Biomedical subjects

Gabriele Cruciani

Publications and source records attributed to Gabriele Cruciani.

At least 19 recordsLinked to original sources

PubMed2006

Calcium channel antagonists discovered by a multidisciplinary approach.

A multidisciplinary project has led to the discovery of novel, structurally diverse, L-type calcium entry blockers (CEBs). The absolute configuration of a recently reported CEB has been determined by vibrational circular dichroism spectroscopy, to assign the stereospecificity of the ligand-channel interaction. Thereafter, a virtual screening procedure was performed with the aim of identifying novel chemotypes for CEBs, starting from a database of purchasable compounds; 340,000 molecules were screened in silico in order to prioritize structures of interest for bioscreening. As a result, 20 compounds were tested in vitro, and functional and binding assays revealed several hits with promising behavior as CEBs.

Animals↗

PubMed2005

MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist.

Identification of metabolic biotransformations can significantly affect the drug discovery process. Since bioavailability, activity, toxicity, distribution, and final elimination all depend on metabolic biotransformations, it would be extremely advantageous if this information could be produced early in the discovery phase. Once obtained, this information can help chemists to judge whether a potential candidate should be eliminated from the pipeline or modified to improve chemical stability or safety of new compounds. The use of in silico methods to predict the site of metabolism in phase I cytochrome-mediated reactions is a starting point in any metabolic pathway prediction. This paper presents a new method, specifically designed for chemists, that provides the cytochrome involved and the site of metabolism for any human cytochrome P450 (CYP) mediated reaction acting on new substrates. The methodology can be applied automatically to all the cytochromes for which 3D structure is known and can be used by chemists to detect positions that should be protected in order to avoid metabolic degradation or to check the suitability of a new scaffold or prodrug. The fully automated procedure is also a valuable new tool in early ADME-Tox assays (absorption, distribution, metabolism, and excretion toxicity assays), where drug safety and metabolic profile patterns must be evaluated as soon, and as early, as possible.

Amphetamines↗

PubMed2005

Predictive models for hERG potassium channel blockers.

We report here a general method for the prediction of hERG potassium channel blockers using computational models generated from correlation analyses of a large dataset and pharmacophore-based GRIND descriptors. These 3D-QSAR models are compared favorably with other traditional and chemometric based HQSAR methods.

Anti-Arrhythmia Agents↗

PubMed2005

Pharmacophore, drug metabolism, and pharmacokinetics models on non-peptide AT1, AT2, and AT1/AT2 angiotensin II receptor antagonists.

About 20 non-peptide angiotensin II receptor antagonists are in various stages of clinical development. Different modeling approaches were used to predict the pharmacophoric requirements for AT(1) (angiotensin II receptor subtype 1) affinity. However, to our knowledge, none was used to predict both the selectivity toward AT(1) and AT(2) (angiotensin II receptor subtype 2) receptor subtypes. In this paper, partial least squares discriminant analysis is applied to derive the chemical features guiding AT(1) and AT(2) selectivity or mixed AT(1)/AT(2) receptor binding. The method can be used to modulate AT(1) versus AT(2) selectivity. Concerns that unopposed stimulation of the AT(2) receptor might produce adverse effects initiated a search for new balanced antagonists. Moreover, it can serve as a fast filtering procedure in database searches. Finally, some relevant pharmacokinetics and metabolic properties of the database of 53 compounds are calculated using the VolSurf and MetaSite software to allow the simultaneous characterization of pharmacodynamic and pharmacokinetics properties of the chemical space of angiotensin II receptor antagonists.

Angiotensin II Type 1 Receptor Blockers↗

PubMed2005

A pharmacophore hypothesis for P-glycoprotein substrate recognition using GRIND-based 3D-QSAR.

Trying to understand the complex interactions that substrates and inhibitors have with the efflux transporter P-glycoprotein has been the subject of various publications. In this work, we have confined our study to substrates by picking a diverse set of 129 compounds based on the efflux ratios from Caco-2 permeability measurements. These compounds were then evaluated for P-glycoprotein inhibition using a calcein-AM assay. The subsequent data was used in a 3D-QSAR analysis using GRIND pharmacophore-based and physicochemical descriptors. Pharmacophore-based descriptors produced a much more robust model than the one obtained from physicochemical-based descriptors. This supports the process proposed by Seelig and co-workers previously published whereby the substrate enters the membrane as the first step and is then recognized by P-glycoprotein in a second step. The strong correlation, highlighted by PLS statistical analysis, between pharmacophoric descriptors and inhibition values suggests that substrate interaction, with perhaps the mouth of the protein or another binding site, plays a key role in the efflux process, yielding a model in which diffusion across the membrane is less important than substrate-protein interaction. One pharmacophore emerged from the analysis of the model. We pose that the recognition elements, at least determined by the molecules used in this study, are two hydrophobic groups 16.5 A apart and two hydrogen-bond-acceptor groups 11.5 A apart and that the dimensions of the molecule also plays a role in its recognition as a substrate.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

PubMed2005

Predicting human serum albumin affinity of interleukin-8 (CXCL8) inhibitors by 3D-QSPR approach.

A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure-property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K(i)) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.

Anti-Inflammatory Agents, Non-Steroidal↗

PubMed2005

A new class of selective myocardial calcium channel modulators. 2. Role of the acetal chain in oxadiazol-3-one derivatives.

In the framework of the continuing interest of this research group in the use of 8-aryl-8-hydroxy-8H-[1,4]thiazino[3,4-c][1,2,4]oxadiazol-3-ones (1) as calcium entry blockers, a number of acetals were synthesized and assayed "in vitro". All of them are structurally related to diltiazem and pyrrolobenzothiazines. The effect on the biological profile was measured by functional assays for a wide variety of acetal residues: saturated linear and branched chains, short and long unsaturated E and/or Z chains as well as benzyl and methylcyclohexyl residues. From selective assays on the most active derivative (5b) (EC(50) = 0.04 microM), which is 20 times more active than diltiazem (EC(50) = 0.79 microM), a muscarinic or adenosinic mechanism of action was excluded. A 3D QSAR model was obtained and validated with homologous literature data, and a virtual receptor scheme was derived for the unknown binding site. The following pharmacophoric features favorably affect the potency: one positively charged center, three lipophilic groups, and two hydrogen-bonding acceptor groups.

Acetals↗

PubMed2004

Hydrogen bonding interactions of covalently bonded fluorine atoms: from crystallographic data to a new angular function in the GRID force field.

Through the years the GRID force field has been tuned to fit experimental observations in crystal structures. This paper describes the determination of the hydrogen bonding pattern for organic fluorines based on an exhaustive inspection of the Protein Data Bank. All the PDB complexes, whose protein structures have cocrystallized fluorine-containing ligands, were examined and geometrically inspected. By applying statistics, the hydrogen bonding geometry was described as a distribution function of the angle at the fluorine: a new specific angular function was consequently defined and inserted in the program GRID to estimate the effect of fluorine hydrogen bonds on the ligand-protein binding. All the fluorine-containing ligands collected from the PDB were docked within their corresponding protein binding sites: introducing the fluorine hydrogen bonding contribution improves the results of the docking experiments in terms of accuracy and ranking.

Binding Sites↗

PubMed2004

GRIND/ALMOND investigations on CysLT1 receptor antagonists of the quinolinyl(bridged)aryl type.

One of the current routes in developing antiasthmatics is CysLT(1) receptor antagonism. For a training set of 54 CysLT(1) receptor antagonists of the quinolinyl(bridged)aryl type we developed chemometric QSAR models applying GRID independent descriptors (=GRIND). PLS analysis resulted in a two-component model explaining 67% of the variance for CysLT(1) receptor binding (r2=0.67, SDEC = 0.47, q2=0.54). GRIND variables 11-50 and 22-55 are responsible for high-affinity binding; variable 11-62 is detrimental. The predictivity of the above chemometric model is tested with a set of 69 CysLT(1) receptor antagonists, exhibiting varying chemical similarity to the training set. Nearly 50% of the test set are quite well predicted. The quality of prediction coincides in part with chemical subclassification: phenylene bridged compounds are quite well predicted; for structures with bridging heterocycles predictions are rather poor. For explaining the outlier behavior, a PLS discriminant analysis including the training set and the strongest outliers of the test set was performed. The scores plot of discriminant PLS shows an almost complete separation between the two subsets. A PLS coefficients plot explains which GRIND variables are important for the discrimination between the training set and the outliers of the test set.

Asthma↗

PubMed2004

Chemometric studies on the bactericidal activity of quinolones via an extended VolSurf approach.

An extended VolSurf approach, that additionally includes SHAPE descriptors, was applied to a dataset of 55 quinolones. Bactericidal activity was measured at Bayer AG, Germany, for Gram-negative (Escherichia coli and Pseudomonas aeruginosa) and Gram-positive bacteria (Staphylococcus aureus and Enterococcus faecalis). Chemometric analysis was first approached via a classical VolSurf approach. The following descriptors were found most important: bactericidal activity particularly increases with high values of the best volume (BV11(OH2)) and the minimum energy (Emin1(OH2)) of the water probe, high values of the integy moment (ID(DRY)) of the lipophilic probe, and high values of the hydrophilic region (W(O)) of the hydrogen bond acceptor probe. Best volume (BV31(OH2)) of the water probe and best volume (BV12(DRY)) and lipophilic regions (D(DRY)) of the lipophilic probe as well as H-bonding capacity derived with the CO probe (HB(O)) are inversely related to activity. PLS analysis yields a five-component model with an r(2) of 0.83 and a q(2) of 0.43 after variable selection via fractional factorial design (FFD). Chemometric modeling could be improved by including newly derived SHAPE descriptors, which were merged with the VolSurf descriptors and subjected to PLS analysis. The global model of this extended VolSurf approach is optimal with two components and exhibits a significantly improved statistical quality; a marginally reduced r(2) (0.75 versus 0.83) is more than compensated by a highly improved predictivity with a q(2) of 0.63 versus 0.43. To prove model quality, external prediction of seven test set quinolones was performed. The precise prediction of all test set molecules nicely demonstrates the robustness and statistical significance of the obtained chemometric model using the extended VolSurf approach.

Anti-Bacterial Agents↗

PubMed2004

Conformer- and alignment-independent model for predicting structurally diverse competitive CYP2C9 inhibitors.

A conformer- and alignment-independent three-dimensional structure-activity relationship (3D-QSAR) model has been derived that is based on flexible molecular interaction fields calculated in GRID and the subsequent description of these fields by use of alignment-independent descriptors derived in ALMOND. The training set consisted of 22 diverse and flexible competitive inhibitors of the drug-metabolizing enzyme CYP2C9 and generated a model with r(2) of 0.81 and q(2) of 0.62. The predicitive capacity of the model was externally evaluated with a test set of 12 competitive inhibitors and 11 out of 12 were predicted within 0.5 log unit. The most relevant points of interaction in the model correlated well to the amino acids involved in CYP2C9-substrate/inhibitor binding in the active site of a CYP2C9 homology model, further validating the mechanistic sense of our model. This approach offers the possibility to derive predicitve 3D-QSAR models without the need for an alignment rule for chemically diverse ligands and in the absence of target protein crystal structure information.

Amino Acids↗

PubMed2004

Structure-based rationalization of antitumor drugs mechanism of action by a MIF approach.

Structural patterns for antitumor drugs, evidenced by means of a molecular interaction field (MIF) approach using grid independent descriptors (GRIND), resembled closely those of a previous independent pharmacological classification based on their antitumor mechanism of action. For topoisomerase II inhibitors, antimitotic agents and DNA antimetabolites, systematic structural patterns were evidenced by MIF and the structural features of "outliers" in these classes corresponded to peculiar pharmacological mechanisms of action supported by literature evidences. Alkylating agents and DNA/RNA antimetabolites, interacting with a large variety of targets by different molecular mechanisms, did not exhibit clustering in the structure-based MIF approach. Moreover MIFS were able to point out similarities between drugs which, in spite of apparent dramatic differences in chemical structure, exhibit the same pharmacological behaviour.

Antineoplastic Agents↗

PubMed2004

GRIND-derived pharmacophore model for a series of alpha-tropanyl derivative ligands of the sigma-2 receptor.

A pharmacophore model for the sigma-2 receptor was derived using GRIND (GRid INdependent Descriptors) descriptors arising from a 3D-level procedure whose main prerogative is that it does not require ligand alignment. PLS models for sigma-2 affinity (sigma-2 model: r2=0.83, q2=0.63) and sigma-1/sigma-2 selectivity (r2=0.72, q2=0.46) were derived using a series of alpha-tropanyl derivatives. The models provide pictures of the virtual receptor site (VRS) significant enough to attain a qualitative pharmacophoric representation of the sigma receptor. They give the internal geometrical relationships within two hydrophobic areas (hydrophobic-1 and -2) and a H-bond donor receptor region with which ligands establish non-covalent bonds.

Computer Simulation↗

PubMed2003

Predicting drug metabolism: a site of metabolism prediction tool applied to the cytochrome P450 2C9.

The aim of the present study is to develop a method for predicting the site at which molecules will be metabolized by CYP 2C9 (cytochrome P450 2C9) using a previously reported protein homology model of the enzyme. Such a method would be of great help in designing new compounds with a better pharmacokinetic profile, or in designing prodrugs where the compound needs to be metabolized in order to become active. The methodology is based on a comparison between alignment-independent descriptors derived from GRID Molecular Interaction Fields for the CYP 2C9 active site, and a distance-based representation of the substrate. The predicted site of metabolism is reported as a ranking list of all the hydrogen atoms of each substrate molecule. Eighty-seven CYP 2C9-catalyzed oxidative reactions reported in the literature have been analyzed. In more than 90% of these cases, the hydrogen atom ranked at the first, second, or third position was the experimentally reported site of oxidation.

Animals↗

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↗

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

Structural differences of matrix metalloproteinases with potential implications for inhibitor selectivity examined by the GRID/CPCA approach.

The matrix metalloproteinases (MMPs) are a family of proteolytic enzymes, which have been the focus of a lot of research in recent years because of their involvement in various disease conditions. In this study, structures of 10 enzymes (MMP1, MMP2, MMP3, MMP7, MMP8, MMP9, MMP12, MMP13, MMP14, and MMP20) were examined with the intention of highlighting regions that could be potential sites for obtaining selectivity. For this purpose, the GRID/CPCA approach as implemented in GOLPE was used. Counterions were included to take into account the different electrostatic properties of the proteins, and the GRID calculations were performed, allowing the protein side chains to move in response to interaction with the probes. In the search for selectivity, the MMPs are known to be a very difficult case because the enzymes of this family are very similar. The well-known differences in the S1' pocket were observed, but in addition, the pockets S3 and S2 called for attention. This is an observation that emphasizes the need for design of inhibitors exploiting the unprimed side of the active site, if possible, in combination with the S1' site. Despite small differences, a rational usage of the findings described in this work should make it possible to use a combination of the features of the individual enzyme pockets, making most of the MMP enzymes possible targets for selective inhibition. The results suggest the possibility of distinguishing between 8 of the 10 enzymes by this approach.

Amino Acid Sequence↗

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↗