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Analgesia of newborn lambs before castration and tail docking with rubber rings.

This study assessed the effects of suckled sucrose and parenteral carprofen treatment on behavioural measurements of discomfort and serum haptoglobin concentration in lambs following rubber ring castration and/or tail docking. Twenty-eight male and 20 ewe lambs were allocated to either a male or ewe lamb control group (n=4) or to one of three male and two ewe lamb treatment groups (n=8). Male lambs in one treatment group received carprofen subcutaneously (0.5 mg/kg) 30 minutes before castration and docking. Lambs in all other treatment groups suckled sucrose or colostrum immediately before castration and/or tail docking. Behavioural measurements of discomfort were made following castration or tail docking in treatment groups and also in control animals which were not castrated or tail docked. Blood sampling of animals in treatment groups for analysis of serum haptoglobin, an acute phase protein used as an indicator of an acute inflammatory response, was performed before castration or docking and at 24 and 48 hours after castration or docking. Control lambs were blood sampled at 0, 24 and 48 hours following behavioural assessment Neither suckled sucrose nor carprofen treatment altered discomfort behaviour associated with castration or tail docking. Haptoglobin levels following castration or tail docking remained close to the detection limits of the assay and were similar to those recorded in control animals.

Analgesics, Non-Narcotic↗

[Analysis of veterinary certificates on tail docking in dogs].

Despite the fact that docking of dogs has been banned in Germany for years, many animals are still docked, mainly owing to overcome traditional thinking. This is possible by some exceptions made by the law: the import of dogs that have been docked abroad, and medical indications for docking. In order to substantiate the necessity of such medical indications, the patient material of the Small Animal Clinic of the Veterinary School Hanover was analysed and compared with a number of veterinary certificates for docked dogs that were to be shown at exhibitions, stating a medical indication. It shows that the latter predominantly cover dogs belonging to breeds that are traditionally docked, the Doberman in the first line. Contrasted with this, dogs from our own patient material showed an even breed distribution, with no Doberman at all within a five year period. Moreover, the fact that certain breeds were predominantly docked by the same veterinarian as well as the medical reasons stated were suspicious. Consequently, doubts should be raised in cases of accumulations of tail amputations in dogs belonging to a traditionally docked breed, when the reasons given are the same in several animals, and when the same veterinarian performs the operation in several dogs belonging to the same breeder. Because of the scientifically proven pain that is caused to the animal both at the time of the procedure and later, as well as the possibility of long lasting chronic health impairment owing to docking, it is necessary to consequently fight this malpractice. In order to prove the stated medical indication in individual cases, either a radiograph or photography must be submitted.

Amputation, Surgical↗

FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function.

The docking of flexible small molecule ligands to large flexible protein targets is addressed in this article using a two-stage simulation-based method. The methodology presented is a hybrid approach where the first component is a dock of the ligand to the protein binding site, based on deriving sets of simultaneously satisfied intermolecular hydrogen bonds using graph theory and a recursive distance geometry algorithm. The output structures are reduced in number by cluster analysis based on distance similarities. These structures are submitted to a modified Monte Carlo algorithm using the AMBER-AA molecular mechanics force field with the Generalized Born/Surface Area (GB/SA) continuum model. This solvent model is not only less expensive than an explicit representation, but also yields increased sampling. Sampling is also increased using a rotamer library to direct some of the protein side-chain movements along with large dihedral moves. Finally, a softening function for the nonbonded force field terms is used, enabling the potential energy function to be slowly turned on throughout the course of the simulation. The docking procedure is optimized, and the results are presented for a single complex of the arabinose binding protein. It was found that for a rigid receptor model, the X-ray binding geometry was reproduced and uniquely identified based on the associated potential energy. However, when side-chain flexibility was included, although the X-ray structure was identified, it was one of three possible binding geometries that were energetically indistinguishable. These results suggest that on relaxing the constraint on receptor flexibility, the docking energy hypersurface changes from being funnel-like to rugged. A further 14 complexes were then examined using the optimized protocol. For each complex the docking methodology was tested for a fully flexible ligand, both with and without protein side-chain flexibility. For the rigid protein docking, 13 out of the 15 test cases were able to find the experimental binding mode; this number was reduced to 11 for the flexible protein docking. However, of these 11, in the majority of cases the experimental binding mode was not uniquely identified, but was present in a cluster of low energy structures that were energetically indistinguishable. These results not only support the presence of a rugged docking energy hypersurface, but also suggest that it may be necessary to consider the possibility of more than one binding conformation during ligand optimization.

Algorithms↗

Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2.

This article describes and reviews our efforts using Hex 3.1 to predict the docking modes of the seven target protein-protein complexes presented in the CAPRI (Critical Assessment of Predicted Interactions) blind docking trial. For each target, the structure of at least one of the docking partners was given in its unbound form, and several of the targets involved large multimeric structures (e.g., Lactobacillus HPr kinase, hemagglutinin, bovine rotavirus VP6). Here we describe several enhancements to our original spherical polar Fourier docking correlation algorithm. For example, a novel surface sphere smothering algorithm is introduced to generate multiple local coordinate systems around the surface of a large receptor molecule, which may be used to define a small number of initial ligand-docking orientations distributed over the receptor surface. High-resolution spherical polar docking correlations are performed over the resulting receptor surface patches, and candidate docking solutions are refined by using a novel soft molecular mechanics energy minimization procedure. Overall, this approach identified two good solutions at rank 5 or less for two of the seven CAPRI complexes. Subsequent analysis of our results shows that Hex 3.1 is able to place good solutions within a list of <or=20 for four of the seven targets. This finding shows that useful in silico protein-protein docking predictions can now be made with increasing confidence, even for very large macromolecular complexes.

Algorithms↗

Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP.

Most current docking methods to identify possible ligands and putative binding sites on a receptor molecule assume a rigid receptor structure to allow virtual screening of large ligand databases. However, binding of a ligand can lead to changes in the receptor protein conformation that are sterically necessary to accommodate a bound ligand. An approach is presented that allows relaxation of the protein conformation in precalculated soft flexible degrees of freedom during ligand-receptor docking. For the immunosuppressant FK506-binding protein FKBP, the soft flexible modes are extracted as principal components of motion from a molecular dynamics simulation. A simple penalty function for deformations in the soft flexible mode is used to limit receptor protein deformations during docking that avoids a costly recalculation of the receptor energy by summing over all receptor atom pairs at each step. Rigid docking of the FK506 ligand binding to an unbound FKBP conformation failed to identify a geometry close to experiment as favorable binding site. In contrast, inclusion of the flexible soft modes during systematic docking runs selected a binding geometry close to experiment as lowest energy conformation. This has been achieved at a modest increase of computational cost compared to rigid docking. The approach could provide a computationally efficient way to approximately account for receptor flexibility during docking of large numbers of putative ligands and putative docking geometries.

Binding Sites↗

A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance.

A thorough evaluation of some of the most advanced docking and scoring methods currently available is described, and guidelines for the choice of an appropriate protocol for docking and virtual screening are defined. The generation of a large and highly curated test set of pharmaceutically relevant protein-ligand complexes with known binding affinities is described, and three highly regarded docking programs (Glide, GOLD, and ICM) are evaluated on the same set with respect to their ability to reproduce crystallographic binding orientations. Glide correctly identified the crystallographic pose within 2.0 A in 61% of the cases, versus 48% for GOLD and 45% for ICM. In general Glide appears to perform most consistently with respect to diversity of binding sites and ligand flexibility, while the performance of ICM and GOLD is more binding site-dependent and it is significantly poorer when binding is predominantly driven by hydrophobic interactions. The results also show that energy minimization and reranking of the top N poses can be an effective means to overcome some of the limitations of a given docking function. The same docking programs are evaluated in conjunction with three different scoring functions for their ability to discriminate actives from inactives in virtual screening. The evaluation, performed on three different systems (HIV-1 protease, IMPDH, and p38 MAP kinase), confirms that the relative performance of different docking and scoring methods is to some extent binding site-dependent. GlideScore appears to be an effective scoring function for database screening, with consistent performance across several types of binding sites, while ChemScore appears to be most useful in sterically demanding sites since it is more forgiving of repulsive interactions. Energy minimization of docked poses can significantly improve the enrichments in systems with sterically demanding binding sites. Overall Glide appears to be a safe general choice for docking, while the choice of the best scoring tool remains to a larger extent system-dependent and should be evaluated on a case-by-case basis.

Algorithms↗

Approaching the CAPRI challenge with an efficient geometry-based docking.

The last 3 rounds (3-5) of CAPRI included a wide range of docking targets. Several targets were especially challenging, since they involved large-scale movements and symmetric rearrangement, while others were based on homology models. We have approached the targets with a variety of geometry-based docking algorithms that include rigid docking, symmetric docking, and flexible docking with symmetry constraints. For all but 1 docking target, we were able to submit at least 1 acceptable quality prediction. Here, we detail for each target the prediction methods used and the specific biological data employed, and supply a retrospective analysis of the results. We highlight the advantages of our techniques, which efficiently exploit the geometric shape complementarity properties of the interaction. These enable them to run only few minutes on a standard PC even for flexible docking, thus proving their scalability toward computational genomic scale experiments. We also outline the major required enhancements, such as the introduction of side-chain position refinement and the introduction of flexibility for both docking partners.

Algorithms↗

Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming.

BACKGROUND: An important prerequisite for computational structure-based drug design is prediction of the structures of ligand-protein complexes that have not yet been experimentally determined by X-ray crystallography or NMR. For this task, docking of rigid ligands is inadequate because it assumes knowledge of the conformation of the bound ligand. Docking of flexible ligands would be desirable, but requires one to search an enormous conformational space. We set out to develop a strategy for flexible docking by combining a simple model of ligand-protein interactions for molecular recognition with an evolutionary programming search technique. RESULTS: We have developed an intermolecular energy function that incorporates steric and hydrogen-bonding terms. The parameters in this function were obtained by docking in three different protein systems. The effectiveness of this method was demonstrated by conformationally flexible docking of the inhibitor AG-1343, a potential new drug against AIDS, into HIV-1 protease. For this molecule, which has nine rotatable bonds, the crystal structure was reproduced within 1.5 A root-mean-square deviation 34 times in 100 simulations, each requiring eight minutes on a Silicon Graphics R4400 workstation. The energy function correctly evaluates the crystal structure as the global energy minimum. CONCLUSIONS: We believe that a solution of the docking problem may be achieved by matching a simple model of molecular recognition with an efficient search procedure. The necessary ingredients of a molecular recognition model include only steric and hydrogen-bond interaction terms. Although these terms are not necessarily sufficient to predict binding affinity, they describe ligand-protein interactions faithfully enough to enable a docking program to predict the structure of the bound ligand. This docking strategy thus provides an important tool for the interdisciplinary field of rational drug design.

Biological Evolution↗

Testing a flexible-receptor docking algorithm in a model binding site.

Sampling receptor flexibility is challenging for database docking. We consider a method that treats multiple flexible regions of the binding site independently, recombining them to generate different discrete conformations. This algorithm scales linearly rather than exponentially with the receptor's degrees of freedom. The method was first evaluated for its ability to identify known ligands of a hydrophobic cavity mutant of T4 lysozyme (L99A). Some 200000 molecules of the Available Chemical Directory (ACD) were docked against an ensemble of cavity conformations. Surprisingly, the enrichment of known ligands from among a much larger number of decoys in the ACD was worse than simply docking to the apo conformation alone. Large decoys, accommodated in the larger cavity conformations sampled in the ensemble, were ranked better than known small ligands. The calculation was redone with an energy correction term that considered the cost of forming the larger cavity conformations. Enrichment improved, as did the balance between high-ranking large and small ligands. In a second retrospective test, the ACD was docked against a conformational ensemble of thymidylate synthase. Compared to docking against individual enzyme conformations, the flexible receptor docking approach improved enrichment of known ligands. Including a receptor conformational energy weighting term improved enrichment further. To test the method prospectively, the ACD database was docked against another cavity mutant of lysozyme (L99A/M102Q). A total of 18 new compounds predicted to bind this polar cavity and to change its conformation were tested experimentally; 14 were found to bind. The bound structures for seven ligands were determined by X-ray crystallography. The predicted geometries of these ligands all corresponded to the observed geometries to within 0.7A RMSD or better. Significant conformational changes of the cavity were observed in all seven complexes. In five structures, part of the observed accommodations were correctly predicted; in two structures, the receptor conformational changes were unanticipated and thus never sampled. These results suggest that although sampling receptor flexibility can lead to novel ligands that would have been missed when docking a rigid structure, it is also important to consider receptor conformational energy.

Algorithms↗

Probing molecular docking in a charged model binding site.

A model binding site was used to investigate charge-charge interactions in molecular docking. This simple site, a small (180A(3)) engineered cavity in cyctochrome c peroxidase (CCP), is negatively charged and completely buried from solvent, allowing us to explore the balance between electrostatic energy and ligand desolvation energy in a system where many of the common approximations in docking do not apply. A database with about 5300 molecules was docked into this cavity. Retrospective testing with known ligands and decoys showed that overall the balance between electrostatic interaction and desolvation energy was captured. More interesting were prospective docking scre"ens that looked for novel ligands, especially those that might reveal problems with the docking and energy methods. Based on screens of the 5300 compound database, both high-scoring and low-scoring molecules were acquired and tested for binding. Out of 16 new, high-scoring compounds tested, 15 were observed to bind. All of these were small heterocyclic cations. Binding constants were measured for a few of these, they ranged between 20microM and 60microM. Crystal structures were determined for ten of these ligands in complex with the protein. The observed ligand geometry corresponded closely to that predicted by docking. Several low-scoring alkyl amino cations were also tested and found to bind. The low docking score of these molecules owed to the relatively high charge density of the charged amino group and the corresponding high desolvation penalty. When the complex structures of those ligands were determined, a bound water molecule was observed interacting with the amino group and a backbone carbonyl group of the cavity. This water molecule mitigates the desolvation penalty and improves the interaction energy relative to that of the "naked" site used in the docking screen. Finally, six low-scoring neutral molecules were also tested, with a view to looking for false negative predictions. Whereas most of these did not bind, two did (phenol and 3-fluorocatechol). Crystal structures for these two ligands in complex with the cavity site suggest reasons for their binding. That these neutral molecules do, in fact bind, contradicts previous results in this site and, along with the alkyl amines, provides instructive false negatives that help identify weaknesses in our scoring functions. Several improvements of these are considered.

Amidines↗

A geometry-based suite of molecular docking processes.

We have developed a geometry-based suite of processes for molecular docking. The suite consists of a molecular surface representation, a docking algorithm, and a surface inter-penetration and contact filter. The surface representation is composed of a sparse set of critical points (with their associated normals) positioned at the face centers of the molecular surface, providing a concise yet representative set. The docking algorithm is based on the Geometric Hashing technique, which indexes the critical points with their normals in a transformation invariant fashion preserving the multi-element geometric constraints. The inter-penetration and surface contact filter features a three-layer scoring system, through which docked models with high contact area and low clashes are funneled. This suite of processes enables a pipelined operation of molecular docking with high efficacy. Accurate and fast docking has been achieved with a rich collection of complexes and unbound molecules, including protein-protein and protein-small molecule associations. An energy evaluation routine assesses the intermolecular interactions of the funneled models obtained from the docking of the bound molecules by pairwise van der Waals and Coulombic potentials. Applications of this routine demonstrate the goodness of the high scoring, geometrically docked conformations of the bound crystal complexes.

Algorithms↗

Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites.

BACKGROUND: Molecular docking seeks to predict the geometry and affinity of the binding of a small molecule to a given protein of known structure. Rigid docking has long been used to screen databases of small molecules, because docking techniques that account for ligand flexibility have either been too slow or have required significant human intervention. Here we describe a docking algorithm, Hammerhead, which is a fast, automated tool to screen for the binding of flexible molecules to protein binding sites. RESULTS: We used Hammerhead to successfully dock a variety of positive control ligands into their cognate proteins. The empirically tuned scoring function of the algorithm predicted binding affinities within 1.3 log units of the known affinities for these ligands. Conformations and alignments close to those determined crystallographically received the highest scores. We screened 80 000 compounds for binding to streptavidin, and biotin was predicted as the top-scoring ligand, with other known ligands included among the highest-scoring dockings. The screen ran in a few days on commonly available hardware. CONCLUSIONS: Hammerhead is suitable for screening large databases of flexible molecules for binding to a protein of known structure. It correctly docks a variety of known flexible ligands, and it spends an average of only a few seconds on each compound during a screen. The approach is completely automated, from the elucidation of protein binding sites, through the docking of molecules, to the final selection of compounds for assay.

Algorithms↗

VRDD: applying virtual reality visualization to protein docking and design.

We have developed an interactive docking program called VRDD. It offers various modes of displaying molecules in an immersive, three-dimensional virtual reality (VR) environment. It allows a user to interactively perform molecular docking aided by automatic docking and side chain conformational search. Binding free energies are computed in real time, and the program enables the user to explore only clash-free orientations of a ligand. VRDD also supplies visual and auditory feedback during docking and side chain search, indicating the levels of atomic overlap and interaction energy. The stunning VR graphics immerse users in the scene and can maximally stimulate their design intuition. We have tested VRDD on three cases with increasing complexity: a nine-residue-long peptide bound to a major histocompatibility complex (MHC) molecule, barstar bound to barnase, and an antibody bound to a hemagglutinin. Without prior knowledge, combinations of hand-docking and automatic refinement led to accurate complex structures for the first two complexes. The third case, for which all automatic docking algorithms failed to identify the correct complex in a previous blind test, also failed for VRDD. Our results show that the combination of VR docking and automatic docking can make unique contributions to molecular modeling.

Antibodies↗

Metal ion dependence, thermodynamics, and kinetics for intramolecular docking of a GAAA tetraloop and receptor connected by a flexible linker.

The GAAA tetraloop-receptor motif is a commonly occurring tertiary interaction in RNA. This motif usually occurs in combination with other tertiary interactions in complex RNA structures. Thus, it is difficult to measure directly the contribution that a single GAAA tetraloop-receptor interaction makes to the folding properties of a RNA. To investigate the kinetics and thermodynamics for the isolated interaction, a GAAA tetraloop domain and receptor domain were connected by a single-stranded A(7) linker. Fluorescence resonance energy transfer (FRET) experiments were used to probe intramolecular docking of the GAAA tetraloop and receptor. Docking was induced using a variety of metal ions, where the charge of the ion was the most important factor in determining the concentration of the ion required to promote docking {[Co(NH(3))(6)(3+)] << [Ca(2+)], [Mg(2+)], [Mn(2+)] << [Na(+)], [K(+)]}. Analysis of metal ion cooperativity yielded Hill coefficients of approximately 2 for Na(+)- or K(+)-dependent docking versus approximately 1 for the divalent ions and Co(NH(3))(6)(3+). Ensemble stopped-flow FRET kinetic measurements yielded an apparent activation energy of 12.7 kcal/mol for GAAA tetraloop-receptor docking. RNA constructs with U(7) and A(14) single-stranded linkers were investigated by single-molecule and ensemble FRET techniques to determine how linker length and composition affect docking. These studies showed that the single-stranded region functions primarily as a flexible tether. Inhibition of docking by oligonucleotides complementary to the linker was also investigated. The influence of flexible versus rigid linkers on GAAA tetraloop-receptor docking is discussed.

Base Sequence↗

Modeling ligand-receptor interaction for some MHC class II HLA-DR4 peptide mimetic inhibitors using several molecular docking and 3D QSAR techniques.

The ligand-receptor interaction between some peptidomimetic inhibitors and a class II MHC peptide presenting molecule, the HLA-DR4 receptor, was modeled using some three-dimensional (3D) quantitative structure-activity relationship (QSAR) methods such as the Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and a pharmacophore building method, the Catalyst program. The structures of these peptidomimetic inhibitors were generated theoretically, and the conformations used in the 3D QSAR studies were defined by docking them into the known structure of HLA-DR4 receptor through the GOLD, GLIDE Rigidly, GLIDE Flexible, and Xscore programs. Some of the parameters used in these docking programs were selected by docking an X-ray ligand into the receptor and comparing the root-means-square difference (RMSD) computed between the coordinates of the X-ray and docked structure. However, the goodness of a docking result for docking a series of peptidomimetic inhibitors into the HLA-DR4 receptor was judged by comparing the Spearman's rank correlation coefficient computed between each docking result and the activity data taken from the literature. The best CoMFA and CoMSIA models were constructed using the aligned structures of the best docking result. The CoMSIA was conducted in a stepwise manner to identify some important molecular features that were further employed in a pharmacophore building process by the Catalyst program. It was found that most inhibitors of the training set were accurately predicted by the best pharmacophore model, the Hypo1 hypothesis constructed. The deviation or conflict found between the actual and predicted activities of some inhibitors of both the training and the test sets were also investigated by mapping the Hypo1 hypothesis onto the corresponding structures of the inhibitors.

Binding Sites↗

"In situ cross-docking" to simultaneously address multiple targets.

In standard docking, every target structure requires separate docking calculations. To overcome this limitation, an approach is presented by which multiple proteins can be addressed simultaneously in a single docking run. This "in situ cross-docking" is built on a grid-based docking method and follows the idea that grids calculated for single binding sites may be joined to one common grid. Docking then allows for a direct selection of the optimal target by the ligand being docked. The approach is technically feasible and can lead to significant time savings over conventional cross-docking.

Algorithms↗

Progressive docking: a hybrid QSAR/docking approach for accelerating in silico high throughput screening.

A combination of protein-ligand docking and ligand-based QSAR approaches has been elaborated, aiming to speed-up the process of virtual screening. In particular, this approach utilizes docking scores generated for already processed compounds to build predictive QSAR models that, in turn, assess hypothetical target binding affinities for yet undocked entries. The "progressive docking" has been tested on drug-like substances from the NCI database that have been docked into several unrelated targets, including human sex hormone binding globulin (SHBG), carbonic anhydrase, corticosteroid-binding globulin, SARS 3C-like protease, and HIV1 reverse transcriptase. We demonstrate that progressive docking can reduce the amount of computations 1.2- to 2.6-fold (when compared to traditional docking), while maintaining 80-99% hit recovery rates. This progressive-docking procedure, therefore, substantially accelerates high throughput screening, especially when using high accuracy (slower) docking approaches and large-sized datasets, and has allowed us to identify several novel potent nonsteroidal SHBG ligands.

Binding Sites↗

Docking-based development of purine-like inhibitors of cyclin-dependent kinase-2.

The cell division cycle is controlled by cyclin-dependent kinases (cdk), which consist of a catalytic subunit (cdk1-cdk8) and a regulatory subunit (cyclin A-H). Purine-like inhibitors of cyclin-dependent kinases have recently been found to be of potential use as anticancer drugs. Rigid and flexible docking techniques were used for analysis of binding mode and design of new inhibitors. X-ray structures of three (ATP, olomoucine, roscovitine) cdk2 complexes were available at the beginning of the study and were used to optimize the docking parameters. The new potential inhibitors were then docked into the cdk2 enzyme, and the enzyme/inhibitor interaction energies were calculated and tested against the assayed activities of cdk1 (37 compounds) and cdk2 (9 compounds). A significant rank correlation between the activity and the rigid docking interaction energy has been found. This implies that (i) the rigid docking can be used as a tool for qualitative prediction of activity and (ii) values obtained by the rigid docking technique into the cdk2 active site can also be used for the prediction of cdk1 activity. While the resulting geometries obtained by the rigid docking are in good agreement with the X-ray data, the flexible docking did not always produce the same inhibitor conformation as that found in the crystal.

CDC2 Protein Kinase↗