parameters of the grid points described in the HB coordinate system of the solute. We propose an HB angle dependency incorporated into the G-SFED model, i.e., the G-SFED-HB model, where the angular-dependent acidity and basicity densities are defined and parametrized with experimental data. The G-SFED-HB model was then applied to calculate the solvation free energies of organic molecules in water, various alcohols and ethers, and the log P values of diverse organic molecules, including peptides and a protein. Both the G-SFED model and the G-SFED-HB model reproduced the experimental solvation free energies with similar accuracy, whereas the distributions of the SFED on the molecular surface calculated by the G-SFED and G-SFED-HB models were quite different, especially for molecules having HB donors or acceptors. Since the angle dependency of HBs was included in the G-SFED-HB model, the SFED distribution of the G-SFED-HB model is well described as compared to that of the G-SFED model.

Discovery of a small-molecule inhibitor of Dvl-CXXC5 interaction by computational approaches.

The Wnt/ß-catenin signaling pathway plays a significant role in the control of osteoblastogenesis and bone formation. CXXC finger protein 5 (CXXC5) has been recently identified as a negative feedback regulator of osteoblast differentiation through a specific interaction with Dishevelled (Dvl) protein. It was reported that targeting the Dvl-CXXC5 interaction could be a novel anabolic therapeutic target for osteoporosis. In this study, complex structure of Dvl PDZ domain and CXXC5 peptide was simulated with molecular dynamics (MD). Based on the structural analysis of binding modes of MD-simulated Dvl PDZ domain with CXXC5 peptide and crystal Dvl PDZ domain with synthetic peptide-ligands, we generated two different pharmacophore models and applied pharmacophore-based virtual screening to discover potent inhibitors of the Dvl-CXXC5 interaction for the anabolic therapy of osteoporosis. Analysis of 16 compounds selected by means of a virtual screening protocol yielded four compounds that effectively disrupted the Dvl-CXXC5 interaction in the fluorescence polarization assay. Potential compounds were validated by fluorescence spectroscopy and nuclear magnetic resonance. We successfully identified a highly potent inhibitor, BMD4722, which directly binds to the Dvl PDZ domain and disrupts the Dvl-CXXC5 interaction. Overall, CXXC5-Dvl PDZ domain complex based pharmacophore combined with various traditional and simple computational methods is a promising approach for the development of modulators targeting the Dvl-CXXC5 interaction, and the potent inhibitor BMD4722 could serve as a starting point to discover or design more potent and specific the Dvl-CXXC5 interaction disruptors.

Discovery of non-peptidic small molecule inhibitors of cyclophilin D as neuroprotective agents in Aß-induced mitochondrial dysfunction.

Cyclophilin D (CypD) is a mitochondria-specific cyclophilin that is known to play a pivotal role in the formation of the mitochondrial permeability transition pore (mPTP).The formation and opening of the mPTP disrupt mitochondrial homeostasis, cause mitochondrial dysfunction and eventually lead to cell death. Several recent studies have found that CypD promotes the formation of the mPTP upon binding to ß amyloid (Aß) peptides inside brain mitochondria, suggesting that neuronal CypD has a potential to be a promising therapeutic target for Alzheimer's disease (AD). In this study, we generated an energy-based pharmacophore model by using the crystal structure of CypD-cyclosporine A (CsA) complex and performed virtual screening of ChemDiv database, which yielded forty-five potential hit compounds with novel scaffolds. We further tested those compounds using mitochondrial functional assays in neuronal cells and identified fifteen compounds with excellent protective effects against Aß-induced mitochondrial dysfunction. To validate whether these effects derived from binding to CypD, we performed surface plasmon resonance (SPR)-based direct binding assays with selected compounds and discovered compound 29 was found to have the equilibrium dissociation constants (KD) value of 88.2 nM. This binding affinity value and biological activity correspond well with our predicted binding mode. We believe that this study offers new insights into the rational design of small molecule CypD inhibitors, and provides a promising lead for future therapeutic development.

In silico probing and biological evaluation of SETDB1/ESET-targeted novel compounds that reduce tri-methylated histone H3K9 (H3K9me3) level.

ERG-associated protein with the SET domain (ESET/SET domain bifurcated 1/SETDB1/KMT1E) is a histone lysine methyltransferase (HKMT) and it preferentially tri-methylates lysine 9 of histone H3 (H3K9me3). SETDB1/ESET leads to heterochromatin condensation and epigenetic gene silencing. These functional changes are reported to correlate with Huntington's disease (HD) progression and mood-related disorders which make SETDB1/ESET a viable drug target. In this context, the present investigation was performed to identify novel peptide-competitive small molecule inhibitors of the SETDB1/ESET by a combined in silico-in vitro approach. A ligand-based pharmacophore model was built and employed for the virtual screening of ChemDiv and Asinex database. Also, a human SETDB1/ESET homology model was constructed to supplement the data further. Biological evaluation of the selected 21 candidates singled out 5 compounds exhibiting a notable reduction of the H3K9me3 level via inhibitory potential of SETDB1/ESET activity in SETDB1/ESET-inducible cell line and HD striatal cells. Later on, we identified two compounds as final hits that appear to have neuronal effects without cytotoxicity based on the result from MTT assay. These compounds hold the calibre to become the future lead compounds and can provide structural insights into more SETDB1/ESET-focused drug discovery research. Moreover, these SETDB1/ESET inhibitors may be applicable for the preclinical study to ameliorate neurodegenerative disorders via epigenetic regulation.

Inhibition of collagenase and melanogenesis by ethanol extracts of Orostachys japonicus A. Berger: possible involvement of Erk and Akt signaling pathways in melanoma cells.

Orostachys japonicus is an herb that contains several functional components and has traditionally been used to treat various diseases in Asia. In this study, bioactive components from different parts of the O. japonicus plant were investigated, and the contents of the functional components in ethanol extracts of O. japonicus cultivated in Korea and China were compared. The antioxidant effects of O. japonicus ethanol extracts were investigated using Raw 264.7 cells. It was found that 2,2-diphenyl-1-picrylhydrazyl radical-scavenging activity was significantly decreased in the cells treated with the extracts. Moreover, the novel inhibitory functions of O. japonicus extracts on collagenase, elastase, and tyrosinase were established. We also found that O. japonicus extracts strongly inhibited melanin synthesis in B16F10 melanoma cells by decreasing MITF protein levels and activating the Erk and Akt signaling pathways. Thus, these findings would be useful for developing new cosmetic and pharmaceutical formulations based on O. japonicus extracts.

Inhibition of cancer cell invasion by new ((3,4-dihydroxy benzylidene)hydrazinyl)pyridine-3-sulfonamide analogs.

Rab GTPases regulate various types of intracellular membrane trafficking in all eukaryotes. Since Rab27a and its multiple effectors are involved in exocytosis of lysosome-related organelles and play a major role in malignancy, compounds targeting Rab27a could be likely used to inhibit invasive growth and tumor metastasis. Thus, we designed and synthesized several compounds based on the previously reported Rab27a-targeting synthetic compounds identified by virtual screening, and investigated their anti-metastatic effects in MDA-MB231 and A375 cells. Among the synthesized compounds, (E)-N-(3-chlorophenyl)-6-(2-(3,4-dihydroxy benzylidene)hydrazinyl)pyridine-3-sulfonamide (3d) and (E)-N-benzyl-6-(2-(3,4-dihydroxy benzylidene)hydrazinyl)-N-methylpyridine-3-sulfonamide (3f) significantly inhibited the invasiveness of both tumor cell lines. Compounds 3d and 3f also decreased the levels of signature extracellular matrix marker proteins (fibronectin, collagen, and α-smooth muscle actin) and representative mesenchymal cell markers (N-cadherin and vimentin). Taken together, our results suggest that novel sulfonamide analogs have anti-metastatic activity in breast and melanoma cancer cell lines and may be used as therapeutic agents to treat malignant cancer.

Pharmacophore-based virtual screening, biological evaluation and binding mode analysis of a novel protease-activated receptor 2 antagonist.

Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor, mediating inflammation and pain signaling in neurons, thus it is considered to be a potential therapeutic target for inflammatory diseases. In this study, we performed a ligand-based virtual screening of 1.6 million compounds by employing a common-feature pharmacophore model and two-dimensional similarity search to identify a new PAR2 antagonist. The common-feature pharmacophore model was established based on the biological screening results of our in-house library. The initial virtual screening yielded a total number of 47 hits, and additional biological activity tests including PAR2 antagonism and anti-inflammatory effects resulted in a promising candidate, compound 43, which demonstrated an IC50 value of 8.22 µM against PAR2. In next step, a PAR2 homology model was constructed using the crystal structure of the PAR1 as a template to explore the binding mode of the identified ligands. A molecular docking method was optimized by comparing the binding modes of a known PAR2 agonist GB110 and antagonist GB83, and applied to predict the binding mode of our hit compound 43. In-depth docking analyses revealed that the hydrophobic interaction with Phe243(5.39) is crucial for PAR2 ligands to exert antagonistic activity. MD simulation results supported the predicted docking poses that PAR2 antagonist blocked a conformational rearrangement of Na(+) allosteric site in contrast to PAR2 agonist that showed Na(+) relocation upon GPCR activation. In conclusion, we identified new a PAR2 antagonist together with its binding mode, which provides useful insights for the design and development of PAR2 ligands.

Identification of small-molecule compounds targeting the dishevelled PDZ domain by virtual screening and binding studies.

The Dishevelled (Dvl) protein, which conveys signals from receptors to the downstream effectors, is a critical constituent of the Wnt/ß-catenin signaling pathway. Because the PDZ domain of Dvl protein functions through associations with a wide range of protein partners, Dvl protein involved in the Wnt signaling pathway has been considered to be therapeutic targets in cancers. In this study, we performed structure-based pharmacophore model of the Dvl PDZ domain to discover novel small-molecule binders and identified eight compounds with micromolar affinity. The most potent compound identified, BMD4702, efficiently bound to the Dvl PDZ domain with 11.2µM affinity and had a 0.186µM KD value according to surface plasmon resonance and fluorescence spectroscopy, respectively. Combining both structural-kinetic relationship analyses and docking studies, we fourmulated that the ligand-binding site is composed of three H-bonds and three hydrophobic features. Thus, our approach led to the identification of potent binders of the Dvl PDZ domain and the findings provide novel insights into structure-based approaches to design high-affinity binders for the Dvl PDZ domain.

Identification of a Small Benzamide Inhibitor of Influenza Virus Using a Cell-Based Screening.

BACKGROUND: The zoonotic transmission of highly pathogenic avian influenza viruses and the global pandemic of H1N1 influenza in 2009 signified the need for a wider coverage of therapeutic options for the control of influenza. METHODS: An in-house compound library was screened using a cytopathic effect inhibition assay. Selected hits were then tested in vivo and used as a core skeleton for derivative synthesis. RESULTS: The hit compound (BMD-2601505) was effective [50% effective concentration (EC50) of 60-70 µM] in reducing the death rate of cells infected with human influenza A and B viruses as well as avian influenza A virus. Furthermore, BMD-2601505 reduced the weight loss and increased the survival after lethal infection. The compound was further modified to enhance its antiviral potency. Results show that one derivative with bromobenzene moiety was most effective (EC50 of 22-37 µM) against the influenza viruses tested. CONCLUSION: We identified a small benzamide compound exhibiting antiviral activity against influenza viruses. The results warrant further evaluation of antiviral activities against drug-resistant influenza isolates.