Epigallocatechin-3-Gallate Promotes Osteo-/Odontogenic Differentiation of Stem Cells from the Apical Papilla through Activating the BMP–Smad Signaling Pathway

Stem cells from apical papilla (SCAPs) are desirable sources of dentin regeneration. Epigallocatechin-3-gallate (EGCG), a natural component of green tea, shows potential in promoting the osteogenic differentiation of bone mesenchymal stem cells. However, whether EGCG regulates the odontogenic differentiation of SCAPs and how this occurs remain unknown. SCAPs from immature human third molars (16–20 years, n = 5) were treated with a medium containing different concentrations of EGCG or bone morphogenic protein 2 (BMP2), with or without LDN193189 (an inhibitor of the canonical BMP pathway). Cell proliferation and migration were analyzed using a CCK-8 assay and wound-healing assay, respectively. Osteo-/odontogenic differentiation was evaluated via alkaline phosphatase staining, alizarin red S staining, and the expression of osteo-/odontogenic markers using qPCR and Western blotting. We found that EGCG (1 or 10 μM) promoted the proliferation of SCAPs, increased alkaline phosphatase activity and mineral deposition, and upregulated the expression of osteo-/odontogenic markers including dentin sialophosphoprotein (Dspp), dentin matrix protein-1 (Dmp-1), bone sialoprotein (Bsp), and Type I collagen (Col1), along with the elevated expression of BMP2 and phosphorylation level of Smad1/5/9 (p < 0.01). EGCG at concentrations below 10 μM had no significant influence on cell migration. Moreover, EGCG-induced osteo-/odontogenic differentiation was significantly attenuated via LDN193189 treatment (p < 0.01). Furthermore, EGCG showed the ability to promote mineralization comparable with that of recombinant BMP2. Our study demonstrated that EGCG promotes the osteo-/odontogenic differentiation of SCAPs through the BMP–Smad signaling pathway.     

Identification of Novel Influenza Polymerase PB2 Inhibitors Using a Cascade Docking Virtual Screening Approach

To discover novel inhibitors that target the influenza polymerase basic protein 2 (PB2) cap-binding domain (CBD), commercial ChemBridge compound libraries containing 384,796 compounds were screened using a cascade docking of LibDock–LigandFit–GOLD, and 60 compounds were selected for testing with cytopathic effect (CPE) inhibition assays and surface plasmon resonance (SPR) assay. Ten compounds were identified to rescue cells from H1N1 virus-mediated death at non-cytotoxic concentrations with EC₅₀ values ranging from 0.30 to 67.65 μM and could bind to the PB2 CBD of H1N1 with Kd values ranging from 0.21 to 6.77 μM. Among these, four compounds (11D4, 12C5, 21A5, and 21B1) showed inhibition of a broad spectrum of influenza virus strains, including oseltamivir-resistant ones, the PR/8-R292K mutant (H1N1, recombinant oseltamivir-resistant strain), the PR/8-I38T mutant (H1N1, recombinant baloxavir-resistant strain), and the influenza B/Lee/40 virus strain. These compounds have novel chemical scaffolds and relatively small molecular weights and are suitable for optimization as lead compounds. Based on sequence and structure comparisons of PB2 CBDs of various influenza virus subtypes, we propose that the Phe323/Gln325, Asn429/Ser431, and Arg355/Gly357 mutations, particularly the Arg355/Gly357 mutation, have a marked impact on the selectivities of PB2 CBD-targeted inhibitors of influenza A and influenza B.     

Identification of Novel Covalent XPO1 Inhibitors Based on a Hybrid Virtual Screening Strategy

Nuclear export protein 1 (XPO1), a member of the nuclear export protein-p (Karyopherin-P) superfamily, regulates the transport of “cargo” proteins. To facilitate this important process, which is essential for cellular homeostasis, XPO1 must first recognize and bind the cargo proteins. To inhibit this process, small molecule inhibitors have been designed that inhibit XPO1 activity through covalent binding. However, the scaffolds for these inhibitors are very limited. While virtual screening may be used to expand the diversity of the XPO1 inhibitor skeleton, enormous computational resources would be required to accomplish this using traditional screening methods. In the present study, we report the development of a hybrid virtual screening workflow and its application in XPO1 covalent inhibitor screening. After screening, several promising XPO1 covalent molecules were obtained. Of these, compound 8 performed well in both tumor cell proliferation assays and a nuclear export inhibition assay. In addition, molecular dynamics simulations were performed to provide information on the mode of interaction of compound 8 with XPO1. This research has identified a promising new scaffold for XPO1 inhibitors, and it demonstrates an effective and resource-saving workflow for identifying new covalent inhibitors.     

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q ² = 0.763, r ² = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.     

Rapid Identification of Potential Drug Candidates from Multi-Million Compounds’ Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds’ databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.     

Ensemble Docking Coupled to Linear Interaction Energy Calculations for Identification of Coronavirus Main Protease (3CLpro) Non-Covalent Small-Molecule Inhibitors

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential inhibitors of the SARS-CoV-2 main viral protease (3CL^pro or M^pro). For this purpose, we developed a novel approach using ensemble docking high-throughput virtual screening directly coupled with subsequent Linear Interaction Energy (LIE) calculations to maximize the conformational space sampling and to assess the binding affinity of identified inhibitors. A large database of small commercial compounds was prepared, and top-scoring hits were identified with two compounds singled out, namely 1-[(R)-2-(1,3-benzimidazol-2-yl)-1-pyrrolidinyl]-2-(4-methyl-1,4-diazepan-1-yl)-1-ethanone and [({(S)-1-[(1H-indol-2-yl)methyl]-3-pyrrolidinyl}methyl)amino](5-methyl-2H-pyrazol-3-yl)formaldehyde. Moreover, we obtained a favorable binding free energy of the identified compounds, and using contact analysis we confirmed their stable binding modes in the 3CL^pro active site. These compounds will facilitate further 3CL^pro inhibitor design.     

Evaluation of Virtual Screening Strategies for the Identification of γ-Secretase Inhibitors and Modulators

γ-Secretase is an intramembrane aspartyl protease that is important in regulating normal cell physiology via cleavage of over 100 transmembrane proteins, including Amyloid Precursor Protein (APP) and Notch family receptors. However, aberrant proteolysis of substrates has implications in the progression of disease pathologies, including Alzheimer’s disease (AD), cancers, and skin disorders. While several γ-secretase inhibitors have been identified, there has been toxicity observed in clinical trials associated with non-selective enzyme inhibition. To address this, γ-secretase modulators have been identified and pursued as more selective agents. Recent structural evidence has provided an insight into how γ-secretase inhibitors and modulators are recognized by γ-secretase, providing a platform for rational drug design targeting this protease. In this study, docking- and pharmacophore-based screening approaches were evaluated for their ability to identify, from libraries of known inhibitors and modulators with decoys with similar physicochemical properties, γ-secretase inhibitors and modulators. Using these libraries, we defined strategies for identifying both γ-secretase inhibitors and modulators incorporating an initial pharmacophore-based screen followed by a docking-based screen, with each strategy employing distinct γ-secretase structures. Furthermore, known γ-secretase inhibitors and modulators were able to be identified from an external set of bioactive molecules following application of the derived screening strategies. The approaches described herein will inform the discovery of novel small molecules targeting γ-secretase.     

Discovery of Novel PI3Kδ Inhibitors Based on the p110δ Crystal Structure

PI3Kδ is a key mediator of B-cell receptor signaling and plays an important role in the pathogenesis of certain hematological malignancies, such as chronic lymphocytic leukemia. Idelalisib, which targets PI3Kδ specifically, is the first approved PI3K inhibitor for cancer therapy. Recently, we carried out virtual screening, cell-based assays, adapta kinase assays, and molecular dynamic analysis to discover novel PI3Kδ inhibitors and identified NSC348884 as a lead PI3Kδ inhibitor. NSC348884 had an excellent docking score, potent PI3Kδ-inhibitory activity, antitumor effects on various cancer cell lines, and a favorable binding mode with the active site of PI3Kδ. Moreover, through the structural modification of NSC348884, we further discovered comp#1, which forms H-bonds with both Val828 and Lys779 in the ATP binding pocket of PI3Kδ, with a more favorable conformation binding to PI3Kδ. In addition, we found that N¹, N¹, N²-trimethyl-N²-((6-methyl-1H-benzo[d]imidazol-2-yl) methyl) ethane-1,2-diamine might be a potential scaffold structure. Thus, the result of this study provides a far more efficient approach for discovering novel inhibitors targeting PI3Kδ.     

Computational Approaches for the Design of Novel Anticancer Compounds Based on Pyrazolo[3,4-d]pyrimidine Derivatives as TRAP1 Inhibitor

In the present in-silico study, various computational techniques were applied to determine potent compounds against TRAP1 kinase. The pharmacophore hypothesis DHHRR_1 consists of important features required for activity. The 3D QSAR study showed a statistically significant model with R² = 0.96 and Q² = 0.57. Leave one out (LOO) cross-validation (R² CV = 0.58) was used to validate the QSAR model. The molecular docking study showed maximum XP docking scores (−11.265, −10.532, −10.422, −10.827, −10.753 kcal/mol) for potent pyrazole analogs (42, 46, 49, 56, 43), respectively, with significant interactions with amino acid residues (ASP 594, CYS 532, PHE 583, SER 536) against TRAP1 kinase receptors (PDB ID: 5Y3N). Furthermore, the docking results were validated using the 100 ns MD simulations performed for the selected five docked complexes. The selected inhibitors showed relatively higher binding affinities than the TRAP1 inhibitor molecules present in the literature. The ZINC database was used for a virtual screening study that screened ZINC05297837, ZINC05434822, and ZINC72286418, which showed similar binding interactions to those shown by potent ligands. Absorption, distribution, metabolism, and excretion (ADME) analysis showed noticeable results. The results of the study may be helpful for the further development of potent TRAP1 inhibitors     

Structural Refinement of 2,4-Thiazolidinedione Derivatives as New Anticancer Agents Able to Modulate the BAG3 Protein

The multidomain BAG3 protein is a member of the BAG (Bcl-2-associated athanogene) family of co-chaperones, involved in a wide range of protein–protein interactions crucial for many key cellular pathways, including autophagy, cytoskeletal dynamics, and apoptosis. Basal expression of BAG3 is elevated in several tumor cell lines, where it promotes cell survival signaling and apoptosis resistance through the interaction with many protein partners. In addition, its role as a key player of several hallmarks of cancer, such as metastasis, angiogenesis, autophagy activation, and apoptosis inhibition, has been established. Due to its involvement in malignant transformation, BAG3 has emerged as a potential and effective biological target to control multiple cancer-related signaling pathways. Recently, by using a multidisciplinary approach we reported the first synthetic BAG3 modulator interfering with its BAG domain (BD), based on a 2,4-thiazolidinedione scaffold and endowed with significant anti-proliferative activity. Here, a further in silico-driven selection of a 2,4-thiazolidinedione-based compound was performed. Thanks to a straightforward synthesis, relevant binding affinity for the BAG3BD domain, and attractive biological activities, this novel generation of compounds is of great interest for the development of further BAG3 binders, as well as for the elucidation of the biological roles of this protein in tumors. Specifically, we found compound 6 as a new BAG3 modulator with a relevant antiproliferative effect on two different cancer cell lines (IC₅₀: A375 = 19.36 μM; HeLa = 18.67 μM).     

C_2h_3自由基与O_2反应机理的量子化学研究

用量子化学从头计算中UMP2(full)方法优化了C_2H_3自由基与O_2反应通道上 驻点（反应物、中间体、过渡态和产物）的几何构型，在Gaussian-3(G3)水平上计 算了它们的能量。在此基础上计算了该反应通道上各基元反应的反应活化能。通过 我们的研究发现，C_2H_3自由基与氧气反应存在着三元环、四元环和五元环反应机 理，且分别生成不同的产物，从反应活化能的计算结果扯CH_2O和CHO是反应的主要 产物，其次还可能生成CH_3 + CO_2, CH_2CO_2 + H, C_2H_2 + O_2H和COHCOH + H等产物，且它们生成几率逐渐减少，我们对生成产物CH_2O + CHO, CH_3 + CO_2, C_2H_2 + O_2H和COHCOH + H四条反应通道化学反应热的计算结果与实验吻 合较好。     

A Hot‐Segment‐Based Approach for the Design of Cross‐Amyloid Interaction Surface Mimics as Inhibitors of Amyloid Self‐Assembly

The design of inhibitors of protein–protein interactions mediating amyloid self‐assembly is a major challenge mainly due to the dynamic nature of the involved structures and interfaces. Interactions of amyloidogenic polypeptides with other proteins are important modulators of self‐assembly. Here we present a hot‐segment‐linking approach to design a series of mimics of the IAPP cross‐amyloid interaction surface with Aβ (ISMs) as nanomolar inhibitors of amyloidogenesis and cytotoxicity of Aβ, IAPP, or both polypeptides. The nature of the linker determines ISM structure and inhibitory function including both potency and target selectivity. Importantly, ISMs effectively suppress both self‐ and cross‐seeded IAPP self‐assembly. Our results provide a novel class of highly potent peptide leads for targeting protein aggregation in Alzheimer’s disease, type 2 diabetes, or both diseases and a chemical approach to inhibit amyloid self‐assembly and pathogenic interactions of other proteins as well.     

Ligand and structure‐based models for the prediction of ligand‐receptor affinities and virtual screenings: Development and application to the β2‐adrenergic receptor

In this study, we evaluated the applicability of ligand‐based and structure‐based models to quantitative affinity predictions and virtual screenings for ligands of the β₂‐adrenergic receptor, a G protein‐coupled receptor (GPCR). We also devised and evaluated a number of consensus models obtained through partial least square regressions, to combine the strengths of the individual components. In all cases, the bioactive conformation of each ligand was derived from molecular docking at the crystal structure of the receptor. We identified the most effective models applicable to the different scenarios, in the presence or in the absence of a training set. For ranking the affinity of closely related analogs when a training set is available, a ligand‐based consensus model (LI‐CM) seems to be the best choice, while the structure‐based MM‐GBSA score seems the best alternative in the absence of a training set. For virtual screening purposes, the structure‐based MM‐GBSA score was found to be the method of choice. Consensus models consistently had performances superior or close to those of the best individual components, and were endowed with a significantly increased robustness. Given multiple models with no a priori knowledge of their predictive capabilities, constructing a consensus model ensures results very close to those that the best model alone would have yielded. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

Study of Aldo-keto Reductase 1C3 Inhibitor with Novel Framework for Treating Leukaemia Based on Virtual Screening and In vitro Biological Activity Testing

Aldo-keto reductase 1C3(AKR1C3) is a potential target for the treatment of acute myeloid leukaemia and T-cell acute lymphoblastic leukaemia. In this study, pharmacophore models, molecular docking and virtual screening of target prediction were used to find a potential AKR1C3 inhibitor. Firstly, eight bacteriocin derivatives(Z1-Z8) were selected as training sets to construct 20 pharmacophore models. The best pharmacophore model MODEL_016 was obtained by Decoy test(the enrichment degree was 21.5117, and the fitting optimisation degree was 0.9668). Secondly, MODEL_016 was used for the virtual screening of ZINC database. Thirdly, the hit 83256 molecules were docked into the AKR1C3 protein. Compared to the total scores and interactions between compounds and protein, 16532 candidate compounds with higher docking scores and interactions with important residues PHE306 and TRP227 were screened. Lastly, eight compounds(A1-A8) that had good absorption, distribution, metabolism, excretion and toxicity(ADMET) properties were obtained by target prediction. Compounds A3 and A7 with high total score and good target prediction results were selected for in vitro biological activity test, whose IC₅₀ values were 268.3 and 88.94 μmol/L, respectively. The results provide an important foundation for the discovery of novel AKR1C3 inhibitors. The research methods used in this study can also provide important references for the research and development of new drugs.     

Interaction of Soy Protein Isolate Hydrolysates with Cyanidin-3-O-Glucoside and Its Effect on the In Vitro Antioxidant Capacity of the Complexes under Neutral Condition

The interaction of soy protein isolate (SPI) and its hydrolysates (SPIHs) with cyanidin-3-O-glucoside (C3G) at pH 7.0 were investigated to clarify the changes in the antioxidant capacity of their complexes. The results of intrinsic fluorescence revealed that C3G binds to SPI/SPIHs mainly through hydrophobic interaction, and the binding affinity of SPI was stronger than that of SPIHs. Circular dichroism and Fourier-transform infrared spectroscopy analyses revealed that the interaction with C3G did not significantly change the secondary structures of SPI/SPIHs, while the surface hydrophobicity and average particle size of proteins decreased. Furthermore, the SPI/SPIHs-C3G interaction induced an antagonistic effect on the antioxidant capacity (ABTS and DPPH) of the complex system, with the masking effect on the ABTS scavenging capacity of the SPIHs-C3G complexes being lower than that of the SPI-C3G complexes. This study contributes to the design and development of functional beverages that are rich in hydrolysates and anthocyanins.     

Study on the Supramolecular Interaction of β-Cyclodextrin with Gemfibrozil by Spectrofluorimetry and Its Analytical Application

The supramolecular interaction of gemfibrozil with β-cyclodextrin （β-CD） was studied by spectrofluorimetry. The mechanism of the inclusion was discussed by spectrofluoremetry, infrared spectrum and ^1H NMR spectrum. The results showed that a 1 ： 1 （β-CD ： gemfibrozil） complex was formed with an apparent association constant of 3.844 × 10^3 L·mol^-1. Based on the enhancement of the fluorescent intensity of gemfibrozil, a spectrofluorimetric method for the determination of gemfibrozil in bulk aqueous solution in the presence of β-CD was developed. The linear range was 3.30 ng·mL^- 1 -6.00 ug·mL^-1 with the detection limit of 0.980 ng·mL^-1. There was no interference from the excipients normally used in tablet composition and the serum main compositions. The proposed method was then successfully applied to the determination of gemfibrozil in capsules and serum.     

CH3N3与C60(NCH3)2作用生成三氮杂富勒烯衍生物的反应机理

利用AM1半经验算法和密度泛函理论, 研究了CH3N3进攻C60(NCH3)2生成三氮杂富勒烯衍生物C60(NCH3)3的反应机理及区域选择性. 计算结果表明, CH3N3加成在C60(NCH3)2的两个不同位置的5/6单键上的反应均遵循分步机理. 反应途径上都存在3个过渡态和3个中间体. 从整个反应活化能、表观活化能以及速控步活化能来看, 生成稳定产物的反应并不占优势.