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At least 487 records · Page 27Linked to original sources
PubMed2003

Presynaptic neurotrophin-3 increases the number of tectal synapses, vesicle density, and number of docked vesicles in chick embryos.

To determine whether presynaptically derived neurotrophins may contribute to synaptic plasticity, we examined whether neurotrophin-3 (NT-3) changed the number, size, vesicle content, or vesicle distribution of synapses within the retinorecipient layers of the chick optic tectum. In this system, endogenous NT-3 derives presynaptically from retinal ganglion cell axons. Retinotectal synapses comprise the majority of synapses in superficial tectal layers, as demonstrated by destruction of retinotectal input by intraocular application of the drug monensin. To examine the effect of increased or decreased levels of NT-3, either exogenous NT-3 or monoclonal NT-3 blocking antibodies were injected into the optic tectum of 19-day-old chick embryos, spiked with radiolabeled protein to verify the success of injections and estimate effective concentrations. After 48 hours, the ultrastructure of superficial tectal layers was analyzed and compared with samples from control tecta injected with cytochrome C. NT-3 increased the number of synapses, synaptic vesicles/profile, synaptic vesicle densities, the number of docked vesicles, and the length of the synaptic profile. Deprivation of anterogradely transported endogenous NT-3 with NT-3 antibodies resulted in the opposite effect: decreased numbers of synapses, decreased vesicle densities, and decreased numbers of docked vesicles. Brain-derived neurotrophic factor (BDNF) had a largely different effect than NT-3. BDNF increased the density of vesicles and deprivation of endogenous TrkB ligands with TrkB fusion protein reduced the density of vesicles in the synapses, without effects on synapse number or docked vesicles. We conclude that anterogradely transported NT-3 affects synapse strength in a way that differs from that of presumably postsynaptic-derived BDNF.

Animals↗
PubMed1987

Import of frog prepropeptide GLa into microsomes requires ATP but does not involve docking protein or ribosomes.

Frog prepropeptide GLa, a precursor to a secretory protein containing 64 amino acids, was processed and imported by dog pancreas microsomes. These events did not depend on either docking protein or on the presence of ribosomes. A hybrid protein between the first 60 amino acids of prepropeptide GLa and an unrelated peptide of 49 amino acids fused to the carboxy terminus, however, behaved like a typical secretory protein precursor with regard to docking protein dependence. This suggests that independence of the need for docking protein, in the case of prepropeptide GLa, can be attributed to the size of the precursor protein. Processing and import of prepropeptide GLa by microsomes were ATP dependent. Therefore, import of proteins into the endoplasmic reticulum (ER) includes an ATP-requiring step not involving a ribosome/ribosome receptor or signal recognition particle (SRP)/docking protein interaction.

Adenosine Triphosphate↗
PubMed2004

Automated docking of highly flexible ligands by genetic algorithms: a critical assessment.

An improved version of the fragment-based flexible ligand docking approach SEED-FFLD is tested on inhibitors of human immunodeficiency virus type 1 protease, human alpha-thrombin and the estrogen receptor beta. The docking results indicate that it is possible to correctly reproduce the binding mode of inhibitors with more than ten rotatable bonds if the strain in their covalent geometry upon binding is not large. A high degree of convergence towards a unique binding mode in multiple runs of the genetic algorithm is proposed as a necessary condition for successful docking.

Algorithms↗
PubMed2002

Docking of small ligands to low-resolution and theoretically predicted receptor structures.

We have developed a simple docking procedure that is able to utilize low-resolution models of proteins created by structure prediction algorithms such as threading or ab initio folding to predict the conformation of receptor-small ligand complexes. In our approach, using only approximate, discretized models of both molecules, we search for the steric and quasi-chemical complementarity between a ligand and the receptor molecules. This averaging procedure allows for the compensation of numerous structural inaccuracies resulting from the theoretical predictions of the receptor structure. The best relative orientation of these two models is obtained by an exhaustive scan over the rigid body's six-dimensional translational and rotational degrees of freedom. The search method is based on a real space grid-searching algorithm, unlike docking methods based on the fast Fourier Transform algorithm. We have applied this algorithm to rebuild structures of several complexes available in the Protein Data Bank. The structures of the receptors are produced by means of our threading algorithm PROSPECTOR, subsequently refined, and then utilized in the docking experiment. In many cases, not only is the localization of the binding site on the receptor surface correctly identified, but the proper orientation of the bounded ligand is also reasonably well reproduced within the level of accuracy of the modeled receptor itself.

Algorithms↗
PubMed2005

Importance of accurate charges in molecular docking: quantum mechanical/molecular mechanical (QM/MM) approach.

The extent to which accuracy of electric charges plays a role in protein-ligand docking is investigated through development of a docking algorithm, which incorporates quantum mechanical/molecular mechanical (QM/MM) calculations. In this algorithm, fixed charges of ligands obtained from force field parameterization are replaced by QM/MM calculations in the protein environment, treating only the ligands as the quantum region. The algorithm is tested on a set of 40 cocrystallized structures taken from the Protein Data Bank (PDB) and provides strong evidence that use of nonfixed charges is important. An algorithm, dubbed "Survival of the Fittest" (SOF) algorithm, is implemented to incorporate QM/MM charge calculations without any prior knowledge of native structures of the complexes. Using an iterative protocol, this algorithm is able in many cases to converge to a nativelike structure in systems where redocking of the ligand using a standard fixed charge force field exhibits nontrivial errors. The results demonstrate that polarization effects can play a significant role in determining the structures of protein-ligand complexes, and provide a promising start towards the development of more accurate docking methods for lead optimization applications.

Algorithms↗
PubMedDate not supplied

Docking of combinatorial peptide libraries into a broadly cross-reactive human IgM.

A monoclonal IgM cryoglobulin with diverse binding behavior was isolated from a patient (Mez) with Waldenström's macroglobulinemia. It gave very high titers in the binding of combinatorially synthesized libraries of peptides ranging in size from two to eight residues. The crystal structure of Mez Fv revealed that the binding site was divided into two cavities of unequal volumes with dimensions and chemical properties that were compatible with the binding of peptides. Access to this unique combination of structural information and peptide binding data led us to carry out Mez-peptide docking simulations to gain insight into the Mez binding propensities. In the present article, the results for docking of five peptide libraries are combined with discussions of the methods and approximations involved in the docking process. We analyze the origins of peptide binding affinity for Mez IgM in terms of its cross-reactivity and its structural preferences.

Antibodies, Monoclonal↗
PubMedDate not supplied

Mcg light chain dimer as a model system for ligand design: a docking study.

Mcg light chain dimer has been extensively studied by crystallography and peptide binding studies to investigate its peptide cross-reactivity as well as to use it as a model system for designing space filling peptide ligands. Here we extend these investigations by utilizing automated docking. Mcg light chain dimer is an ideal model system for such study due to the availability of experimental data for both the native structure and the 14 complexes with various peptide ligands. We show the ability of the docking approach to reproduce the experimental structures and discuss the limitations associated with such outcomes. We demonstrate the usefulness of the docking approach in generating structural information otherwise not available from the experiment.

Binding Sites, Antibody↗
PubMed1997

Template-based docking of a prolactin receptor proline-rich motif octapeptide to FKBP12: implications for cytokine receptor signaling.

A conserved proline-rich motif (PRM) in the cytoplasmic domain of cytokine receptors has been suggested to be a signaling switch regulated by the action of the FK506 binding protein (FKBP) family of peptidylprolyl isomerases (O'Neal KD, Yu-Lee LY, Shearer WT, 1995, Ann NY Acad Sci 766:282-284). We have docked the prolactin receptor PRM (Ile1-Phe2-Pro3-Pro4-Val5-Pro6-Gly7-Pro8) to the ligand binding site of FKBP12. The procedure involved conformational search restricted by NMR restraints (O'Neal KD et al., 1996, Biochem J 315:833-844), energy minimization of the octapeptide conformers so obtained, template-based docking of a selected conformer to FKBP12, and energy refinement of the resulting complex. The template used was the crystal structure of a cyclic FK506-peptide hybrid bound to FKBP12. Val5-Pro6 of the PRM was taken to be the biologically relevant Xaa-Pro bond. The docked conformer is stabilized by two intramolecular hydrogen bonds, N7H7-->O4 and N2H2-->O8, and two intermolecular ones, Ile56; N-H-->O = C:Pro6 and Tyr82:O-H-->O = C:Gly7. This conformer features a Type I beta-turn and has extensive hydrophobic contacts with the FKBP12 binding surface. The observed interactions support the hypothesis that FKBP12 catalyzes cis-trans isomerization in the PRM when it is part of the longer cytoplasmic domain of a cytokine receptor, and suggest a significant role for the PRM in signal transduction.

Amino Acid Sequence↗
PubMed2003

Implicit solvent models for flexible protein-protein docking by molecular dynamics simulation.

The suitability of three implicit solvent models for flexible protein-protein docking by procedures using molecular dynamics simulation is investigated. The three models are (i) the generalized Born (GB) model implemented in the program AMBER6.0; (ii) a distance-dependent dielectric (DDD) model; and (iii) a surface area-dependent model that we have parameterized and call the NPSA model. This is a distance-dependent dielectric model modified by neutralizing the ionizable side-chains and adding a surface area-dependent solvation term. These solvent models were first tested in molecular dynamics simulations at 300 K of the native structures of barnase, barstar, segment B1 of protein G, and three WW domains. These protein structures display a range of secondary structure contents and stabilities. Then, to investigate the performance of the implicit solvent models in protein docking, molecular dynamics simulations of barnase/barstar complexation, as well as PIN1 WW domain/peptide complexation, were conducted, starting from separated unbound structures. The simulations show that the NPSA model has significant advantages over the DDD and GB models in maintaining the native structures of the proteins and providing more accurate docked complexes.

Bacterial Proteins↗
PubMed2003

A novel shape complementarity scoring function for protein-protein docking.

Shape complementarity is the most basic ingredient of the scoring functions for protein-protein docking. Most grid-based docking algorithms use the total number of grid points at the binding interface to quantify shape complementarity. We have developed a novel Pairwise Shape Complementarity (PSC) function that is conceptually simple and rapid to compute. The favorable component of PSC is the total number of atom pairs between the receptor and the ligand within a distance cutoff. When applied to a benchmark of 49 test cases, PSC consistently ranks near-native structures higher and produces more near-native structures than the traditional grid-based function, and the improvement was seen across all prediction levels and in all categories of the benchmark. Without any post-processing or biological information about the binding site except the complementarity-determining region of antibodies, PSC predicts the complex structure correctly for 6 test cases, and ranks at least one near-native structure in the top 20 predictions for 18 test cases. Our docking program ZDOCK has been parallelized and the average computing time is 4 minutes using sixteen IBM SP3 processors. Both ZDOCK and the benchmark are freely available to academic users (http://zlab.bu.edu/~ rong/dock).

Binding Sites↗
PubMed2003

A soft docking algorithm for predicting the structure of antibody-antigen complexes.

An efficient soft docking algorithm is described for predicting the mode of binding between an antibody and its antigen based on the three-dimensional structures of the molecules. The basic tools are the "simplified protein" model and the docking algorithm of Wodak and Janin. The side-chain flexibility of Arg, Lys, Asp, Glu, and Met residues on the protein surface is taken into account. A combined filtering technique is used to select candidate binding modes. After energy minimization, we calculate a scoring function, which includes electrostatic and desolvation energy terms. This procedure was applied to targets 04, 05, and 06 of CAPRI, which are complexes of three different camelid antibody VHH variable domains with pig alpha-amylase. For target 06, two native-like structures with a root-mean-square deviation < 4.0 A relative to the X-ray structure were found within the five top ranking structures. For targets 04 and 05, our procedure produced models where more than half of the antigen residues forming the epitope were correctly predicted, albeit with a wrong VHH domain orientation. Thus, our soft docking algorithm is a promising tool for predicting antibody-antigen recognition.

Algorithms↗
PubMed2003

ZDOCK: an initial-stage protein-docking algorithm.

The development of scoring functions is of great importance to protein docking. Here we present a new scoring function for the initial stage of unbound docking. It combines our recently developed pairwise shape complementarity with desolvation and electrostatics. We compare this scoring function with three other functions on a large benchmark of 49 nonredundant test cases and show its superior performance, especially for the antibody-antigen category of test cases. For 44 test cases (90% of the benchmark), we can retain at least one near-native structure within the top 2000 predictions at the 6 degrees rotational sampling density, with an average of 52 near-native structures per test case. The remaining five difficult test cases can be explained by a combination of poor binding affinity, large backbone conformational changes, and our algorithm's strong tendency for identifying large concave binding pockets. All four scoring functions have been integrated into our Fast Fourier Transform based docking algorithm ZDOCK, which is freely available to academic users at http://zlab.bu.edu/~ rong/dock.

Algorithms↗
PubMed2004

Visualizing complexes of phospholipids with Streptomyces phospholipase D by automated docking.

The automated docking program AutoDock was used to dock nine phosphatidic acids (PAs), six phosphatidylcholines, five phosphatidylethanolamines, four phosphatidylglycerols, one phosphatidylinositol and two phosphatidylserines, which have two identical saturated fatty acid residues with an even numbers of carbon atoms, onto the active site of Streptomyces sp. PMF phospholipase D (PLD). Two PAs with one double bond on the fatty acid chain linked to the C2 of the glycerol residue were also docked. In general, binding energies become progressively more negative as fatty acid residues become longer. When these residues are of sufficient length, one is coiled against a hydrophobic cliff in a well that also holds the glycerol and phosphate residues and the head group, while the other generally is bound by a hydrophobic surface outside the well. Phosphatidylcholines have the only head group that is firmly bound by the active site, giving a possible structural explanation for the low selectivity of Streptomyces PLD for other phospholipid substrates.

Binding Sites↗
PubMed2005

Various strategies of using residual dipolar couplings in NMR-driven protein docking: application to Lys48-linked di-ubiquitin and validation against 15N-relaxation data.

When classical, Nuclear Overhauser Effect (NOE)-based approaches fail, it is possible, given high-resolution structures of the free molecules, to model the structure of a complex in solution based solely on chemical shift perturbation (CSP) data in combination with orientational restraints from residual dipolar couplings (RDCs) when available. RDCs can be incorporated into the docking following various strategies: as direct restraints and/or as intermolecular intervector projection angle restraints (Meiler et al., J Biomol NMR 2000;16:245-252). The advantage of the latter for docking is that they directly define the relative orientation of the molecules. A combined protocol in which RDCs are first introduced as intervector projection angle restraints and at a later stage as direct restraints is shown here to give the best performance. This approach, implemented in our information-driven docking approach HADDOCK (Dominguez et al., J Am Chem Soc 2003;125:1731-1737), is used to determine the solution structure of the Lys48-linked di-ubiquitin, for which chemical shift mapping, RDCs, and (15)N-relaxation data have been previously obtained (Varadan et al., J Mol Biol 2002;324:637-647). The resulting structures, derived from CSP and RDC data, are cross-validated using (15)N-relaxation data. The solution structure differs from the crystal structure by a 20 degrees rotation of the two ubiquitin units relative to each other.

Algorithms↗
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↗
PubMed2005

Progress in protein-protein docking: atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side-chain flexibility.

RosettaDock uses real-space Monte Carlo minimization (MCM) on both rigid-body and side-chain degrees of freedom to identify the lowest free energy docked arrangement of 2 protein structures. An improved version of the method that uses gradient-based minimization for off-rotamer side-chain optimization and includes information from unbound structures was used to create predictions for Rounds 4 and 5 of CAPRI. First, large numbers of independent MCM trajectories were carried out and the lowest free energy docked configurations identified. Second, new trajectories were started from these lowest energy structures to thoroughly sample the surrounding conformation space, and the lowest energy configurations were submitted as predictions. For all cases in which there were no significant backbone conformational changes, a small number of very low-energy configurations were identified in the first, global search and subsequently found to be close to the center of the basin of attraction in the free energy landscape in the second, local search. Following the release of the experimental coordinates, it was found that the centers of these free energy minima were remarkably close to the native structures in not only the rigid-body orientation but also the detailed conformations of the side-chains. Out of 8 targets, the lowest energy models had interface root-mean-square deviations (RMSDs) less than 1.1 A from the correct structures for 6 targets, and interface RMSDs less than 0.4 A for 3 targets. The predictions were top submissions to CAPRI for Targets 11, 12, 14, 15, and 19. The close correspondence of the lowest free energy structures found in our searches to the experimental structures suggests that our free energy function is a reasonable representation of the physical chemistry, and that the real space search with full side-chain flexibility to some extent solves the protein-protein docking problem in the absence of significant backbone conformational changes. On the other hand, the approach fails when there are significant backbone conformational changes as the steric complementarity of the 2 proteins cannot be modeled without incorporating backbone flexibility, and this is the major goal of our current work.

Algorithms↗
PubMed2005

Development and testing of an automated approach to protein docking.

A new version of GRAMM was applied to Targets 14, 18, and 19 in CAPRI Round 5. The predictions were generated without manual intervention. Ten top-ranked matches for each target were submitted. The docking was performed by a rigid-body procedure with a smoothed potential function to accommodate conformational changes. The first stage was a global search on a fine grid with a projection of a smoothed Lennard-Jones potential. The top predictions from the first stage were subjected to the conjugate gradient minimization with the same smoothed potential. The resulting local minima were reranked according to the weighted sum of Lennard-Jones potential, pairwise residue-residue statistical preferences, cluster occupancy, and the degree of the evolutionary conservation of the predicted interface. For Targets 14 and 18, the conformation of the complex was predicted with root-mean-square deviation (RMSD) of the ligand interface atoms 0.68 A and 1.88 A correspondingly. For Target 19, the interface areas on both proteins were correctly predicted. The performance of the procedure was also analyzed on the benchmark of bound-unbound protein complexes. The results show that, on average, conformations of only 3 side-chains need to be optimized during docking of unbound structures before the backbone changes become a limiting factor. The GRAMM-X docking server is available for public use at http://www.bioinformatics.ku.edu.

Algorithms↗
PubMed2005

Biologically enhanced sampling geometric docking and backbone flexibility treatment with multiconformational superposition.

An efficient biologically enhanced sampling geometric docking method is presented based on the FTDock algorithm to predict the protein-protein binding modes. The active site data from different sources, such as biochemical and biophysical experiments or theoretical analyses of sequence data, can be incorporated in the rotation-translation scan. When discretizing a protein onto a 3-dimensional (3D) grid, a zero value is given to grid points outside a sphere centered on the geometric center of specified residues. In this way, docking solutions are biased toward modes where the interface region is inside the sphere. We also adopt a multiconformational superposition scheme to represent backbone flexibility in the proteins. When these procedures were applied to the targets of CAPRI, a larger number of hits and smaller ligand root-mean-square deviations (RMSDs) were obtained at the conformational search stage in all cases, and especially Target 19. With Target 18, only 1 near-native structure was retained by the biologically enhanced sampling geometric docking method, but this number increased to 53 and the least ligand RMSD decreased from 8.1 A to 2.9 A after performing multiconformational superposition. These results were obtained after the CAPRI prediction deadlines.

Algorithms↗