SEARCH · PubMed Health

Results for “Molecular Docking Simulation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,297 records · Page 72Linked to original sources

PubMed1996

Ligand recognition in mu opioid receptor: experimentally based modeling of mu opioid receptor binding sites and their testing by ligand docking.

For three-dimensional understanding of the mechanisms that control potency and selectivity of the ligand binding at the atomic level, we have analysed opioid receptor-ligand interaction based on the receptor's 3D model. As a first step, we have constructed molecular models for the multiple opioid receptor subtypes using bacteriorhodopsin as a template. The S-activated dihydromorphine derivatives should serve as powerful tools in mapping the three-dimensional structure of the mu opioid receptor, including the nature of the agonist-mediated conformational change that permits G protein-coupling to "second messenger' effector molecules, and in identifying specific ligand-binding contacts with the mu opioid receptor. The analyses of the interactions of some opioid ligands with the predicted ligand binding sites are consistent with the results of the affinity labeling experiments.

Affinity Labels↗

PubMed2002

MIAX: a new paradigm for modeling biomacromolecular interactions and complex formation in condensed phases.

A new paradigm is proposed for modeling biomacromolecular interactions and complex formation in solution (protein-protein interactions so far in this report) that constitutes the scaffold of the automatic system MIAX (acronym for Macromolecular Interaction Assessment X). It combines in a rational way a series of computational methodologies, the goal being the prediction of the most native-like protein complex that may be formed when two isolated (unbound) protein monomers interact in a liquid environment. The overall strategy consists of first inferring putative precomplex structures by identification of binding sites or epitopes on the proteins surfaces and a simultaneous rigid-body docking process using geometric instances alone. Precomplex configurations are defined here as all those decoys the interfaces of which comply substantially with the inferred binding sites and whose free energy values are lower. Retaining all those precomplex configurations with low energies leads to a reasonable number of decoys for which a flexible treatment is amenable. A novel algorithm is introduced here for automatically inferring binding sites in proteins given their 3-D structure. The procedure combines an unsupervised learning algorithm based on the self-organizing map or Kohonen network with a 2-D Fourier spectral analysis. To model interaction, the potential function proposed here plays a central role in the system and is constituted by empirical terms expressing well-characterized factors influencing biomacromolecular interaction processes, essentially electrostatic, van der Waals, and hydrophobic. Each of these procedures is validated by comparing results with observed instances. Finally, the more demanding process of flexible docking is performed in MIAX embedding the potential function in a simulated annealing optimization procedure. Whereas search of the entire configuration hyperspace is a major factor precluding hitherto systems from efficiently modeling macromolecular interaction modes and complex structures, the paradigm presented here may constitute a step forward in the field because it is shown that a rational treatment of the information available from the 3-D structure of the interacting monomers combined with conveniently selected computational techniques can assist to elude search of regions of low probability in configuration space and indeed lead to a highly efficient system oriented to solve this intriguing and fundamental biologic problem.

Algorithms↗

PubMed2005

Enantiomeric N-methyl-4-piperidyl benzilates as muscarinic receptor ligands: Radioligand binding studies and docking studies to models of the three muscarinic receptors M1, M2 and M3.

Benzilic ester derivatives with a basic moiety like N-methyl-4-piperidyl benzilates are potential drugs for the treatment of urinary incontinence, duodenal and gastric ulcers and Parkinson's disease. The effect of structural variations of chiral N-methyl-4-piperidyl benzilates was investigated using radioligand binding studies on muscarinic receptors (M1-M3). The results of the binding studies demonstrate that the absolute configuration and the aromatic substituent of benzilates have an influence on muscarinic affinity and selectivity. In this regard, (S)-configuration of benzilates and hydrophilic aromatic substituents seems to enhance muscarinic affinity. A model of the receptor ligand complex for N-methyl-4-piperidyl benzilates was obtained by molecular modelling. Both the affinity of enantiomeric benzilic esters and the subtype selectivity for muscarinic receptors are comprehensively explained by this model.

Animals↗

PubMed2005

Comparing protein-ligand docking programs is difficult.

There is currently great interest in comparing protein-ligand docking programs. A review of recent comparisons shows that it is difficult to draw conclusions of general applicability. Statistical hypothesis testing is required to ensure that differences in pose-prediction success rates and enrichment rates are significant. Numerical measures such as root-mean-square deviation need careful interpretation and may profitably be supplemented by interaction-based measures and visual inspection of dockings. Test sets must be of appropriate diversity and of good experimental reliability. The effects of crystal-packing interactions may be important. The method used for generating starting ligand geometries and positions may have an appreciable effect on docking results. For fair comparison, programs must be given search problems of equal complexity (e.g. binding-site regions of the same size) and approximately equal time in which to solve them. Comparisons based on rescoring require local optimization of the ligand in the space of the new objective function. Re-implementations of published scoring functions may give significantly different results from the originals. Ostensibly minor details in methodology may have a profound influence on headline success rates.

Algorithms↗

PubMed1997

Entamoeba histolytica: computer-assisted modeling of phosphofructokinase for the prediction of broad-spectrum antiparasitic agents.

Pyrophosphate-dependent phosphofructokinase (PPi-PFK) is the rate-limiting glycolytic enzyme found in the pathogenic protists Entamoeba histolytica, Giardia lamblia, Toxoplasma gondii, Trichomonas vaginalis, and Naegleria fowleri. The enzyme differs significantly from ATP-dependent phosphofructokinases found in humans and as such represents an important drug target. Current therapy for infections caused by these pathogens is inadequate, especially for children, pregnant women, and the immune compromised. The development of more selective, safer agents in imperative, as parasitic infections are currently a significant health threat worldwide and will likely become increasingly common agents of disease in the future. For the purpose of designing drugs to treat parasitic infections, we have constructed a model of PPi-PFK from E. histolytica based on the three-dimensional structure of the ATP-dependent PFK from Bacillus stearothermophilus. The model was used with the computer program Dock 3.5 (University of California, San Francisco) to predict the binding of pyrophosphate and selected bisphosphonates to the enzyme. The predicted drug-enzyme interactions suggested that two of these compounds would be competitive inhibitors of pyrophosphate. These drugs were tested against E. histolytica and inhibited the growth of amebae in vitro. This class of compounds may have broad-spectrum antiparasitic activity and, in the future, may facilitate the treatment of serious parasitic infections.

Amino Acid Sequence↗

PubMed2006

Identification of human liver mitochondrial aldehyde dehydrogenase as a potential target for microcystin-LR.

Microcystins (MCs) are hepatotoxins produced by a variety of freshwater cyanobacteria. The toxicity of these hepatotoxins is a severe health issue for both humans and livestock; MCs have been implicated in the development of liver cancer, necrosis, and even deadly intrahepatic bleeding. Microcystin-LR (MC-LR) is the MC variant most commonly encountered in a contaminated aquatic system. Thus far, MC-LR has only been shown to target the serine/threonine protein phosphatases 1 and 2A (PP1 and PP2A) and it is still unknown whether MC-LR can bind and inhibit any other protein targets inside the cell. To find potential MC-LR targets, we screened a phage display library for peptide ligands that specifically recognize MC-LR. Using these peptide sequences as guides, we performed a series of bioinformatics analyses revealing that MC-LR binds human liver aldehyde dehydrogenase 2 (ALDH2) at residues 447-451. We confirmed MC-LR binding of ALDH2 via automated docking computation, which yielded results matching our experimental and bioinformatics analyses. ALDH2 dysfunction may lead to aldehyde-induced reactive oxygen species (ROS) generation and, in turn, apoptosis. Therefore, ALDH2 could potentially be a target of MC-LR associated with the process of ROS-induced apoptosis. Our current study presents a new approach to the study of interactions of biological molecules by combining phage display technology with computational methods.

Aldehyde Dehydrogenase↗

PubMed2003

Biochemical filtering of a protein-protein docking simulation identifies the structure of a complex between a recombinant antibody fragment and alpha-bungarotoxin.

The structural characterization of a complex of alpha-bungarotoxin with a recombinant antibody fragment that mimics the acetylcholine receptor was achieved using docking simulation procedures. To drive the computer simulation towards a limited set of solutions with biological significance, a filter, incorporating general considerations of antigen-antibody interactions, specificity of the selected antibody fragment and results from alpha-bungarotoxin epitope mapping, was adopted. Two similar structures were obtained for the complex, both of them stabilized by cation-pi and hydrophobic interactions due to tyrosilyl residues of the antibody fragment. Site-directed mutagenesis studies, removing each of the latter aromatic residues and causing full inactivation of the interaction process between the antibody fragment and the neurotoxin, support the validity of the calculated structure of the complex.

Amino Acid Sequence↗

PubMed2001

Ligand-protein inverse docking and its potential use in the computer search of protein targets of a small molecule.

Ligand-protein docking has been developed and used in facilitating new drug discoveries. In this approach, docking single or multiple small molecules to a receptor site is attempted to find putative ligands. A number of studies have shown that docking algorithms are capable of finding ligands and binding conformations at a receptor site close to experimentally determined structures. These algorithms are expected to be equally applicable to the identification of multiple proteins to which a small molecule can bind or weakly bind. We introduce a ligand-protein inverse-docking approach for finding potential protein targets of a small molecule by the computer-automated docking search of a protein cavity database. This database is developed from protein structures in the Protein Data Bank (PDB). Docking is conducted with a procedure involving multiple-conformer shape-matching alignment of a molecule to a cavity followed by molecular-mechanics torsion optimization and energy minimization on both the molecule and the protein residues at the binding region. Scoring is conducted by the evaluation of molecular-mechanics energy and, when applicable, by the further analysis of binding competitiveness against other ligands that bind to the same receptor site in at least one PDB entry. Testing results on two therapeutic agents, 4H-tamoxifen and vitamin E, showed that 50% of the computer-identified potential protein targets were implicated or confirmed by experiments. The application of this approach may facilitate the prediction of unknown and secondary therapeutic target proteins and those related to the side effects and toxicity of a drug or drug candidate. Proteins 2001;43:217-226.

Computer Simulation↗

PubMed2004

Discerning the structure and energy of multiple transition states in protein folding using psi-analysis.

We quantify the degree to which folding occurs along a complex landscape with structurally distinct pathways using psi-analysis in combination with a protein engineering method that identifies native, non-covalent polypeptide interactions and their relative populations at the rate-limiting step. By probing the proximity of two specific partners, this method is extremely well-suited for comparison to theoretical simulations. Using ubiquitin as a model system, we detect individual pathways with site-resolved resolution, demonstrating that the protein folds through a native-like transition state ensemble with a common nucleus that contains heterogeneous features on its periphery. The consensus transition state topology has part of the major helix docked against four properly aligned beta-strands. However, structural heterogeneity exists in the transition state ensemble, wherein peripheral regions are differentially populated according to their relative stability. Pathway diversity reflects the variable order of formation of these peripheral elements, which radiate outward from the common nucleus. These results, which show only moderate agreement with traditional mutational phi-analysis, provide an extraordinarily detailed and quantitative description of protein folding.

Amino Acid Sequence↗

PubMed2006

Prediction of small-molecule binding to cytochrome P450 3A4: flexible docking combined with multidimensional QSAR.

The inhibition of cytochrome P450 3A4 (CYP3A4) by small molecules is a major mechanism associated with undesired drug-drug interactions, which are responsible for a substantial number of late-stage failures in the pharmaceutical drug-development process. For a quantitative prediction of associated pharmacokinetic parameters, a computational model was developed that allows prediction of the inhibitory potential of 48 structurally diverse molecules. Based on the experimental structure of CYP3A4, possible binding modes were first sampled by using automated docking (Yeti software) taking protein flexibility into account. The results are consistent with both X-ray crystallographic data and data from metabolic studies. Next, an ensemble of energetically favorable orientations was composed into a 4D dataset for use as input for a multidimensional QSAR technique (Raptor software). A dual-shell binding-site model that allows an explicit induced fit was then generated by using hydrophobicity scoring and hydrogen-bond propensity. The simulation reached a cross-validated r2 value of 0.825 and a predictive r2 value of 0.659. On average, the predicted binding affinity of the training ligands deviates by a factor of 2.7 from the experiment; those of the test set deviate by a factor of 3.8 in Ki.

Cytochrome P-450 CYP3A↗

PubMed2006

NOMAD-Ref: visualization, deformation and refinement of macromolecular structures based on all-atom normal mode analysis.

Normal mode analysis (NMA) is an efficient way to study collective motions in biomolecules that bypasses the computational costs and many limitations associated with full dynamics simulations. The NOMAD-Ref web server presented here provides tools for online calculation of the normal modes of large molecules (up to 100,000 atoms) maintaining a full all-atom representation of their structures, as well as access to a number of programs that utilize these collective motions for deformation and refinement of biomolecular structures. Applications include the generation of sets of decoys with correct stereochemistry but arbitrary large amplitude movements, the quantification of the overlap between alternative conformations of a molecule, refinement of structures against experimental data, such as X-ray diffraction structure factors or Cryo-EM maps and optimization of docked complexes by modeling receptor/ligand flexibility through normal mode motions. The server can be accessed at the URL http://lorentz.immstr.pasteur.fr/nomad-ref.php.

Computer Graphics↗

PubMed2003

Vpu from HIV-1 on an atomic scale: experiments and computer simulations.

Vpu is an 81 amino acid protein encoded by HIV-1. Its role is to amplify viral release by two mechanisms: (i) docking to CD4 with the consequence of targeting CD4 for ubiquitine-mediated degradation, and (ii) formation of ion channels to enhance particle release. The intensive research on its in vivo function, combined with structural investigations, makes this viral membrane protein one of the better characterised membrane proteins. The wealth of structural information enables the use of computational methods to elucidate the mechanisms of function on an atomic scale. The discovery of Vpu and the development of structural models in a chronological order is summarised and first efforts on investigating the mechanics are outlined.

Amino Acid Sequence↗

PubMed2004

Arg343 in human surfactant protein D governs discrimination between glucose and N-acetylglucosamine ligands.

Surfactant protein D (SP-D), one of the members of the collectin family of C-type lectins, is an important component of pulmonary innate immunity. SP-D binds carbohydrates in a calcium-dependent manner, but the mechanisms governing its ligand recognition specificity are not well understood. SP-D binds glucose (Glc) stronger than N-acetylglucosamine (GlcNAc). Structural superimposition of hSP-D with mannose- binding protein C (MBP-C) complexed with GlcNAc reveals steric clashes between the ligand and the side chain of Arg343 in hSP-D. To test whether Arg343 contributes to Glc > GlcNAc recognition specificity, we constructed a computational model of Arg343-->Val (R343V) mutant hSP-D based on homology with MBP-C. Automated docking of alpha-Me-Glc and alpha-Me-GlcNAc into wild-type hSP-D and the R343V mutant of hSP-D suggests that Arg343 is critical in determining ligand-binding specificity by sterically prohibiting one binding orientation. To empirically test the docking predictions, an R343V mutant recombinant hSP-D was constructed. Inhibition analysis shows that the R343V mutant binds both Glc and GlcNAc with higher affinity than the wild-type protein and that the R343V mutant binds Glc and GlcNAc equally well. These data demonstrate that Arg343 is critical for hSP-D recognition specificity and plays a key role in defining ligand specificity differences between MBP and SP-D. Additionally, our results suggest that the number of binding orientations contributes to monosaccharide binding affinity.

Acetylglucosamine↗

PubMed2003

Targeting Stat3 with G-quartet oligodeoxynucleotides in human cancer cells.

Stat3 is an oncogene that is activated in many human cancer cells. Genetic approaches that disrupt Stat3 activity result in inhibition of cancer cell growth and enhanced cell apoptosis supporting the development of novel drugs targeting Stat3 for cancer therapy. G-quartet oligodeoxynucleotides (ODNs) were demonstrated to be potent inhibitors of Stat3 DNA binding activity in vitro with the G-quartet ODN, T40214, having an IC(50) of 7 microM. Computer-simulated docking studies indicated that G-quartet ODNs mainly interacted with the SH2 domain of Stat3 and were capable of inserting between the SH2 domains of Stat3 dimers bound to DNA. We demonstrated that the G-rich ODN T40214, which forms a G-quartet structure at intracellular but not extracellular K+ ion concentrations, is delivered efficiently into the cytoplasm and nucleus of cancer cells where it inhibited IL-6-stimulated Stat3 activation and suppressed Stat3-mediated upregulation of bcl-x and mcl-1 gene expression. Thus, G-quartet represents a new class of drug for targeting of Stat3 within cancer cells.

Base Sequence↗

PubMed2006

Activity-structure correlations in divergent lectin evolution: fine specificity of chicken galectin CG-14 and computational analysis of flexible ligand docking for CG-14 and the closely related CG-16.

Gene duplication and sequence divergence are driving forces toward establishing protein families. To examine how sequence changes affect carbohydrate specificity, the two closely related proto-type chicken galectins CG-14 and CG-16 were selected as models. Binding properties were analyzed using a highly sensitive solid-phase assay. We tested 56 free saccharides and 34 well-defined glycoproteins. The two galectins share preference for the II (Galbeta1-4GlcNAc) versus I (Galbeta1-3GlcNAc) version of beta-galactosides. A pronounced difference is found owing to the reactivity of CG-14 with histo-blood group ABH active oligosaccharides and A/B active glycoproteins. These experimental results prompted to determine activity-structure correlations by modeling. Computational analysis included consideration of the flexibility of binding partners and the presence of water molecules. It provided a comparative description of complete carbohydrate recognition domains, which had so far not been characterized in animal galectins. The structural models assigned II, I selectivity to a region downstream of the central Trp moiety. Docking revealed that the tetrasaccharides can be accommodated in their free-state low-energy conformations. CG-14's preference for A versus B epitopes could be attributed to a contact between His124 and the N-acetyl group of GalNAc. Regarding intergalectin comparison, the Ala53/Cys51 exchange affects the interaction potential of His54/His52. Close inspection of simulated dynamic interplay revealed reorientation of His124 at the site of the His124/Glu123 substitution, with potential impact on ligand dissociation. In summary, this study identifies activity differences and provides information on their relation to structural divergence, epitomizing the value of this combined approach beyond galectins.

Amino Acid Sequence↗

PubMed1991

Structural polymorphism in the major groove of a 5S RNA gene complements the zinc finger domains of transcription factor IIIA.

Metal complexes that bind to DNA on the basis of shape-selection have been used to map the conformational features of the DNA binding site for transcription factor IIIA. Conformationally distinct segments are detected on the 5S rRNA gene that correspond closely to the binding sites identified for the individual zinc finger domains of the protein. The local conformations are characterized by a major groove opened because of a change in base pair inclination and/or displacement at a central 5'-pyrimidine-purine-3' step, flanked by a widened minor groove, as would arise at the junctions between alternating B- and A-like DNA segments. Docking experiments with a consensus structure of a zinc finger reveal that the mixed A-B binding site accommodates the peptide domain better than either canonical B- or A-DNA helices. The close structural matching of the conformational variations in the 5S rDNA both to the proposed sites of zinc finger binding and to the shape of an individual zinc finger domain points to DNA structural polymorphism as providing an important determinant in recognition. In particular, shape selection in the 5' half of the internal control region may orient the multiple finger domains.

Animals↗

PubMed2004

Normal mode-based fitting of atomic structure into electron density maps: application to sarcoplasmic reticulum Ca-ATPase.

A method for the flexible docking of high-resolution atomic structures into lower resolution densities derived from electron microscopy is presented. The atomic structure is deformed by an iterative process using combinations of normal modes to obtain the best fit of the electron microscopical density. The quality of the computed structures has been evaluated by several techniques borrowed from crystallography. Two atomic structures of the SERCA1 Ca-ATPase corresponding to different conformations were used as a starting point to fit the electron density corresponding to a different conformation. The fitted models have been compared to published models obtained by rigid domain docking, and their relation to the known crystallographic structures are explored by normal mode analysis. We find that only a few number of modes contribute significantly to the transition. The associated motions involve almost exclusively rotation and translation of the cytoplasmic domains as well as displacement of cytoplasmic loops. We suggest that the movements of the cytoplasmic domains are driven by the conformational change that occurs between nonphosphorylated and phosphorylated intermediate, the latter being mimicked by the presence of vanadate at the phosphorylation site in the electron microscopy structure.

Calcium-Transporting ATPases↗

PubMed2005

Chiral recognition of aromatic compounds by beta-cyclodextrin based on bimodal complexation.

The chiral recognition of the selected aromatic chiral compounds by native beta-cyclodextrin (beta-CD) based on bimodal complexation was studied using a flexible docking algorithm FDOCK. A quantitative empirical free energy relationship model was employed to predict the complex stability constants and the preferred binding modes. The results showed that the calculated complex stability constants are in good agreement with the experimental data. Furthermore, the main force responsible for host-guest complexation is the van der Waals force and the chiral molecules are completely included into the beta-CD cavity. The chiral recognition for the selected aromatic chiral compounds is the result of the van der Waals force counterbalancing with the other effects, such as the electrostatic interaction and the hydrophobic effect.

Algorithms↗