Identification of Novel HCV RNA‐dependent RNA polymerase Inhibitors Using Pharmacophore‐Guided Virtual Screening

We performed pharmacophore‐guided virtual screening experiments using FlexX‐Pharm to identify novel inhibitors of hepatitis C virus RNA‐dependent RNA polymerase. Pharmacophore model generated from our previous analysis of the binding modes as well as structure‐based three‐dimensional quantitative structure–activity relationship studies of aryl diketoacid analogues was used. In pharmacophore‐guided virtual screening study, among 37 447 compounds in LeadQuest chemical library, 40 compounds were selected as novel candidates of hepatitis C virus RNA‐dependent RNA polymerase inhibitors, and their biological activities were evaluated. Especially, T29 was chosen for further development.     

Pharmacophore‐Based Drug Design and Biological Evaluation of Novel ABCB1 Inhibitors

Overexpression of ABCB1 is one of major barriers for multidrug resistance in chemotherapy and limits drug oral bioavailability. Inhibition of ABCB1 would sensitize multidrug resistance in clinical cancer chemotherapy. With this aim, a 3D pharmacophore model was created based on known ABCB1 inhibitors with correlation coefficient of 0.94, comprising three hydrophobic features and one hydrogen bond acceptor. It was further validated and used to search our in‐house 3D database for potential ABCB1 inhibitors. The inhibitory activities of the best hits were evaluated by several biological assays, such as rhodamine 123 accumulation assay, chemosensitization assay, multidrug resistance 1‐Madin‐Darby canine kidney cells/Madin‐Darby canine kidney cells permeability assay. Finally, compounds YZ‐3 and YZ‐16 were identified as potential leads to be developed in the designing of novel potent ABCB1 inhibitors.     

Tubulin Inhibitor Identification by Bioactive Conformation Alignment Pharmacophore‐Guided Virtual Screening

Microtubules are important cellular component that are critical for proper cellular function. Microtubules are synthesized by polymerization of αβ tubulin heterodimers called protofilaments. Microtubule dynamics facilitate proper cell division during mitosis. Disruption of microtubule dynamics by small‐molecule agents inhibits mitosis, resulting in apoptotic cell death and preventing cell cycle progression. To identify a novel small molecule that binds the αβ tubulin interface to affect microtubule dynamics, we developed a bioactive conformation alignment pharmacophore (BCAP) model to screen tubulin inhibitors from a huge database. The application of BCAP model generated based on the known αβ‐tubulin interface binders enabled us to identify several small‐molecules that cause apoptosis in human promyelocytic leukemia (HL‐60) cells. Virtual screening combined with an in vitro assay yielded 15 cytotoxic molecules. In particular, ethyl 2‐(4‐(5‐methyl‐3‐nitro‐1H‐pyrazol‐1‐yl)butanamido)‐4‐phenylthiophene‐3‐carboxylate ( H05 ) inhibited tubulin polymerization with an IC₅₀ of 17.6 μm concentration. The virtual screening results suggest that the application of an unbiased BCAP pharmacophore greatly eliminates unlikely compounds from a huge database and maximizes screening success. From the limited compounds tested in the tubulin polymerization inhibitor (TPI) assay, compound H05 was discovered as a tubulin inhibitor. This compound requires further structure activity optimization to identify additional potent inhibitors from the same class of molecules.     

Pharmacophore‐Based Virtual Screening to Aid in the Identification of Unknown Protein Function

A pharmacophore‐based virtual screening method was developed and validated for use in predicting the function of a novel protein in terms of small metabolite binding. Five test cases were used for the validation study which spanned two different folds, four superfamilies, and three enzyme classes. Binding sites were predicted using a combination of two methods (CASTp and THEMATICS). The binding site was mapped with chemical probes representing hydrogen‐bond donor, acceptor, negative ionizable, positive ionizable, and hydrophobe. The interaction maps were converted to three or four feature pharmacophore models and used to search a database containing 80 018 tautomers/protomers/conformers of 10 535 metabolites. The pharmacophore‐based virtual screening eliminated >92% of the database as potential substrates and retrieved specific hits, which were ranked using a physics‐based scoring function. The known substrate or product was ranked within the top 0.7% and substrate‐like compounds within the top 1% of the metabolite database for all of the five test cases. The results suggest that using this pharmacophore‐based virtual screening is a time‐efficient strategy that can be applied to screen large databases to help predict the function of small metabolite binding proteins.     

Discovery of HIV‐1 Integrase Inhibitors: Pharmacophore Mapping,Virtual Screening,Molecular Docking,Synthesis, and Biological Evaluation

HIV‐1 integrase enzyme plays an important role in the life cycle of HIV and responsible for integration of virus into human genome. Here, both computational and synthetic approaches were used to design and synthesize newer HIV‐1 integrase inhibitors. Pharmacophore mapping was performed on 20 chemically diverse molecules using DISCOtech, and refinement was carried out using GASP. Ten pharmacophore models were generated, and model 2, containing four features including two donor sites, one acceptor atom, and one hydrophobic region, was considered the best model as it has the highest fitness score. It was used as a query in NCI and Maybridge databases. Molecules having more than 99% Q_fit value were used to design 30 molecules bearing pteridine ring and were docked on co‐crystal structure of HIV‐1 integrase enzyme. Among these, six molecules, showing good docking score compared with the reference standards, were synthesized by conventional as well as microwave‐assisted methods. All compounds were characterized by physical and spectral data and evaluated for in vitro anti‐HIV activity against the replication of HIV‐1 (IIIB) in MT‐4 cells. The used approach of molecular docking and anti‐HIV activity data of designed molecules will provide significant insights to discover novel HIV‐1 Integrase Inhibitors.     

基于计算机虚拟筛选技术寻找NDM-1抑制剂

β-内酰胺类抗生素的广泛使用,使得越来越多的细菌产生由β-内酰胺酶介导的耐药性,针对丝氨酸β-内酰胺酶,目前已有克拉维酸、舒巴坦等抑制剂与临床常用抗生素配伍使用,但尚无金属β-内酰胺酶的有效抑制剂,因此,寻找金属β-内酰胺酶尤其是目前最受瞩目的新德里金属β-内酰胺酶-1[NDM-1(B1类)]的抑制剂是遏制"超级细菌"引起的感染最迫切的要求。虚拟筛选作为发现新的先导化合物、寻找新药物的有力手段,大大缩小了人工进行配体活性筛选研究范围。我们通过计算机虚拟筛选技术,利用Discovery Studio 2.5和GOLD 3.0平台,基于NDM-1晶体结构(PDB:3Q6X),从一个含有2059个天然产物分子的化合物库里筛选得到6个可能具有金属β-内酰胺酶NDM-1(B1类)抑制活性的化合物结构。     

组蛋白赖氨酸特异性脱甲基酶1（LSD1）在肿瘤治疗中的应用进展

组蛋白去甲基化酶LSD1的发现揭示了组蛋白赖氨酸的甲基化与其他化学修饰如乙酰化、泛素化等一样,是动态调节的过程。 LSD1控制基因转录的激活和抑制以及p15、p19、p21、p53等抑癌基因的活性,在癌症的发生和发展中起着重要的作用,是一个潜在的抗癌药物开发靶蛋白。     

Identification of Novel Urease Inhibitors by High-Throughput Virtual and in Vitro Screening

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A Specific Pharmacophore Model of Aurora B Kinase Inhibitors and Virtual Screening Studies Based on it

In this study, 3D‐pharmacophore models of Aurora B kinase inhibitors have been developed by using HipHop and HypoGen modules in Catalyst software package. The best pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9911), consists of one hydrogen‐bond acceptor, one hydrogen‐bond donor, one hydrophobic aliphatic moiety and one ring aromatic feature. Hypo1 was validated by test set and cross‐validation methods. And the specificity of Hypo1 to Aurora B inhibitors was examined with the use of selective inhibitors against Aurora B and its paralogue Aurora A. The results clearly indicate that Hypo1 can differentiate selective inhibitors of Aurora B from those of Aurora A, and the ring aromatic feature likely plays some important roles for the specificity of Hypo1. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge and Chinese Nature Product Database (CNPD) for identifying new inhibitors of Aurora B. The hit compounds were subsequently subjected to filtering by Lipinski’s rule of five and docking studies to refine the retrieved hits, and some compounds selected from the top ranked hits have been suggested for further experimental assay studies.     

Identification of novel polo-like kinase 1 inhibitors by a hybrid virtual screening

Polo-like kinase 1 is an important and attractive oncological target that plays a key role in mitosis and cytokinesis. A combined pharmacophore- and docking-based virtual screening was performed to identify novel polo-like kinase 1 inhibitors. A total of 34 hit compounds were selected and tested in vitro, and some compounds showed inhibition of polo-like kinase 1 and human tumor cell growth. The most potent compound (66) inhibited polo-like kinase 1 with an IC(50) value of 6.99 μm. The docked binding models of two hit compounds were discussed in detail. These compounds contained novel chemical scaffolds and may be used as foundations for the development of novel classes of polo-like kinase 1 inhibitors.     

Ligand-Based Virtual Screening,Molecular Docking,Molecular Dynamics,and MM-PBSA Calculations towards the Identification of Potential Novel Ricin Inhibitors

Ricin is a toxin found in the castor seeds and listed as a chemical weapon by the Chemical Weapons Convention (CWC) due to its high toxicity combined with the easiness of obtention and lack of available antidotes. The relatively frequent episodes of usage or attempting to use ricin in terrorist attacks reinforce the urge to develop an antidote for this toxin. In this sense, we selected in this work the current RTA (ricin catalytic subunit) inhibitor with the best experimental performance, as a reference molecule for virtual screening in the PubChem database. The selected molecules were then evaluated through docking studies, followed by drug-likeness investigation, molecular dynamics simulations and Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculations. In every step, the selection of molecules was mainly based on their ability to occupy both the active and secondary sites of RTA, which are located right next to each other, but are not simultaneously occupied by the current RTA inhibitors. Results show that the three PubChem compounds 18309602, 18498053, and 136023163 presented better overall results than the reference molecule itself, showing up as new hits for the RTA inhibition, and encouraging further experimental evaluation.     

Identification of Novel Anaplastic Lymphoma Kinase (ALK) Inhibitors Using a Common Feature Pharmacophore Model Derived from Known Ligands Crystallized with ALK

In this investigation, a common feature pharmacophore model of anaplastic lymphoma kinase inhibitors was developed based on several known anaplastic lymphoma kinase inhibitors that were co‐crystallized with anaplastic lymphoma kinase. The established pharmacophore model Hypo1 was carefully validated and then adopted to screen two in silico chemical databases, Specs (202 408 compounds) and Enamine (1 105 894 compounds), for retrieving novel anaplastic lymphoma kinase inhibitors. The hit compounds were further filtered using a fast bumping‐check tool and molecular docking. Finally, 25 compounds were selected and purchased from market. The bioactivity of these compounds was firstly measured at the cellular level against a typical anaplastic lymphoma kinase mutant‐driven cancer cell line, Karpas299. And six of them showed a good anti‐viability activity. The kinase inhibitory potency against the recombinant human anaplastic lymphoma kinase kinase was tested to the most active compound at the cellular level, T0508‐5181 (from Specs), which gave a half maximal inhibitory concentration (IC₅₀) of 5.3 μm .     

Novel Scaffold Identification of mGlu1 Receptor Negative Allosteric Modulators Using a Hierarchical Virtual Screening Approach

Metabotropic glutamate receptor 1 (mGluR1) is considered as an attractive drug target for neuropathic pain treatments. The hierarchical virtual screening approach for identifying novel scaffolds of mGluR1 allosteric modulators was performed using a homology model built with the dopamine D3 crystal structure as template. The mGluR1 mutagenesis data, conserved amino acid sequences across class A and class C GPCRs, and previously reported multiple sequence alignments of class C GPCRs to the rhodopsin template, were employed for the sequence alignment to overcome difficulties of model generation with low sequence identity of mGluR1 and dopamine D3. The structures refined by molecular dynamics simulations were employed for docking of Asinex commercial libraries after hierarchical virtual screening with pharmacophore and naïve Bayesian models. Five of 35 compounds experimentally evaluated using a calcium mobilization assay exhibited micromolar activities (IC50) with chemotype novelty that demonstrated the validity of our methods. A hierarchical structure and ligand‐based virtual screening approach with homology model of class C GPCR based on dopamine D3 class A GPCR structure was successfully performed and applied to discover novel negative mGluR1 allosteric modulators.     

Discovery of Novel Allosteric Eg5 Inhibitors Through Structure‐Based Virtual Screening

Mitotic kinesin Eg5 is an attractive anticancer drug target. Discovery of Eg5 inhibitors has been focused on targeting the ‘monastrol‐binding site’. However, acquired drug resistance has been reported for such inhibitors. Therefore, identifying new Eg5 inhibitors which function through a different mechanism(s) could complement current drug candidates and improve drug efficacy. In this study, we explored a novel allosteric site of Eg5 and identified new Eg5 inhibitors through structure‐based virtual screening. Experiments with the saturation‐transfer difference NMR demonstrated that the identified Eg5 inhibitor SRI35566 binds directly to Eg5 without involving microtubules. Moreover, SRI35566 and its two analogs significantly induced monopolar spindle formation in colorectal cancer HCT116 cells and suppressed cancer cell viability and colony formation. Together, our findings reveal a new allosteric regulation mechanism of Eg5 and a novel drug targeting site for cancer therapy.     

Identification of Novel Gyrase B Inhibitors as Potential Anti‐TB drugs: Homology Modelling,Hybrid Virtual Screening and Molecular Dynamics Simulations

Using an integrated computational approach involving homology modelling, pharmacophore/structure‐based virtual screening, molecular dynamics simulations and per‐residue energy contribution, 10 compounds were proposed as potential TB inhibitors. Via validated docking calculations, binding free energy calculations showed that the proposed compounds presented better binding affinity with DNA gyrase B when compared to novobiocin. The compiled in silico approach employed in this study may serve as a useful tool in the process of the design and development of drugs, not only against TB, but also for a wide range of biological systems.     

Identification of Dipeptidyl Peptidase IV Inhibitors: Virtual Screening,Synthesis and Biological Evaluation

Inhibition of dipeptidyl peptidase IV is an important approach for the treatment of type‐2 diabetes. In this study, we reported a multistage virtual screening workflow that integrated 3D pharmacophore models, structural consensus docking, and molecular mechanics/generalized Born surface area binding energy calculation to identify novel dipeptidyl peptidase IV inhibitors. After screening our in‐house database, two hit compounds, HWL‐405 and HWL‐892, having persistent high performance in all stages of virtual screening were identified. These two hit compounds together with several analogs were synthesized and evaluated for in vitro inhibition of dipeptidyl peptidase IV. The experimental data indicated that most designed compounds exhibited significant dipeptidyl peptidase IV inhibitory activity. Among them, compounds 35f displayed the greatest potency against dipeptidyl peptidase IV in vitro with the IC₅₀ value of 78 nm . In an oral glucose tolerance test in normal male Kunming mice, compound 35f reduced blood glucose excursion in a dose‐dependent manner.     

The Discovery of a Novel and Selective Inhibitor of PTP1B Over TCPTP: 3D QSAR Pharmacophore Modeling,Virtual Screening,Synthesis, and Biological Evaluation

Given the special role of insulin and leptin signaling in various biological responses, protein‐tyrosine phosphatase‐1B (PTP1B) was regarded as a novel therapeutic target for treating type 2 diabetes and obesity. However, owing to the highly conserved (sequence identity of about 74%) in active pocket, targeting PTP1B for drug discovery is a great challenge. In this study, we employed the software package Discovery Studio to develop 3D QSAR pharmacophore models for PTP1B and TCPTP inhibitors. It was further validated by three methods (cost analysis, test set prediction, and Fisher's test) to show that the models can be used to predict the biological activities of compounds without costly and time‐consuming synthesis. The criteria for virtual screening were also validated by testing the selective PTP1B inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed a novel and selective inhibitor of PTP1B over TCPTP. After that, a most likely binding mode was proposed. Thus, the findings reported here may provide a new strategy in discovering selective PTP1B inhibitors.