Biomedical subjects

Yipin Lu

Publications and source records attributed to Yipin Lu.

11 recordsLinked to original sources

PubMed2006

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↗

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↗

PubMed2006

Structure-based design of spiro-oxindoles as potent, specific small-molecule inhibitors of the MDM2-p53 interaction.

Potent, specific, non-peptide small-molecule inhibitors of the MDM2-p53 interaction were successfully designed. The most potent inhibitor (MI-63) has a K(i) value of 3 nM binding to MDM2 and greater than 10,000-fold selectivity over Bcl-2/Bcl-xL proteins. MI-63 is highly effective in activation of p53 function and in inhibition of cell growth in cancer cells with wild-type p53 status. MI-63 has excellent specificity over cancer cells with deleted p53 and shows a minimal toxicity to normal cells.

Antineoplastic Agents↗

PubMed2005

Structure-based design of potent non-peptide MDM2 inhibitors.

A successful structure-based design of a class of non-peptide small-molecule MDM2 inhibitors targeting the p53-MDM2 protein-protein interaction is reported. The most potent compound 1d binds to MDM2 protein with a Ki value of 86 nM and is 18 times more potent than a natural p53 peptide (residues 16-27). Compound 1d is potent in inhibition of cell growth in LNCaP prostate cancer cells with wild-type p53 and shows only a weak activity in PC-3 prostate cancer cells with a deleted p53. Importantly, 1d has a minimal toxicity to normal prostate epithelial cells. Our studies provide a convincing example that structure-based strategy can be employed to design highly potent, non-peptide, cell-permeable, small-molecule inhibitors to target protein-protein interaction, which remains a very challenging area in chemical biology and drug design.

Biomimetic Materials↗

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

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↗

PubMed2004

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↗

PubMed2004

Formation of a novel reversible cytochrome P450 spectral intermediate: role of threonine 303 in P450 2E1 inactivation.

tert-Butyl acetylene (tBA) is a mechanism-based inactivator of cytochromes P450 2E1 and 2E1 T303A; however, the inactivation of the T303A mutant could be reversed by overnight dialysis. The inactivation of P450 2E1 T303A, but not the wild-type 2E1 enzyme, by tBA resulted in the formation of a novel reversible acetylene-iron spectral intermediate with an absorption maximum at 485 nm. The formation of this intermediate required oxygen and could be monitored spectrally with time. Although the alternate oxidants tert-butyl hydroperoxide (tBHP) and cumene hydroperoxide (CHP) supported the inactivation of wild-type P450 2E1 by tBA in a reductase- and NADPH-free system, only tBHP supported the inactivation of the 2E1 T303A mutant. The losses in enzymatic activity occurred concomitantly with losses in the native P450 heme, which were accompanied by the formation of tBA-adducted heme products. The inactivations supported by tBHP and CHP were completely irreversible with overnight dialysis. Spectral binding constants (K(s)) for the binding of tBA to the 2E1 P450s together with models of the enzymes with the acetylenic inactivator bound in the active site suggest that the T303A mutation results in increased hydrophobic interactions between tBA and nearby P450 residues, leading to a higher binding affinity for the acetylene compound in the mutant enzyme. Together, these data support a role for the highly conserved T303 residue in proton delivery to the active site of P450 2E1 and in the inactivation of the 2E1 P450s by small acetylenic compounds.

Alkynes↗

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↗

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↗

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↗