Biomedical subjects

Manuel Pastor

Publications and source records attributed to Manuel Pastor.

12 recordsLinked to original sources

PubMed2006

QF2004B, a potential antipsychotic butyrophenone derivative with similar pharmacological properties to clozapine.

The aim of the present work was to characterize a lead compound displaying relevant multi-target interactions, and with an in vivo behavioral profile predictive of atypical antipsychotic activity. Synthesis, molecular modeling and in vitro and in vivo pharmacological studies were carried out for 2-[4-(6-fluorobenzisoxazol-3-yl)piperidinyl]methyl-1,2,3,4-tetrahydro-carbazol-4-one (QF2004B), a conformationally constrained butyrophenone analogue. This compound showed a multi-receptor profile with affinities similar to those of clozapine for serotonin (5-HT2A, 5-HT1A, and 5-HT2C), dopamine (D1, D2, D3 and D4), alpha-adrenergic (alpha1, alpha2), muscarinic (M1, M2) and histamine H1 receptors. In addition, QF2004B mirrored the antipsychotic activity and atypical profile of clozapine in a broad battery of in vivo tests including locomotor activity (ED50 = 1.19 mg/kg), apomorphine-induced stereotypies (ED50 = 0.75 mg/kg), catalepsy (ED50 = 2.13 mg/kg), apomorphine- and DOI (2,5-dimethoxy-4-iodoamphetamine)-induced prepulse inhibition (PPI) tests. These results point to QF2004B as a new lead compound with a relevant multi-receptor interaction profile for the discovery and development of new antipsychotics.

Animals↗

PubMed2005

Anchor-GRIND: filling the gap between standard 3D QSAR and the GRid-INdependent descriptors.

The aim of this work is to present the anchor-GRIND methodology. Anchor-GRIND efficiently combines a priori chemical and biological knowledge about the studied compounds with alignment-independent molecular descriptors derived from molecular interaction fields. Such descriptors are particularly useful for series of ligands sharing a common scaffold but with very diverse substituents. The method uses a specific position of the molecular structure (the "anchor point") to compare the spatial distribution of the molecular interaction fields of the substituents. The descriptors produced are more detailed and specific than the original GRIND while still avoiding the bias introduced by the alignment. Three data sets have been studied to demonstrate the usefulness of the anchor-GRIND methodology for 3D-QSAR modeling. The two first data sets respectively include congeneric series of the hepatitis C virus NS3 protease and of the acetylcholinesterase inhibitors. The third data set discriminates between factor Xa inhibitors of high and low affinity. In all the series presented, the models obtained with the anchor-GRIND are statistically sound and easy to interpret.

Acetylcholinesterase↗

PubMed2004

Comparative analysis of putative agonist-binding modes in the human A1 adenosine receptor.

A recent study reported a model of the human A(1) adenosine receptor and its agonist binding site, proposing two putative binding modes in the same binding site for the natural agonist, adenosine. The present work investigates the flexibility of this binding site by exhaustive exploration with the natural agonist and with three other adenosine derivatives: N6-cyclopentyladenosine (CPA), 2-chloro-N6-cyclopentyladenosine (CCPA), and 5'-N-ethylcarboxamidoadenosine (NECA). Our aim was to find a common binding mode for agonists that would explain the role in the binding process of the different substitutions allowed at the 2, N6, and 5' positions of adenosine. This problem was addressed through docking simulations, molecular dynamics studies, and estimations of the ligand-binding free energy with both the AUTODOCK scoring function and the linear interaction energy (LIE) approach. The results point to a single receptor-binding position that explains the effects of the different chemical modifications on the adenosine derivatives considered here.

Adenosine↗

PubMed2004

Incorporating molecular shape into the alignment-free Grid-Independent Descriptors.

The recently introduced GRid-INdependent Descriptors (GRIND) were designed to provide a suitable description of a series of ligands for 3D-QSAR studies not requiring the spatial superimposition of their structures. Despite the proven usefulness of the method, it was recognized that the original GRIND failed to describe appropriately the shape of the ligand molecules, which in some cases plays a major role in ligand-receptor binding. For this reason, the original descriptors have been enhanced with the addition of a molecular shape description based on the local curvature of the molecular surface. The integration of this description into the GRIND allows the generation of 3D-QSAR models able to identify both favorable and unfavorable shape complementarity in a simple and alignment-independent way. The usefulness of the new GRIND-shape description in 3D-QSAR is illustrated using two structure-activity studies: one performed on a set of xanthine-like antagonists of the A(1) adenosine receptor; another performed on a series of Plasmodium falciparum plasmepsin II inhibitors.

Adenosine A1 Receptor Antagonists↗

PubMed2004

Novel approaches for modeling of the A1 adenosine receptor and its agonist binding site.

The present work describes the building of a human A(1) adenosine receptor (hA(1)AR) model, based on the X-ray crystal structure of bovine rhodopsin, and its use as a basis for the investigation of some important structural characteristics of the receptor. One of the issues investigated was the protonation position of two histidine residues known to influence ligand binding, with protonation of His251 (6.52) in epsilon position and His278 (7.43) in delta position showing the best agreement with experimental evidence. The model was also used to study the position and structural role of water molecules present in the helical bundle. Finally, the binding site location and the ligand docking were investigated using an objective strategy. A suitable site for the binding of the ribose moiety of adenosine was first postulated and further confirmed by means of a novel chemometric strategy based on GRIND descriptors. Using this position as an anchor point, the binding of adenosine was studied by docking and molecular dynamics simulations obtaining two putative binding positions in good agreement with experimental data.

Adenosine↗

PubMed2003

Surface descriptors for protein-ligand affinity prediction.

Molecular descriptors calculated by the VolSurf program have been extensively used to model pharmacokinetic properties, e.g., passive permeability through the gastrointestinal tract or through the blood-brain barrier. These descriptors quantify steric, hydrophobic, and hydrogen bond interactions between model compounds and different environments. Since these interactions are the same as those involved in the ligand-receptor binding, VolSurf descriptors could potentially be relevant in modeling this process as well. We obtained a significant model (r(2) = 0.85, q(2) = 0.75) using VolSurf descriptors derived from the ligand, the protein, and the ligand-protein complex for a diverse set of 38 structures previously used in the VALIDATE (ref 23) training set. Furthermore, a statistically significant model (r(2) = 0.94, q(2) = 0.89) was obtained using the same type of descriptors for a homogeneous set of glycogen phosphorylase inhibitors (ref 25). Using the VolSurf computational framework, both ligand-receptor binding and the ligand's pharmacokinetic behavior can be modeled simultaneously during the preclinical aspects of drug discovery.

Ligands↗

PubMed2003

Conformationally constrained butyrophenones as new pharmacological tools to study 5-HT 2A and 5-HT 2C receptor behaviours.

This study presents new pharmacological and molecular modelling studies on a recently described series of conformationally constrained butyrophenones. Alignment-free three-dimensional quantitative structure-activity relationship models developed on the basis of GRid Independent descriptors and partial least squares regression analysis, allow feasible predictions of activity of new compounds and reveal structural requirements for optimal affinity, particularly in the case of the 5-HT(2A) receptor. The requirements for the 5-HT(2A) affinity consist in a precise distance between hydrogen bond donor (protonated amino group) and hydrogen bond acceptor groups, as well as an optimal distance between the protonated amino group and the farthest extreme of the compounds. Another significant result has been the characterisation of two structurally similar compounds as interesting pharmacological tools (1-[(4-Oxo-4,5,6,7-tetrahydrobenzo[b]furan-5-yl)ethyl]-4-(6-fluorobenzisoxazol-3-yl)piperidine and 1-[(4-Oxo-4,5,6,7-tetrahydrobenzo[b]furan-6-yl)methyl]-4-(6-fluorobenzisoxazol-3-yl)piperidine). In spite of their structural similarity, the first compound shows clearly higher affinity for the 5-HT(2C) receptor (about 100 fold) and higher Meltzer ratio (1.17 vs. 0.99) than the second. Moreover, the first compound inhibits arachidonic acid release in a biphasic concentration-dependent way in functional experiments at the 5-HT(2A) receptor and it acts as inverse agonist at the 5-HT(2C) receptor, behaviours that are not shown by the second compound.

Animals↗

PubMed2003

Use of alignment-free molecular descriptors in diversity analysis and optimal sampling of molecular libraries.

The selection of a sample of diverse compounds is a common strategy for exploring large molecular libraries. However, the success of such approach depends on the selection of relevant molecular descriptors and the use of appropriate sampling methods. In the context of pharmaceutical research, the molecular descriptors should be based on physicochemical properties related with the pharmacological behaviour of the compounds. In this sense, the alignment-free GRIND and VolSurf molecular descriptors are promising candidates since they have been successfully used in the modelling of both pharmacodynamic and pharmacokinetic properties of drugs. This work describes the use of such descriptors in the diversity sampling of a library of primary amines and compares the results with those obtained in a previous study that used quantum-mechanical descriptors. As in the previous work, principal component (PC) analysis was applied to reduce the dimensionality and remove redundant information of the original descriptors, and the compounds were sampled on the basis of k-means clustering on the space of the selected PCs. The results of the present study show that VolSurf and GRIND provide similar quality sampling regarding global features of the molecules such as hydrophilicity, however the topology of the compounds is considered differently. The similarity between particular compounds strongly depends on the original descriptors used. However all the sample selections done in the PC space after k-means clustering provide the same apparent diversity in comparison to the whole dataset. The results indicate that there is no best set of descriptors on a diversity basis. The selection of descriptors must be based on the drug features to be investigated.

Combinatorial Chemistry Techniques↗

PubMed2002

Suitability of molecular descriptors for database mining. A comparative analysis.

Database mining methods rely on the molecular descriptors used to characterize a structural database. In the present investigation, five different types of descriptors (log P, UNITY fingerprints, ISIS keys, VolSurf, and GRIND) are applied to characterize various databases (n = 1007, 100, and 229) comprising drugs almost exclusively. The validity of the descriptors is comparatively analyzed via principal component analysis and its hierarchical variant, consensus principal component analysis. Both pharmacodynamic and pharmacokinetic aspects of database mining are treated. For pharmacodynamic aspects, clustering behavior achieved with the different descriptors is tested on the chemically homogeneous beta-blockers, benzodiazepines, and penicillins and on the chemically more diverse class I antiarrhythmics. The following ranking is observed: UNITY fingerprints > ISIS keys and GRIND > VolSurf > log P. Regarding information content, the CPCA superweight plot indicates similarity between fingerprints and ISIS keys as well as between VolSurf and log P, while GRIND differs from all the remaining descriptors. Solubility data and blood/brain barrier penetrating behavior serve as test cases for pharmacokinetic aspects. Comparison of the descriptors applied to these data reveals that VolSurf has the most realistic and consistent behavior, GRIND shows intermediate behavior, while UNITY fingerprints and ISIS keys are not well suited for pharmacokinetic profiling. From this comparative analysis, we conclude that VolSurf descriptors exhibit particular advantages in treating pharmacokinetic aspects; UNITY fingerprints, ISIS keys, and GRIND descriptors are of special value for tackling pharmacodynamic aspects of database mining. The parameter log P is of limited applicability in database mining because of rather poor reliability and lack of completeness of data.

Computing Methodologies↗

PubMed2002

GBR compounds and mepyramines as cocaine abuse therapeutics: chemometric studies on selectivity using grid independent descriptors (GRIND).

Cocaine is one of the most widely abused drugs in the industrial world. Substantial evidence has accumulated that the dopamine transporter (DAT) is a key target for cocaine regarding its reinforcing effects. This work describes the application of chemometric methods to a data set of 54 N(1)-benzhydryl-oxy-alkyl-N(4)-phenyl-alk(en)yl-piperazines (GBR compounds) and chemically related mepyramines as putative candidates in cocaine abuse therapy. The aim of the study is to gain insight into the structural requirements that determine the affinity of the data set molecules to the DAT and the serotonin transporter (SERT) as well as their inhibitory potency on dopamine uptake. The compounds in the dataset are described using the recently developed GRID independent descriptors (GRIND), which allow one to obtain fast three-dimensional quantitative structure-activity relationship models without the need of aligning and superimposing the structures; the results are interpreted in a convenient pharmacophoric-like fashion. In the first part of the work, the selectivity of the database molecules for DAT binding vs dopamine reuptake inhibition is investigated. In the second part, the selectivity of the compounds for DAT binding vs SERT binding is studied. In both cases, significant models are obtained, which define the structural features responsible for the respective selectivity profiles. Moreover, the information has potential interest for the design of new derivatives with improved selectivity.

Carrier Proteins↗

PubMed2002

Distant collaboration in drug discovery: the LINK3D project.

The work describes the development of novel software supporting synchronous distant collaboration between scientists involved in drug discovery and development projects. The program allows to visualize and share data as well as to interact in real time using standard intranets and Internet resources. Direct visualization of 2D and 3D molecular structures is supported and original tools for facilitating remote discussion have been integrated. The software is multiplatform (MS-Windows, SGI-IRIX, Linux), allowing for a seamless integration of heterogeneous working environments. The project aims to support collaboration both within and between academic and industrial institutions. Since confidentiality is very important in some scenarios, special attention has been paid to security aspects. The article presents the research carried out to gather the requirements of collaborative software in the field of drug discovery and development and describes the features of the first fully functional prototype obtained. Real-world testing activities carried out on this prototype in order to guarantee its adequacy in diverse environments are also described and discussed.

Computer Graphics↗

PubMed2002

Environmental justice and regional inequality in southern California: implications for future research.

Environmental justice offers researchers new insights into the juncture of social inequality and public health and provides a framework for policy discussions on the impact of discrimination on the environmental health of diverse communities in the United States. Yet, causally linking the presence of potentially hazardous facilities or environmental pollution with adverse health effects is difficult, particularly in situations in which diverse populations are exposed to complex chemical mixtures. A community-academic research collaborative in southern California sought to address some of these methodological challenges by conducting environmental justice research that makes use of recent advances in air emissions inventories and air exposure modeling data. Results from several of our studies indicate that communities of color bear a disproportionate burden in the location of treatment, storage, and disposal facilities and Toxic Release Inventory facilities. Longitudinal analysis further suggests that facility siting in communities of color, not market-based "minority move-in," accounts for these disparities. The collaborative also investigated the health risk implications of outdoor air toxics exposures from mobile and stationary sources and found that race plays an explanatory role in predicting cancer risk distributions among populations in the region, even after controlling for other socioeconomic and demographic indicators. Although it is unclear whether study results from southern California can be meaningfully generalized to other regions in the United States, they do have implications for approaching future research in the realm of environmental justice. The authors propose a political economy and social inequality framework to guide future research that could better elucidate the origins of environmental inequality and reasons for its persistence.

Air Pollutants↗