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Biomedical subjects

Robin Taylor

Publications and source records attributed to Robin Taylor.

15 recordsLinked to original sources
PubMed2005

Modeling water molecules in protein-ligand docking using GOLD.

We implemented a novel approach to score water mediation and displacement in the protein-ligand docking program GOLD. The method allows water molecules to switch on and off and to rotate around their three principal axes. A constant penalty, sigma(p), representing the loss of rigid-body entropy, is added for water molecules that are switched on, hence rewarding water displacement. We tested the methodology in an extensive validation study. First, sigma(p) is optimized against a training set of 58 protein-ligand complexes. For this training set, our algorithm correctly predicts water mediation/displacement in approximately 92% of the cases. We observed small improvements in the quality of the predicted binding modes for water-mediated complexes. In the second part of this work, an entirely independent set of 225 complexes is used. For this test set, our algorithm correctly predicts water mediation/displacement in approximately 93% of the cases. Improvements in binding mode quality were observed for individual water-mediated complexes.

Algorithms↗
PubMed2005

Librarians, crystal structures and drug design.

There are now 355,000 published crystal structures of organic and metal-organic compounds, all of which have been acquired, validated, chemically annotated and organised for searching in the Cambridge Structural Database (CSD). The CSD is used in rational drug design and is beginning to answer important questions relevant to the formulation of pharmaceutical active ingredients. The value and credibility of this research are ultimately dependent on the accuracy and completeness of the underlying crystal-structure data.

Crystallization↗
PubMed2005

The synthesis of silica nanospheres doped with polyoxometalates.

The hetero-polyoxometalate (POM) Na13[Eu(SiMoW10O39)2] displayed enhanced luminescence when coordinated to compounds with a common amine functionality. The POM was then doped into silica spheres and was found to be confined to the particle core when added with an amine-based polymer.

Microscopy, Electron↗
PubMed2005

Nucleotide passivated cadmium sulfide quantum dots.

Semiconductor quantum dots are finding numerous applications in biological systems; in this paper, we report the simple in situ preparation of nucleotide capped cadmium sulfide (CdS) nanoparticles and investigate the interaction of the capping agent with the nanoparticle surface.

Cadmium Compounds↗
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↗
PubMed2004

Research applications of the Cambridge Structural Database (CSD).

Crystal structure data are of fundamental importance in a wide spectrum of scientific activities. This tutorial review summarises the principal application areas, so far, for the data from more than 300,000 crystal structures of small organic and metal-organic compounds that are stored in the Cambridge Structural Database (CSD). Direct use of the accumulated data is valuable in establishing standard molecular dimensions, determining conformational preferences and in the study of intermolecular interactions, all of which are crucial in structural chemistry and rational drug design. More recently, information derived from the CSD has been used to construct two dynamic libraries of structural knowledge: Mogul, which stores intramolecular information, and IsoStar, which stores information about intermolecular interactions. These electronic libraries provide information "at the touch of a button". In their turn, the libraries also serve as sources of structural knowledge for applications software that address specific problems in small-molecule and biological chemistry.

Journal Article↗
PubMed2004

Combined use of physicochemical data and small-molecule crystallographic contact propensities to predict interactions in protein binding sites.

Knowledge-based methods are a good alternative to force-field-based methods for the analysis of sites of interaction in protein binding cavities. Both the Protein Data Bank (PDB) and the Cambridge Structural Database (CSD) offer a good amount of data on non-covalent interactions. Although different from protein-derived data, small-molecule crystal data from the CSD are worth looking at as they provide a much more abundant and diverse set of intermolecular contacts. CSD data, when properly corrected by use of octanol-water pi values, can be used to predict the type of ligand chemical group most likely to occupy a given position within a protein binding site. Comparison with observed positions of ligand groups shows that the success rates of these predictions vary from 23% to 84%. Often, the group predicted to be most preferred at a given position is similar but not identical to the observed ligand group; if these are considered successes, prediction success rates range from 71% to 94%. Using PDB data, the corresponding rates are 16% to 79%, and 61% to 96%. Specificity of prediction of NH groups is somewhat better when using PDB interaction data, but results of prediction of hydrophobic groups seem worse than those obtained with CSD data. We have analysed the importance of data selection by applying different filters to eliminate unwanted interactions from our knowledge-base. The presence of certain types of interactions can be undesirable if they are unrepresentative of biological situations (contact to solvent molecules in small-molecule crystal structures, secondary crystallographic contacts) or if they are likely to add noise to the data without conveying much new information (long-distance contacts, sparsely-populated data sets). The elimination of solvent contacts was found to have no effect on the prediction of ligand groups in our test set. Both secondary-contact filtering and noise filtering were found to have a clear beneficial effect on predictive ability.

Binding Sites↗
PubMed2004

Generation of multiple pharmacophore hypotheses using multiobjective optimisation techniques.

Pharmacophore methods provide a way of establishing a structure activity relationship for a series of known active ligands. Often, there are several plausible hypotheses that could explain the same set of ligands and, in such cases, it is important that the chemist is presented with alternatives that can be tested with different synthetic compounds. Existing pharmacophore methods involve either generating an ensemble of conformers and considering each conformer of each ligand in turn or exploring conformational space on-the-fly. The ensemble methods tend to produce a large number of hypotheses and require considerable effort to analyse the results, whereas methods that vary conformation on-the-fly typically generate a single solution that represents one possible hypothesis, even though several might exist. We describe a new method for generating multiple pharmacophore hypotheses with full conformational flexibility being explored on-the-fly. The method is based on multiobjective evolutionary algorithm techniques and is designed to search for an ensemble of diverse yet plausible overlays which can then be presented to the chemist for further investigation.

Algorithms↗
PubMed2004

Olanzapine penetration into brain is greater in transgenic Abcb1a P-glycoprotein-deficient mice than FVB1 (wild-type) animals.

The transmembrane energy-dependent efflux transporter P-glycoprotein (P-gp) limits a range of drugs from penetrating cells and deposits them into the extracellular space. P-gp is highly expressed in several normal tissues, including the luminal surface of capillary endothelial cells in the brain of humans. In this study, we tested whether olanzapine distribution to tissues highly expressing P-gp or devoid of this transporter was similar in Abcb1a (-/-) mice lacking P-gp and control animals. At 1 h following the intraperitoneal injection of 2.5 microg olanzapine/g mouse, olanzapine concentrations were statistically and significantly higher in brain (three-fold), liver (2.6-fold), and kidney (1.8-fold) of Abcb1a (-/-) mice than those of the control FVB Abcb1a (+/+) mice, and not statistically different in plasma, spleen, or penile tissue. Similar differences were also found for the ratios of organ:plasma and organ:spleen between the two groups. This is the first report that the presence of the Abcb1a gene is an important factor controlling brain access to olanzapine. The finding that the brain penetration of olanzapine is limited by P-gp implies that the highly prevalent functional polymorphisms of ABCB1 in humans may be a factor contributing to variability in dose requirements for this antipsychotic drug.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2002

A new test set for validating predictions of protein-ligand interaction.

We present a large test set of protein-ligand complexes for the purpose of validating algorithms that rely on the prediction of protein-ligand interactions. The set consists of 305 complexes with protonation states assigned by manual inspection. The following checks have been carried out to identify unsuitable entries in this set: (1) assessing the involvement of crystallographically related protein units in ligand binding; (2) identification of bad clashes between protein side chains and ligand; and (3) assessment of structural errors, and/or inconsistency of ligand placement with crystal structure electron density. In addition, the set has been pruned to assure diversity in terms of protein-ligand structures, and subsets are supplied for different protein-structure resolution ranges. A classification of the set by protein type is available. As an illustration, validation results are shown for GOLD and SuperStar. GOLD is a program that performs flexible protein-ligand docking, and SuperStar is used for the prediction of favorable interaction sites in proteins. The new CCDC/Astex test set is freely available to the scientific community (http://www.ccdc.cam.ac.uk).

Algorithms↗
PubMed2002

New software for searching the Cambridge Structural Database and visualizing crystal structures.

Two new programs have been developed for searching the Cambridge Structural Database (CSD) and visualizing database entries: ConQuest and Mercury. The former is a new search interface to the CSD, the latter is a high-performance crystal-structure visualizer with extensive facilities for exploring networks of intermolecular contacts. Particular emphasis has been placed on making the programs as intuitive as possible. Both ConQuest and Mercury run under Windows and various types of Unix, including Linux.

Journal Article↗
PubMed2002

Life-science applications of the Cambridge Structural Database.

Several studies show that the molecular geometries and intermolecular interactions observed in small-molecule crystal structures are relevant to the modelling of in vivo situations, although the influence of crystal packing is sometimes important and should always be borne in mind. Torsional distributions derived from the Cambridge Structural Database (CSD) can be used to map out potential-energy surfaces and thereby help identify experimentally validated conformational minima of molecules with several rotatable bonds. The use of crystallographic data in this way is complementary to in vacuo theoretical calculations since it gives insights into conformational preferences in condensed-phase situations. Crystallographic data also underpin many molecular-fragment libraries and programs for generating three-dimensional models from two-dimensional chemical structures. The modelling of ligand binding to metalloenzymes is assisted by information in the CSD on preferred coordination numbers and geometries. CSD data on intermolecular interactions are useful in structure-based inhibitor design both in indicating how probable a protein-ligand interaction is and what its geometry is likely to be. They can also be used to guide searches for bioisosteric replacements. Crystallographically derived information has contributed to many life-science software applications, including programs for locating binding 'hot spots' on proteins, docking ligands into enzyme active sites, de novo ligand design, molecular superposition and three-dimensional QSAR. Overall, crystallographic data in general, and the CSD in particular, are very significant tools for the rational design of biologically active molecules.

Crystallography, X-Ray↗
PubMedDate not supplied

Retrieval of crystallographically-derived molecular geometry information.

The crystallographically determined bond length, valence angle, and torsion angle information in the Cambridge Structural Database (CSD) has many uses. However, accessing it by means of conventional substructure searching requires nontrivial user intervention. In consequence, these valuable data have been underutilized and have not been directly accessible to client applications. The situation has been remedied by development of a new program (Mogul) for automated retrieval of molecular geometry data from the CSD. The program uses a system of keys to encode the chemical environments of fragments (bonds, valence angles, and acyclic torsions) from CSD structures. Fragments with identical keys are deemed to be chemically identical and are grouped together, and the distribution of the appropriate geometrical parameter (bond length, valence angle, or torsion angle) is computed and stored. Use of a search tree indexed on key values, together with a novel similarity calculation, then enables the distribution matching any given query fragment (or the distributions most closely matching, if an adequate exact match is unavailable) to be found easily and with no user intervention. Validation experiments indicate that, with rare exceptions, search results afford precise and unbiased estimates of molecular geometrical preferences. Such estimates may be used, for example, to validate the geometries of libraries of modeled molecules or of newly determined crystal structures or to assist structure solution from low-resolution (e.g. powder diffraction) X-ray data.

Journal Article↗
PubMedDate not supplied

Factors affecting d-block metal-ligand bond lengths: toward an automated library of molecular geometry for metal complexes.

Metal-ligand (M-L) bond lengths for a range of ligands (carboxylates, chlorides, pyridines, water, tertiary phosphines, and alkenes) and a variety of metals have been retrieved from the Cambridge Structural Database, CSD. Analysis of the factors which affect M-L bond lengths (for example, ligand coordination mode, oxidation state, metal coordination number and geometry, spin and Jahn-Teller effects, and ligand trans to M-L bond) shows that it is generally possible to subdivide the M-L data sets systematically to obtain better defined, unimodal, bond length distributions with means and sample standard deviations (SSDs) which reflect the nature of the bond in question. Typically, the SSDs for the M-L data sets can be reduced to 0.04-0.05 A by these methods. This work is an extension to tables of bond lengths in organometallic compounds and coordination complexes published in 1989. The importance of the factors which affect M-L bond lengths for particular metal-ligand groups are discussed. From the case studies reported, an algorithm is proposed by which compilation of a library of molecular geometry for metal complexes may be automated. The points that need to be considered to produce such a molecular library from the data stored in the CSD are discussed. The development of such a library would allow users to retrieve chemically well-defined geometric data rapidly and accurately. This should be of use, for example, to crystallographers and molecular modelers.

Journal Article↗