Biomedical subjects

Xueliang Fang

Publications and source records attributed to Xueliang Fang.

12 recordsLinked to original sources

PubMed2006

Blockade of AKT activation in prostate cancer cells with a small molecule inhibitor, 9-chloro-2-methylellipticinium acetate (CMEP).

AKT inhibitors are potentially promising drug candidates for the treatment of cancer. The inhibitory effects of a potent and selective AKT/BKB small molecule inhibitor, 9-chloro-2-methylellipticinium acetate (CMEP), on the activation of AKT, its antiproliferation and apoptosis-inducing effects in prostate cancer cell lines: DU-145, PC-3, LNCaP, and CL-1, an androgen-independent LNCaP variant, and CL-1 xenograft mouse model were assessed by Western blot analysis, kinase assay, cell survival assay, and apoptosis assay in this report. It has been observed that the expression levels of AKT1, AKT2, and AKT3 vary, but the levels of phospho-Ser473 AKT and phospho-Thr308 AKT are quite unique in these cancer cell lines, and that CL-1 cells have the highest basal levels of AKT activation among these cell lines. In PC-3 cells, CMEP has been found to inhibit only AKT activation at both normal and serum-starvation conditions, not to inhibit PI3K, PDK1, or MAPK. More importantly, it has been discovered that CMEP inhibits cell proliferation, and induces apoptosis in prostate cancer cells which have high-levels of AKT activation and lack PTEN or harbor PTEN mutation, such as CL-1, LNCaP, and PC-3; only shows a minimal activity in DU-145 cancer cells which do not have AKT activation. Furthermore, it has been demonstrated that CMEP treatment inhibits phospho-Ser473 AKT and phospho-p70S6K while stimulating TSC2 in the tumor tissue from CL-1-bearing mice. In conclusion, by specific blockade of the activation of AKT, CMEP preferentially inhibits growth and induces apoptosis in prostate cancer cells which have high-levels of AKT activation.

Animals↗

PubMed2006

Discovery of a nanomolar inhibitor of the human murine double minute 2 (MDM2)-p53 interaction through an integrated, virtual database screening strategy.

An integrated, virtual database screening strategy has led to 7-[anilino(phenyl)methyl]-2-methyl-8-quinolinol (4, NSC 66811) as a novel inhibitor of the murine double minute 2 (MDM2)-p53 interaction. This quinolinol binds to MDM2 with a Ki of 120 nM and activates p53 in cancer cells with a mechanism of action consistent with targeting the MDM2-p53 interaction. It mimics three p53 residues critical in the binding to MDM2 and represents a promising new class of non-peptide inhibitors of the MDM2-p53 interaction.

Aniline Compounds↗

PubMed2005

The PDBbind database: methodologies and updates.

We have developed the PDBbind database to provide a comprehensive collection of binding affinities for the protein-ligand complexes in the Protein Data Bank (PDB). This paper gives a full description of the latest version, i.e., version 2003, which is an update to our recently reported work. Out of 23 790 entries in the PDB release No.107 (January 2004), 5897 entries were identified as protein-ligand complexes that meet our definition. Experimentally determined binding affinities (K(d), K(i), and IC(50)) for 1622 of these were retrieved from the references associated with these complexes. A total of 900 complexes were selected to form a "refined set", which is of particular value as a standard data set for docking and scoring studies. All of the final data, including binding affinity data, reference citations, and processed structural files, have been incorporated into the PDBbind database accessible on-line at http:// www.pdbbind.org/.

Databases, Protein↗

PubMed2005

CHMIS-C: a comprehensive herbal medicine information system for cancer.

A comprehensive herbal medicine information system for cancer (CHMIS-C) has been developed. The current version of the database integrates information on more than 200 anticancer herbal recipes that have been used for the treatment of different types of cancer in clinic, 900 individual ingredients, and 8500 small organic molecules isolated from herbal medicines. Furthermore, subsidiary databases of literature references and molecular targets have been constructed. A number of web-based searching tools have been developed and integrated into the information system for efficient data mining. The compounds in the database have been linked to the corresponding entries in the National Cancer Institute's database, and to a database of drugs approved by the U.S. Food and Drug Administration. This paper provides a description of the individual subsidiary databases, integration of the entire database, and data mining tools. We demonstrate that this comprehensive information system may be used as an effective informatics tool for anticancer drug discovery.

Antineoplastic Agents, Phytogenic↗

PubMed2005

Identification of novel neuroprotective agents using pharmacophore modeling.

In addition to its endocrine function, for which it was named, thyrotropin-releasing hormone (TRH) has substantial neuroprotective actions as well as other physiological effects. We have developed a number of modified TRH analogues as well as cyclic dipeptides structurally related to a major metabolic product of TRH, which have enhanced neuroprotective activity but none of the other major physiological effects of TRH. The extensive structure-activity data developed with these compounds were used to develop a pharmacophore model. Subsequently, a web-based pharmacophore searching program was used to query several large three-dimensional databases. Of the 219 compounds identified whose structures met the pharmacophore model, 15 were chosen for study in a classical model of neuronal cell death in vitro; five of these, 2-6, showed neuroprotective activity. Thus, pharmacophore modeling developed from neuroprotective small peptides can be used to identify novel lead compounds as neuroprotective agents.

Animals↗

PubMed2004

Development and optimization of a binding assay for the XIAP BIR3 domain using fluorescence polarization.

The X-linked inhibitor of apoptosis protein (XIAP) is a potent cellular inhibitor of apoptosis. Designing small-molecule inhibitors that target the BIR3 domain of XIAP, where Smac/DIABLO (second mitochondria-derived activator of caspase/direct IAP-binding protein with low pI) and caspase-9 bind, is a promising strategy for inhibiting the antiapoptotic activity of XIAP and for overcoming apoptosis resistance of cancer cells mediated by XIAP. Herein, we report the development of a homogeneous high-throughput assay based on fluorescence polarization for measuring the binding affinities of small-molecule inhibitors to the BIR3 domain of XIAP. Among four fluorescent probes tested, a mutated N-terminal Smac peptide (AbuRPFK-(5-Fam)-NH(2)) showed the highest affinity (Kd =17.92 nM) and a large dynamic range (deltamP = 231 +/- 0.9), and was selected as the most suitable probe for the binding assay. The binding conditions (DMSO tolerance and stability) have been investigated. Under optimized conditions, a Z' factor of 0.88 was achieved in a 96-well format for high-throughput screening. It was found that the popular Cheng-Prusoff equation is invalid for the calculation of the competitive inhibition constants (Ki values) for inhibitors in the FP-based competitive binding assay conditions, and accordingly, a new mathematical equation was developed, validated, and used to compute the Ki values. An associated Web-based computer program was also developed for this task. Several known Smac peptides with high and low affinities have been evaluated under the assay conditions and the results obtained indicated that the FP-based competitive binding assay performs correctly as designed: it can quantitatively and accurately determine the binding affinities of Smac-based peptide inhibitors with a wide range of affinities, and is suitable for high-throughput screening of inhibitors binding to the XIAP BIR3 domain.

Binding, Competitive↗

PubMed2004

The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures.

We have screened the entire Protein Data Bank (Release No. 103, January 2003) and identified 5671 protein-ligand complexes out of 19 621 experimental structures. A systematic examination of the primary references of these entries has led to a collection of binding affinity data (K(d), K(i), and IC(50)) for a total of 1359 complexes. The outcomes of this project have been organized into a Web-accessible database named the PDBbind database.

Databases, Protein↗

PubMed2004

Discovery of embelin as a cell-permeable, small-molecular weight inhibitor of XIAP through structure-based computational screening of a traditional herbal medicine three-dimensional structure database.

The X-linked inhibitor of apoptosis (XIAP) is a promising new molecular target for the design of novel anticancer drugs aiming at overcoming apoptosis-resistance of cancer cells to chemotherapeutic agents and radiation therapy. Recent studies demonstrated that the BIR3 domain of XIAP where caspase-9 and Smac proteins bind is an attractive site for designing small-molecule inhibitors of XIAP. Through computational structure-based screening of an in-house traditional herbal medicine three-dimensional structure database of 8221 individual natural products, followed by biochemical testing of selected candidate compounds, we discovered embelin from the Japanese Ardisia herb as a small-molecular weight inhibitor that binds to the XIAP BIR3 domain. We showed that embelin binds to the XIAP BIR3 protein with an affinity similar to that of the natural Smac peptide using a fluorescence polarization-based binding assay. Our NMR analysis further conclusively confirmed that embelin interacts with several crucial residues in the XIAP BIR3 domain with which Smac and caspsase-9 bind. Embelin inhibits cell growth, induces apoptosis, and activates caspase-9 in prostate cancer cells with high levels of XIAP, but has a minimal effect on normal prostate epithelial and fibroblast cells with low levels of XIAP. In stably XIAP-transfected Jurkat cells, embelin effectively overcomes the protective effect of XIAP to apoptosis and enhances the etoposide-induced apoptosis and has a minimal effect in Jurkat cells transfected with vector control. Taken together, our results showed that embelin is a fairly potent, nonpeptidic, cell-permeable, small-molecule inhibitor of XIAP and represents a promising lead compound for designing an entirely new class of anticancer agents that target the BIR3 domain of XIAP.

Antineoplastic Agents↗

PubMed2003

Molecular modeling of the three-dimensional structure of dopamine 3 (D3) subtype receptor: discovery of novel and potent D3 ligands through a hybrid pharmacophore- and structure-based database searching approach.

The dopamine 3 (D3) subtype receptor has been implicated in several neurological conditions, and potent and selective D3 ligands may have therapeutic potential for the treatment of drug addiction, Parkinson's disease, and schizophrenia. In this paper, we report computational homology modeling of the D3 receptor based upon the high-resolution X-ray structure of rhodopsin, extensive structural refinement in the presence of explicit lipid bilayer and water environment, and validation of the refined D3 structural models using experimental data. We further describe the development, validation, and application of a hybrid computational screening approach for the discovery of several classes of novel and potent D3 ligands. This computational approach employs stepwise pharmacophore and structure-based searching of a large three-dimensional chemical database for the identification of potential D3 ligands. The obtained hits are then subjected to structural novelty screening, and the most promising compounds are tested in a D3 binding assay. Using this approach we identified four compounds with K(i) values better than 100 nM and eight compounds with K(i) values better than 1 microM out of 20 compounds selected for testing in the D3 receptor binding assay. Our results suggest that the D3 structural models obtained from this study may be useful for the discovery and design of novel and potent D3 ligands. Furthermore, the employed hybrid approach may be more effective for lead discovery from a large chemical database than either pharmacophore-based or structure-based database screening alone.

Algorithms↗

PubMedDate not supplied

A web-based 3D-database pharmacophore searching tool for drug discovery.

Three-Dimensional (3D) structural database pharmacophore searching has become a very effective approach for discovery of novel lead compounds in drug discovery. Although several commercial programs are available, these commercial programs are primarily used as a stand alone and require a local database. In recent years, the Internet has become the main medium of choice for multiuser application program distribution. Herein, we describe our development of a Web-based 3D-database pharmacophore-searching tool based on the server-client Web architecture. Both rigid and conformationally flexible searching methods are implemented. Our results show that for a typical three-center rigid pharmacophore search, the run time for searching 50 000 compounds is less than three minutes, and for four-center pharmacophore searching, the run time is less than 10 minutes on a desktop computer. For a flexible 3D-pharmacophore search, the run time for searching 50 000 compounds generally takes between one and several hours. The search results are comparable to those obtained using a commercial program. We expect that this Web-based tool will be very useful for scientists who are interested in 3D-database pharmacophore searching via the Internet.

Database Management Systems↗

PubMedDate not supplied

Web-based tools for mining the NCI databases for anticancer drug discovery.

In this paper, we describe the development of a set of integrated Web-based tools for mining the National Cancer Institute's (NCI) anticancer databases for anticancer drug discovery. For data mining, three different correlation algorithms were implemented, which included the commonly used Pearson's correlation algorithm available from the NCI's COMPARE program, the Spearman's and Kendall's correlation algorithms. In addition, we implemented the p-value test to evaluate the significance of the correlation results. These Web-based data mining tools allow robust analysis of the correlation between the in vitro anticancer activity of the drugs in the NCI anticancer database, the protein levels and mRNA levels of molecular targets (genes) in the NCI 60 human cancer cell lines for identification of potential lead compounds for a specific molecular target and for study of the molecular mechanism action of a drug. Examples were provided to identify PKC ligands using a lead compound and to identify potential ErbB-2 inhibitors using the mRNA levels of ErbB-2 in the NCI 60 tumor cell lines.

Antineoplastic Agents↗

PubMedDate not supplied

An extensive test of 14 scoring functions using the PDBbind refined set of 800 protein-ligand complexes.

Fourteen popular scoring functions, i.e., X-Score, DrugScore, five scoring functions in the Sybyl software (D-Score, PMF-Score, G-Score, ChemScore, and F-Score), four scoring functions in the Cerius2 software (LigScore, PLP, PMF, and LUDI), two scoring functions in the GOLD program (GoldScore and ChemScore), and HINT, were tested on the refined set of the PDBbind database, a set of 800 diverse protein-ligand complexes with high-resolution crystal structures and experimentally determined Ki or Kd values. The focus of our study was to assess the ability of these scoring functions to predict binding affinities based on the experimentally determined high-resolution crystal structures of proteins in complex with their ligands. The quantitative correlation between the binding scores produced by each scoring function and the known binding constants of the 800 complexes was computed. X-Score, DrugScore, Sybyl::ChemScore, and Cerius2::PLP provided better correlations than the other scoring functions with standard deviations of 1.8-2.0 log units. These four scoring functions were also found to be robust enough to carry out computation directly on unaltered crystal structures. To examine how well scoring functions predict the binding affinities for ligands bound to the same target protein, the performance of these 14 scoring functions were evaluated on three subsets of protein-ligand complexes from the test set: HIV-1 protease complexes (82 entries), trypsin complexes (45 entries), and carbonic anhydrase II complexes (40 entries). Although the results for the HIV-1 protease subset are less than desirable, several scoring functions are able to satisfactorily predict the binding affinities for the trypsin and the carbonic anhydrase II subsets with standard deviation as low as 1.0 log unit (corresponding to 1.3-1.4 kcal/mol at room temperature). Our results demonstrate the strengths as well as the weaknesses of current scoring functions for binding affinity prediction.

Algorithms↗