Biomedical subjects

Robert D Clark

Publications and source records attributed to Robert D Clark.

15 recordsLinked to original sources

PubMed2005

N-substituted piperazines abused by humans mimic the molecular mechanism of 3,4-methylenedioxymethamphetamine (MDMA, or 'Ecstasy').

3,4-Methylenedioxymethamphetamine (MDMA, or 'Ecstasy') is an illicit drug that stimulates the release of serotonin (5-HT) and dopamine (DA) from neurons. Recent evidence reveals that drug users are ingesting piperazine analogs, like 1-benzylpiperazine (BZP, or 'A2') and 1-(m-trifluoromethylphenyl)piperazine (TFMPP, or 'Molly'), to mimic psychoactive effects of MDMA. In the present study, we compared the neurochemistry of MDMA, BZP, and TFMPP in rats. The effects of MDMA, BZP, and TFMPP on transporter-mediated efflux of [3H]5-HT and [3H]MPP+ (DA transporter substrate) were determined in synaptosomes. The effects of drugs on extracellular levels of 5-HT and DA were examined using in vivo microdialysis in conscious rats. MDMA evoked transporter-mediated release of [3H]5-HT and [3H]MPP+. BZP released [3H]MPP+, whereas TFMPP was a selective releaser of [3H]5-HT. MDMA (1-3 mg/kg, i.v.) increased dialysate 5-HT and DA in a dose-related fashion, with actions on 5-HT being predominant. BZP (3-10 mg/kg, i.v.) elevated dialysate DA and 5-HT, while TFMPP (3-10 mg/kg, i.v.) elevated 5-HT. Administration of BZP plus TFMPP at a 1:1 ratio (BZP/TFMPP) produced parallel increases in dialysate 5-HT and DA; a 3 mg/kg dose of BZP/TFMPP mirrored the effects of MDMA. At a 10 mg/kg dose, BZP/TFMPP increased dialysate DA more than the summed effects of each drug alone, and some rats developed seizures. Our results show that BZP/TFMPP and MDMA share the ability to evoke monoamine release, but dangerous drug-drug synergism may occur when piperazines are coadministered at high doses.

Animals↗

PubMed2004

"Lead hopping". Validation of topomer similarity as a superior predictor of similar biological activities.

Two extensive studies quantifying the ability of topomer shape similarity to forecast a variety of biological similarities are described. In a prospective trial of "lead hopping", using topomer similarity for virtual screening and queries from the patent literature, biological assays of 308 selected compounds (representing 0.03% of those available, per assay type) yielded 11 successful "lead hops" in the 13 assays attempted. The hit rate averaged over all assays was 39% ("activity"defined as inhibition > or =20% at 10 microM), significantly greater than an unexpectedly high negative control hit rate of 15%. The average "Tanimoto 2D fingerprint similarity" between query and "lead hop" structures (0.36) was little more than the Tanimoto similarity between random drug-like structures. Topomer shape and Tanimoto 2D fingerprint similarities were also compared retrospectively, in their tendencies to concentrate together potential and actual drugs reported to belong to the same "activity class", for twenty classes. Among the most similar 3% of structures (corresponding to "> or =0.85 Tanimoto" for these structures), an average of 62% of the topomer similar selection possessed a near neighbor belonging to the same activity class, roughly a one-third superiority over the "Tanimoto > or = 0.85" selection containing 48% actives in avoiding false positives. Conversely, the least similar 75% of structures contained 0.3% actives for topomer similarity vs 1.0% actives for Tanimoto 2D fingerprint similarity, a 3-fold superiority for topomers in avoiding false negatives.

Computing Methodologies↗

PubMed2004

Modelling in vitro hepatotoxicity using molecular interaction fields and SIMCA.

There is currently a great deal of interest in creating computational tools for predicting the pharmacological properties of drug development candidates, ranging from physicochemical properties such as pK(a) and solubility to more complex biological properties such as oral bioavailability and toxicity. The limiting factor in many cases is a shortage of good data from which to construct training sets. In other cases, large amounts of data are available, but they use surrogate end-points or are comprised of compounds very different from those usually encountered in drug discovery and development. In such cases large training sets and global models are not necessarily better than local models based on smaller data sets. Such considerations make it as important to examine the available data carefully so as to avoid over-interpretation of the models obtained as it is to minimise errors in prediction per se. The kinds of complications likely to be encountered for in vitro hepatotoxicity modelling are discussed in general terms and illustrated in particular by SIMCA analysis of data obtained from assays of cultured hepatocytes for a large, structurally diverse data set and a smaller, much more focussed one.

Adenosine Triphosphate↗

PubMed2004

Alignment of three-dimensional molecules using an image recognition algorithm.

This paper describes a novel approach, based on image recognition in two dimensions, for the atom-based alignment of two rigid molecules in three dimensions. The atoms are characterised by their partial charges and their positions relative to the remaining atoms in the molecule. Based on this information, a cost of matching a pair of atoms, one from each molecule, is assigned to all possible pairs. A preliminary set of intermolecular atom equivalences that minimises the total atom matching cost is then determined using an algorithm for solving the linear assignment problem. Several geometric heuristics are described that aim to reduce the number of atom equivalences that are inconsistent with the 3D structures. Those that remain are used to calculate an alignment transformation that achieves an optimal superposition of atoms that have a similar local geometry and partial charge. This alignment is then refined by calculating a new set of equivalences consisting of atom pairs that are approximately overlaid, irrespective of partial charge. A range of examples is provided to demonstrate the efficiency and effectiveness of the method.

Algorithms↗

PubMed2004

Effects of "Legal X" piperazine analogs on dopamine and serotonin release in rat brain.

3,4-Methylenedioxymethamphetamine (MDMA) is a popular illicit drug that evokes transporter-mediated release of serotonin (5-HT) and dopamine (DA) from nerve cells. Recently, drug users have ingested combinations of the piperazine analogs, 1-benzylpiperazine (BZP) and 1-(m-trifluoromethylphenyl)piperazine (TFMPP), in an attempt to mimic the subjective effects of MDMA. In the present study, we compared neurochemical effects of MDMA, BZP, and TFMPP in rat brain. The ability of MDMA, BZP, and TFMPP to stimulate efflux of [3H]5-HT and [3H]MPP+ (a DA transporter substrate) was determined in vitro using release assays in synaptosomes. The ability of these drugs to increase extracellular 5-HT and DA in vivo was assessed using intracranial microdialysis in nucleus accumbens. MDMA stimulated transporter-mediated release of 5-HT (EC50 = 58 nM) and MPP+ (EC50 = 119 nM). BZP was a selective releaser of MPP+ (EC50 = 175 nM), whereas TFMPP was a selective releaser of 5-HT (EC50 = 121 nM). MDMA injections (1 and 3 mg/kg, i.v.) increased dialysate 5-HT and DA in a dose-related manner, but actions on 5-HT were predominant. BZP (3 and 10 mg/kg, i.v.) elevated dialysate DA and 5-HT, while TFMPP (3 and 10 mg/kg, i.v.) elevated only 5-HT. The coadministration of BZP plus TFMPP (BZP/TFMPP) produced marked elevations in extracellular 5-HT and DA that mirrored the effects of MDMA. At the high dose of BZP/TFMPP (10 mg/kg, i.v.), the rise in dialysate DA exceeded the summed effects of the drugs alone. Our results support the hypothesis that the BZP/TFMPP combination mimics the neurochemical mechanism of MDMA, providing a basis for recreational use of these agents. Additionally, the findings suggest possible drug-drug synergism when piperazine drugs are coadministered at high doses.

Animals↗

PubMed2003

(+)-Fenfluramine and its major metabolite, (+)-norfenfluramine, are potent substrates for norepinephrine transporters.

(+/-)-Fenfluramine is an amphetamine analog that was once widely prescribed as an appetite suppressant. Although (+/-)-fenfluramine is no longer clinically available, the mechanisms underlying its anorectic properties are still of interest. Upon peripheral administration, stereoisomers of (+/-)-fenfluramine are N-deethylated to form the metabolites, (+)- and (-)-norfenfluramine. It is well accepted that isomers of (+/-)-fenfluramine and (+/-)-norfenfluramine interact with 5-hydroxytryptamine (serotonin, 5-HT) transporters to release 5-HT from neurons. However, the effects of these drugs on other monoamine transporters are not well characterized. In this study, we examined the interaction of stereoisomers of (+/-)-fenfluramine and (+/-)-norfenfluramine with transporters for 5-HT, norepinephrine (NE), and dopamine (DA). Results from in vitro assays confirmed these drugs are potent substrates for 5-HT transporters: (+)-fenfluramine, (-)-fenfluramine, (+)-norfenfluramine, and (-)-norfenfluramine released [3H]5-HT from synaptosomes with EC50 values of 52, 147, 59, and 287 nM, respectively. Importantly, (+)-fenfluramine and (+)-norfenfluramine released [3H]NE with EC50 values of 302 and 73 nM. Results from in vivo microdialysis experiments showed that intravenous injection of (+)-norfenfluramine elevates extracellular levels of 5-HT, NE, and DA in rat frontal cortex. The effects of (+)-norfenfluramine on NE and DA were antagonized by pretreatment with the NE uptake blocker nisoxetine. In summary, administration of fenfluramines can increase synaptic levels of 5-HT, NE, and DA in the cortex, and (+)-norfenfluramine likely contributes to these effects. Release of NE and DA evoked by (+)-norfenfluramine is at least partly mediated via NE transporters. Our results emphasize the potential involvement of noradrenergic mechanisms in the actions of fenfluramines.

Animals↗

PubMed2003

Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA.

We have developed a method that combines molecular interaction fields with soft independent modeling of class analogy (SIMCA) to predict pharmacokinetic drug properties. Several additional considerations to those made in traditional QSAR are required in order to develop a successful QSPR strategy that is capable of accommodating the many complex factors that contribute to key pharmacokinetic properties such as ADME (absorption, distribution, metabolism, and excretion) and toxicology. An accurate prediction of oral bioavailability, for example, requires that absorption and first-pass hepatic elimination both be taken into consideration. To accomplish this, general properties of molecules must be related to their solubility and ability to penetrate biological membranes, and specific features must be related to their particular metabolic and toxicological profiles. Here we describe a method, which is applicable to structurally diverse data sets while utilizing as much detailed structural information as possible. We address the issue of the molecular alignment of a structurally diverse set of compounds using idiotropic field orientation (IFO), a generalization of inertial field orientation. We have developed a second flavor of this method, which directly incorporates electrostatics into the molecular alignment. Both variations of IFO produce a characteristic orientation for each structure and the corresponding molecular fields can then be analyzed using SIMCA. Models are presented for human intestinal absorption, blood-brain barrier penetration and bioavailability to demonstrate ways in which this tool can be used early in the drug development process to identify leads likely to exhibit poor pharmacokinetic behavior in pre-clinical studies, and we have explored the influence of conformation and molecular field type on the statistical properties of the models obtained.

Biological Transport, Active↗

PubMed2003

Molecular design and bioavailability.

A "snapshot" of current medicinal chemistry work on bioavailability is drawn from issues of J. Med. Chem. covering the time period between September 2001 and September 2002. An exhaustive compilation of reported absolute oral bioavailability (F) values for this period is included, covering 34 structural series and 107 distinct compounds, with data for multiple species in many cases. This is supplemented with a discussion of more qualitative oral bioavailability results, and with illustrative examples addressing clearance, prodrug design, and blood/brain barrier penetration problems. Papers discussing predictions pertaining to one or another aspect of bioavailability are also discussed, and some thoughts on future directions of work on in silico prediction in this area are presented.

Administration, Oral↗

PubMed2002

Consensus scoring for ligand/protein interactions.

Several different functions have been put forward for evaluating the energetics of ligand binding to proteins. Those employed in the DOCK, GOLD and FlexX docking programs have been especially widely used, particularly in connection with virtual high-throughput screening (vHTS) projects. Until recently, such evaluation functions were usually considered only in conjunction with the docking programs that relied on them. In such studies, the evaluation function in question actually fills two distinct roles: it serves as the objective function being optimized (fitness function), but is also the scoring function used to compare the candidate docking configurations generated by the program. We have used descriptions available in the open literature to create free-standing scoring functions based on those used in DOCK and GOLD, and have implemented the more recently formulated PMF [J. Med. Chem. 42 (1999) 791] scoring function as well. The performance of these functions was examined individually for each of several data sets for which both crystal structures and affinities are available, as was the performance of the FlexX scoring function. Various ways of combining individual scores into a consensus score (CScore) were also considered. The individual and consensus scores were also used to try to pick out configurations most similar to those found in crystal structures from among a set of candidate configurations produced by FlexX docking runs. We find that the reliability and interpretability of results can be improved by combining results from all four functions into a CScore.

Crystallography, X-Ray↗

PubMedDate not supplied

Statistical variation in progressive scrambling.

The two methods most often used to evaluate the robustness and predictivity of partial least squares (PLS) models are cross-validation and response randomization. Both methods may be overly optimistic for data sets that contain redundant observations, however. The kinds of perturbation analysis widely used for evaluating model stability in the context of ordinary least squares regression are only applicable when the descriptors are independent of each other and errors are independent and normally distributed; neither assumption holds for QSAR in general and for PLS in particular. Progressive scrambling is a novel, nonparametric approach to perturbing models in the response space in a way that does not disturb the underlying covariance structure of the data. Here, we introduce adjustments for two of the characteristic values produced by a progressive scrambling analysis - the deprecated predictivity (Q*2s) and standard error of prediction (SDEPs*) - that correct for the effect of introduced perturbation. We also explore the statistical behavior of the adjusted values (Q*2(0) and SDEP0*) and the sensitivity to perturbation (dq2/dryy'2). It is shown that the three statistics are all robust for stable PLS models, in terms of the stochastic component of their determination and of their variation due to sampling effects involved in training set selection.

Data Interpretation, Statistical↗

PubMedDate not supplied

OptiDock: virtual HTS of combinatorial libraries by efficient sampling of binding modes in product space.

Products from combinatorial libraries generally share a common core structure that can be exploited to improve the efficiency of virtual high-throughput screening (vHTS). In general, it is more efficient to find a method that scales with the total number of reagents (Sigma growth) rather with the number of products (Pi growth). The OptiDock methodology described herein entails selecting a diverse but representative subset of compounds that span the structural space encompassed by the full library. These compounds are docked individually using the FlexX program (Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. J. Mol. Biol. 1995, 251, 470-489) to define distinct docking modes in terms of reference placements for combinatorial core atoms. Thereafter, substituents in R-cores (consisting of the core structure substituted at a single variation site) are docked, keeping the core atoms fixed at the coordinates dictated by each reference placement. Interaction energies are calculated for each docked R-core with respect to the target protein, and energies for whole compounds are calculated by finding the reference core placement for which the sum of corresponding R-core energies is most negative. The use of diverse whole compounds to define binding modes is a key advantage of the protocol over other combinatorial docking programs. As a result, OptiDock returns better-scoring conformers than does serially applied FlexX. OptiDock is also better able to find a viable docked pose for each library member than are other combinatorial approaches.

Binding Sites↗

PubMedDate not supplied

Predicting pK(a) by molecular tree structured fingerprints and PLS.

This is the second phase of the pK(a) predictor published earlier (J. Chem. Inf. Comput. Sci. 2002, 42, 796-805). The algorithm has been extended by treating specific chemical classes separately and generating tree-structured molecular descriptors tailored to each individual class. A training set consisting of 625 acids and 412 bases covers the major areas of chemical space involved in protonation and deprotonation. The models obtained demonstrate excellent statistics (SE = 0.41 for acids and 0.30 for bases) and yielded accurate predictions on an external test set. The quality and statistical performance of pK(a) prediction has been improved considerably over the initial implementation of the method.

Algorithms↗

PubMedDate not supplied

Efficient generation, storage, and manipulation of fully flexible pharmacophore multiplets and their use in 3-D similarity searching.

Pharmacophore triplets and quartets have been used by many groups in recent years, primarily as a tool for molecular diversity analysis. In most cases, slow processing speeds and the very large size of the bitsets generated have forced researchers to compromise in terms of how such multiplets were stored, manipulated, and compared, e.g., by using simple unions to represent multiplets for sets of molecules. Here we report using bitmaps in place of bitsets to reduce storage demands and to improve processing speed. Here, a bitset is taken to mean a fully enumerated string of zeros and ones, from which a compressed bitmap is obtained by replacing uniform blocks ("runs") of digits in the bitset with a pair of values identifying the content and length of the block (run-length encoding compression). High-resolution multiplets involving four features are enabled by using 64 bit executables to create and manipulate bitmaps, which "connect" to the 32 bit executables used for database access and feature identification via an extensible mark-up language (XML) data stream. The encoding system used supports simple pairs, triplets, and quartets; multiplets in which a privileged substructure is used as an anchor point; and augmented multiplets in which an additional vertex is added to represent a contingent feature such as a hydrogen bond extension point linked to a complementary feature (e.g., a donor or an acceptor atom) in a base pair or triplet. It can readily be extended to larger, more complex multiplets as well. Database searching is one particular potential application for this technology. Consensus bitmaps built up from active ligands identified in preliminary screening can be used to generate hypothesis bitmaps, a process which includes allowance for differential weighting to allow greater emphasis to be placed on bits arising from multiplets expected to be particularly discriminating. Such hypothesis bitmaps are shown to be useful queries for database searching, successfully retrieving active compounds across a range of structural classes from a corporate database. The current implementation allows multiconformer bitmaps to be obtained from pregenerated conformations or by random perturbation on-the-fly. The latter application involves random sampling of the full range of conformations not precluded by steric clashes, which limits the usefulness of classical fingerprint similarity measures. A new measure of similarity, The Stochastic Cosine, is introduced here to address this need. This new similarity measure uses the average number of bits common to independently drawn conformer sets to normalize the cosine coefficient. Its use frees the user from having to ensure strict comparability of starting conformations and having to use fixed torsional increments, thereby allowing fully flexible characterization of pharmacophoric patterns.

Adrenergic beta-Antagonists↗

PubMedDate not supplied

OptDesign: extending optimizable k-dissimilarity selection to combinatorial library design.

Optimizable k-dissimilarity (OptiSim) selection entails drawing a series of subsamples of size k from a population and choosing the "best" candidate from each such subsample for inclusion in the selection set. By varying the size of the subsample, one can control the balance between representativeness and diversity in the selection set obtained. In the original formulation, a uniform random sampling from among valid candidates was used to draw the subsamples from a single target population. Here we describe in detail two key modifications that serve to extend the OptiSim methodology to vector selection for interdependent variables, specifically as applied to the design of combinatorial sublibraries. The first modification involves pivoting between variables: subsamples are drawn from each reagent pool in turn, with the viability of each candidate being evaluated in isolation as well as in terms of the products it will produce from complementary reagents already selected. The filters applied may be static or dynamic in nature, with molecular weight and hydrophobicity being examples of the former and structural diversity with respect to reagents already selected being an example of the latter. The second key modification is adding the ability to bias the selection of candidate reagents for inclusion in the subsamples. Taken together, these modifications support the efficient generation of multiblock and other sparse matrix designs that are both representative and diverse, and for which "backfilling" of designs edited to remove undesirable reagents or products is straightforward. The method is intrinsically fast and efficient, since enumeration of the full combinatorial is not required- only those candidates actually considered for inclusion need be evaluated. Moreover, because the subsample selection step is separate from the diversity-based selection of the "best" candidate, incorporating such bias in favor of a competing criterion such as low price provides a "natural," nonparametric mechanism for generating designs that are likely to be "good" in a double-objective, Pareto sense.

Journal Article↗

PubMedDate not supplied

Boosted leave-many-out cross-validation: the effect of training and test set diversity on PLS statistics.

It is becoming increasingly common in quantitative structure/activity relationship (QSAR) analyses to use external test sets to evaluate the likely stability and predictivity of the models obtained. In some cases, such as those involving variable selection, an internal test set--i.e., a cross-validation set--is also used. Care is sometimes taken to ensure that the subsets used exhibit response and/or property distributions similar to those of the data set as a whole, but more often the individual observations are simply assigned 'at random.' In the special case of MLR without variable selection, it can be analytically demonstrated that this strategy is inferior to others. Most particularly, D-optimal design performs better if the form of the regression equation is known and the variables involved are well behaved. This report introduces an alternative, non-parametric approach termed 'boosted leave-many-out' (boosted LMO) cross-validation. In this method, relatively small training sets are chosen by applying optimizable k-dissimilarity selection (OptiSim) using a small subsample size (k = 4, in this case), with the unselected observations being reserved as a test set for the corresponding reduced model. Predictive errors for the full model are then estimated by aggregating results over several such analyses. The countervailing effects of training and test set size, diversity, and representativeness on PLS model statistics are described for CoMFA analysis of a large data set of COX2 inhibitors.

Algorithms↗