Biomedical subjects

Renxiao Wang

Publications and source records attributed to Renxiao Wang.

9 recordsLinked to original sources

PubMed2004

Breast cancer cells can evade apoptosis-mediated selective killing by a novel small molecule inhibitor of Bcl-2.

Proteins of the Bcl-2 family are key regulators of caspase activation and apoptosis. Some members of this family, notably Bcl-2 and Bcl-x(L), are overexpressed in cancer cells, which have been associated with chemoresistance. We have designed and synthesized a small molecule inhibitor of Bcl-2, named YC137, and studied its role in cancer cells. In vitro studies showed that YC137 inhibits the binding of the Bid BH3 peptide to Bcl-2, thus disrupting an interaction essential for the antiapoptotic activity of Bcl-2. This inhibitor induces apoptosis of hematopoietic progenitors overexpressing Bcl-2 but not Bcl-x(L) and breast cancer cells that express high levels of Bcl-2. On the contrary, a variety of normal primary cells, including CD34(+) progenitors, myoblasts, and peripheral blood mononuclear cells, do not respond to the inhibitor. A breast cancer cell line resistant to YC137 was generated. Analysis of resistant cells revealed a reduced expression of Bcl-2, which correlated with low activation of signal transducer and activator of transcription-3 (Stat3) and reduced expression of the human epidermal growth factor receptor-2 (HER2). Of note, YC137-resistant cells were more sensitive to apoptosis induced by chemotherapy. Because HER2 has not been linked previously to the Stat3-Bcl-2 transcriptional pathway, we additionally confirmed that specific blockade of HER2 in breast cancer cells resulted in down-regulation of Stat3 activity and reduced levels of Bcl-2. Consistently, HER2 blockade led to YC137 resistance. These data provide evidence for the selective killing of tumor cells by YC137 and represent the first example of in vitro selection of cancer cells refractory to a Bcl-2 inhibitor.

Apoptosis↗

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

Structure-based method for analyzing protein-protein interfaces.

Hydrogen bond, hydrophobic and vdW interactions are the three major non-covalent interactions at protein-protein interfaces. We have developed a method that uses only these properties to describe interactions between proteins, which can qualitatively estimate the individual contribution of each interfacial residue to the binding and gives the results in a graphic display way. This method has been applied to analyze alanine mutation data at protein-protein interfaces. A dataset containing 13 protein-protein complexes with 250 alanine mutations of interfacial residues has been tested. For the 75 hot-spot residues (deltadelta G > or = 1.5 kcal mol(-1)), 66 can be predicted correctly with a success rate of 88%. In order to test the tolerance of this method to conformational changes upon binding, we utilize a set of 26 complexes with one or both of their components available in the unbound form. The difference of key residues exported by the program is 11% between the results using complexed proteins and those from unbound ones. As this method gives the characteristics of the binding partner for a particular protein, in-depth studies on protein-protein recognition can be carried out. Furthermore, this method can be used to compare the difference between protein-protein interactions and look for correlated mutation.

Alanine↗

PubMed2003

Comparative evaluation of 11 scoring functions for molecular docking.

Eleven popular scoring functions have been tested on 100 protein-ligand complexes to evaluate their abilities to reproduce experimentally determined structures and binding affinities. They include four scoring functions implemented in the LigFit module in Cerius2 (LigScore, PLP, PMF, and LUDI), four scoring functions implemented in the CScore module in SYBYL (F-Score, G-Score, D-Score, and ChemScore), the scoring function implemented in the AutoDock program, and two stand-alone scoring functions (DrugScore and X-Score). These scoring functions are not tested in the context of a particular docking program. Instead, conformational sampling and scoring are separated into two consecutive steps. First, an exhaustive conformational sampling is performed by using the AutoDock program to generate an ensemble of docked conformations for each ligand molecule. This conformational ensemble is required to cover the entire conformational space as much as possible rather than to focus on a few energy minima. Then, each scoring function is applied to score this conformational ensemble to see if it can identify the experimentally observed conformation from all of the other decoys. Among all of the scoring functions under test, six of them, i.e., PLP, F-Score, LigScore, DrugScore, LUDI, and X-Score, yield success rates higher than the AutoDock scoring function. The success rates of these six scoring functions range from 66% to 76% if using root-mean-square deviation < or =2.0 A as the criterion. Combining any two or three of these six scoring functions into a consensus scoring scheme further improves the success rate to nearly 80% or even higher. However, when applied to reproduce the experimentally determined binding affinities of the 100 protein-ligand complexes, only X-Score, PLP, DrugScore, and G-Score are able to give correlation coefficients over 0.50. All of the 11 scoring functions are further inspected by their abilities to construct a descriptive, funnel-shaped energy surface for protein-ligand complexation. The results indicate that X-Score and DrugScore perform better than the other ones at this aspect.

Algorithms↗

PubMed2003

Theoretical elucidation of kinetic and thermodynamic control of radical addition regioselectivity.

The cyclizations of two structurally similar 2-oxo-5-hexenyl-type radicals have been investigated by ab initio and density functional (UB3LYP/6-31+G**//UHF/6-31G* and UB3LYP/6-31G*//UB3LYP/6-31G*) calculations. The origin of apparently contradictory reports of 6-endo and 5-exo cyclizations is determined. Kinetic control favors 6-endo cyclization, while thermodynamic control gives 5-exo cyclization, and the observation of different products from different research groups arises from the difference in experimental conditions used by the two groups. The outcome of a new cyclization reaction was predicted by using these theoretical techniques. Kinetic control is predicted to yield exclusively the products of 6-endo cyclization, while thermodynamic control would lead to an approximately equal mixture of one 6-endo and one 5-exo cyclized product. Experimental studies revealed that the reaction yields only the products of 6-endo cyclization through kinetic control.

Alkenes↗

PubMed2002

Further development and validation of empirical scoring functions for structure-based binding affinity prediction.

New empirical scoring functions have been developed to estimate the binding affinity of a given protein-ligand complex with known three-dimensional structure. These scoring functions include terms accounting for van der Waals interaction, hydrogen bonding, deformation penalty, and hydrophobic effect. A special feature is that three different algorithms have been implemented to calculate the hydrophobic effect term, which results in three parallel scoring functions. All three scoring functions are calibrated through multivariate regression analysis of a set of 200 protein-ligand complexes and they reproduce the binding free energies of the entire training set with standard deviations of 2.2 kcal/mol, 2.1 kcal/mol, and 2.0 kcal/mol, respectively. These three scoring functions are further combined into a consensus scoring function, X-CSCORE. When tested on an independent set of 30 protein-ligand complexes. X-CSCORE is able to predict their binding free energies with a standard deviation of 2.2 kcal/mol. The potential application of X-CSCORE to molecular docking is also investigated. Our results show that this consensus scoring function improves the docking accuracy considerably when compared to the conventional force field computation used for molecular docking.

Binding Sites↗

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↗