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Biomedical subjects

Chao-Yie Yang

Publications and source records attributed to Chao-Yie Yang.

11 recordsLinked to original sources

Design, synthesis, and evaluation of a potent, cell-permeable, conformationally constrained second mitochondria derived activator of caspase (Smac) mimetic.

A potent, cell-permeable, conformationally constrained second mitochondria derived activator of caspase mimetic (SM-131, 2) has been designed, synthesized, and evaluated. Compound 2 binds to X-linked inhibitors of apoptosis proteins (XIAP) with a Ki of 61 nM in a competitive binding assay and directly antagonizes the XIAP inhibition of caspase-9 activity in a cell-free functional assay. Compound 2 achieves an IC50 of 100 nM in inhibition of cell growth and effectively induces cell death in the MDA-MB-231 human breast cancer cell line.

Azepines↗

Structure-based design of potent small-molecule inhibitors of anti-apoptotic Bcl-2 proteins.

A structure-based approach was employed to design a new class of small-molecule inhibitors of Bcl-2. The most potent compound 5 (TW-37) binds to Bcl-2 with a K(i) value of 290 nM and also to Bcl-xL and Mcl-1 with high affinities. Compound 5 potently inhibits cell growth in PC-3 prostate cancer cells with an IC(50) value of 200 nM and effectively induces apoptosis in a dose-dependent manner.

Apoptosis↗

M-score: a knowledge-based potential scoring function accounting for protein atom mobility.

A knowledge-based potential scoring function, named M-Score, has been developed based upon 2331 high-resolution crystal structures of protein-ligand complexes. M-Score considers the mobility of protein atoms, describing the location of each protein atom by a Gaussian distribution instead of a fixed position based upon the isotropic B-factors. This leads to an increase in the number of atom-pairs in the construction of knowledge-based potentials and a smoothing effect on the pairwise distribution functions. M-Score was validated using 896 complexes which were not included in the 2331 data set and whose experimentally determined binding affinities were available. The overall linear correlation coefficient (r) between the calculated scores and experimentally determined binding affinities (pKi or pKd) for these 896 complexes is -0.49. Evaluation of M-Score against 17 protein families showed that we obtained good to excellent correlations for six protein families, modest correlations for four protein families, and poor correlations for the remaining seven protein families.

Algorithms↗

Binding free energy contributions of interfacial waters in HIV-1 protease/inhibitor complexes.

Water molecules are commonly observed in crystal structures of protein-ligand complexes where they mediate protein-ligand binding. It is of considerable theoretical and practical importance to determine quantitatively the individual free energy contributions of these interfacial water molecules to protein-ligand binding and to elucidate factors that influence them. The double-decoupling free energy molecular dynamics simulation method has been used to calculate the binding free energy contribution for each of the four interfacial water molecules observed in the crystal structure of HIV-1 protease complexed with KNI-272, a potent inhibitor. While two of these water molecules contribute significantly to the binding free energy, the other two have close to zero contribution. It was further observed that the protonation states of two catalytic aspartate residues, Asp25 and Asp125, strongly influence the free energy contribution of a conserved water molecule Wat301 and that different inhibitors significantly influence the free energy contribution of Wat301. Our results have important implications on our understanding of the role of interfacial water molecules in protein-ligand binding and to structure-based drug design aimed at incorporating these interfacial water molecules into ligands.

Binding Sites↗

A systematic analysis of the effect of small-molecule binding on protein flexibility of the ligand-binding sites.

Using atomic B-factors from high-resolution crystal structures of proteins and protein-ligand complexes, we have studied the effect of small-molecule ligand binding on protein flexibility. For the majority of proteins studied, ligand binding to a protein results in an increase in atomic mobility for some protein atoms at the ligand-binding site, and it leads to an increase in protein flexibility of the entire ligand-binding site in several cases.

Binding Sites↗

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↗

Enantiomerically pure hexahydropyrazinoquinolines as potent and selective dopamine 3 subtype receptor ligands.

We report the design and synthesis of a series of enantiomerically pure hexahydropyrazinoquinolines as potent and selective ligands for the dopamine 3 subtype receptor using a newly developed synthetic method and using in vitro pharmacological evaluation. Our efforts yielded optically pure ligands with high affinities for the D(3) receptor and outstanding selectivity over closely related D(1)-like and D(2)-like receptors. For example, compound 38a has a K(i) value of 5.7 nM to the D(3) receptor and selectivity greater than 10000- and 1600-fold over the D(1)-like and D(2)-like receptors, respectively, and thus is one of the most selective D(3) ligands reported to date.

Animals↗

Structure-based design, synthesis and biochemical testing of novel and potent Smac peptido-mimetics.

Structure-based design, chemical synthesis and biochemical testing of a series of novel Smac peptido-mimetics as inhibitors of XIAP protein are described. The most potent compound, 6j, has a binding affinity (K(i) value) of 24 nM to XIAP BIR3 protein and is 24 times more potent than the native Smac AVPI peptide. Further optimization of these potent Smac mimetics may ultimately lead to the development of a novel class of anticancer drugs for the treatment of human cancer by overcoming apoptosis-resistance of cancer cells through targeting the inhibitor of apoptosis proteins.

Apoptosis Regulatory Proteins↗

Structure-based design of potent, conformationally constrained Smac mimetics.

A successful structure-based design and synthesis of a class of highly potent conformationally constrained Smac mimetics is described. The most potent compound has a Ki value of 25 nM binding to the XIAP BIR3 protein and is 23 times more potent than natural Smac peptides. These potent Smac mimetics can serve as powerful chemical and pharmacological tools to further elucidate the role of Smac and its cellular binding partners in apoptosis regulation and may be developed as a new class of anti-cancer drugs.

Apoptosis Regulatory Proteins↗

Structure-based discovery of nonpeptidic small organic compounds to block the T cell response to myelin basic protein.

We have utilized a computational structure-based approach to identify nonpeptidic small organic compounds that bind to a human leukocyte antigen (HLA) DR1301 molecule (HLA-DR1301 or DR1301) and block the presentation of myelin basic protein peptide 152-165 (MBP 152-165) to T cells. A three-dimensional (3D) structure of DR1301 was derived by homology modeling followed by extensive molecular dynamics simulation for structural refinement. Computational structure-based database searching was performed to identify nonpeptidic small-molecule candidates from the National Cancer Institute (NCI) database containing over 150 000 compounds that can effectively interact with the peptide-binding groove of the HLA molecule. By in vitro testing of 106 candidate small molecules, two lead compounds were confirmed to specifically block IL-2 secretion by DR1301-restricted T cells in a dose-dependent and reversible manner. The specificity of blocking DR1301-restricted MBP presentation was further validated in a binding assay using an analogue of the most potent lead compound. Computational docking was performed to predict the three-dimensional binding model of these confirmed small molecule blockers to the DR1301 molecule and to gain structural insight into their interactions. Our results suggest that computational structure-based searching is an effective approach to discover nonpeptidic small organic compounds to block the interaction between DR1301 and T cells. The nonpeptidic small organic compounds identified in this study are useful pharmacological tools to study the interactions between HLA molecules and T cells and a starting point for the development of a novel therapeutic strategy for the treatment of multiple sclerosis (MS) or other immune-related disorders.

Animals↗

Structure-based design, synthesis, and evaluation of conformationally constrained mimetics of the second mitochondria-derived activator of caspase that target the X-linked inhibitor of apoptosis protein/caspase-9 interaction site.

A successful structure-based design of conformationally constrained second mitochondria-derived activator of caspase (Smac) mimetics that target the XIAP/caspase-9 interaction site is described. The most potent Smac mimetic 12d has a Ki of 350 nM for binding to the XIAP BIR3 domain protein. 12d is found to be effective in enhancing apoptosis induced by cisplatin in PC-3 human prostate cancer cells.

Amino Acid Motifs↗