Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P06889 (Mol)
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The recently proposed MS-WHIM indices, a set of theoretical descriptors containing information about size, shape and electrostatic distribution of a molecule, have been further investigated. The main objectives of this work were: (i) to confirm the descriptive power of MS-WHIM in modelling specific biological interactions, (ii) to analyse the dependence of MS-WHIM on the type of atomic charges used for computing electrostatic potential and (iii) to compare the performances of MS-WHIM with those provided by other global 3D molecular descriptors. The spatial autocorrelation of atomic and molecular surface properties were selected for comparison purposes. WHIM-based and autocorrelation-based vectors were calculated for two molecular sets from the literature, namely a series of 18 HIV-1 reverse transcriptase inhibitors and a set of 36 sulphonamide endothelin inhibitors. PLS was adopted to derive statistical predictive models that were validated by means of cross-validation. The reported results confirmed that MS-WHIM indices are able to provide meaningful statistical correlations with biological activity. MS-WHIM descriptors are sensitive to the type of partial atomic charges applied and improved models were obtained using more accurate charges. Moreover for both the datasets, MS-WHIM results, in terms of fitting and predictive power of PLS models, were superior to those from autocorrelation. Finally, the strengths/weaknesses of global 3D-QSAR descriptors over local CoMFA-like methods, as well as the main differences between WHIM-based and autocorrelation-based vectors, are discussed.
J Comput Aided Mol Des 2000 Mar
PMID:Global 3D-QSAR methods: MS-WHIM and autocorrelation. 1075 83

Poor intestinal permeability of drugs constitutes a major bottleneck in the successful development of candidate drugs. Fast computational tools to help in designing compounds with increased probability of oral absorption are required, since both medicinal and combinatorial chemists are under pressure to consider increasing numbers of virtual and existing compounds. The QSAR paradigm for drug absorption is expressed as a function of molecular size, hydrogen-bonding capacity, and lipophilicity. A nonlinear PLS model that can be achieved with minimal computational efforts is described. The QSAR model correlates human intestinal absorption (%HIA) data, and apparent Caco-2 cell permeability data, to parameters calculated from molecular structures. Two properties were found to be relevant for absorption predictions, namely H-bonding capacity, and hydrophobic transferability. The parsimony principle was applied in several aspects: single conformers were used to compute molecular surface areas; the definitions of "polar" and "nonpolar" surfaces were done in a simplistic fashion; simple and fast 2D descriptors were used to estimate other properties; the 1 PLS component model was selected. These choices result in a minimalistic model for oral absorption. The use of both %HIA and Caco-2 permeability data was found to stabilize and improve the model. This QSAR model can serve as a simple, quantitative extension of the "rule of five" scheme (Lipinski, C.A., Lombardo, F., Dominy, B.W., and Feeney, P.J. Adv. Drug Deliv. Rev. 1997, 23, 3-25), in a manner that can prove beneficial to the drug discovery process.
J Mol Graph Model
PMID:Toward minimalistic modeling of oral drug absorption. 1084 Jun 86

Different classes of Peripheral-type Benzodiazepine Receptor (PBR) ligands were examined and common structural elements were detected and used to develop a rational binding model based on energetically allowed ligand conformations. Two lipophilic regions and one electrostatic interaction site are essential features for high affinity ligand binding, while a further lipophilic region plays an important modulator role. A comparative molecular field analysis, performed over 130 PBR ligands by means of the GRID/GOLPE methodology, led to a PLS model with both high fitting and predictive values (r2 = 0.898, Q2 = 0.761). The outcome from the 3D QSAR model and the GRID interaction fields computed on the putative endogenous PBR ligands DBI (Diazepam Binding Inhibitor) and TTN (Tetracontatetraneuropeptide) was used to identify the amino acids most probably involved in PBR binding. Three amino acids, bearing lipophilic side chains, were detected in DBI (Phe49, Leu47 and Met46) and in TTN (Phe33, Leu31 and Met30) as likely residues underlying receptor binding. Moreover, a qualitative comparison of the molecular electrostatic potentials of DBI, TTN and selected synthetic ligands indicated also similar electronic properties. Convergent results from the modeling studies of synthetic and endogenous ligands suggest a common binding mode to PBRs. This may help the rational design of new high affinity PBR ligands.
J Comput Aided Mol Des 2000 Nov
PMID:Development of a unique 3D interaction model of endogenous and synthetic peripheral benzodiazepine receptor ligands. 1113 68

We showed previously that soluble low-molecular-mass tumor-associated antigens (TAA) could suppress chemically-induced tumorigenesis. In this study, we analyzed the mechanism of those findings. Studies were performed on the spleen and mammary gland tumors obtained from the following groups of rats: i) control rats treated with dimethyl-benz(alpha)antracene (DMBA), ii) vaccinated and carcinogen-treated rats with non regressed tumors, iii) vaccinated and carcinogen-treated rats with regressed tumors. Different zones of the spleen and tumors and their cellular content (Ki67+ and CD8+ cells, and macrophages) were analyzed morphometrically and immunohistochemically. Reaction of the spleen to vaccination was manifested in a significant increase in all areas of the white pulp and in a decrease in the size of the red pulp. The total number of cells in the white pulp (germinal center and PALS) and in the marginal zone was significantly higher in the spleen of rats with regressed tumors. The number of Ki67+ cells decreased significantly in both groups of vaccinated rats, but most prominently in the marginal zone and the red pulp in rats with regressed tumors. An increased number of CD8+ lymphocytes and macrophages was also seen in the red pulp. Different areas of the tumors (peripheral vs. inside at depth) showed different responses to vaccination and this difference was related to conditions of carcinogenesis, i.e. non-regressed vs. regressed tumors. In regressed tumors, all parameters studied were easily distinguishable in both areas of the tumors, while in non-regressed tumors, a marked distinction was seen only at their periphery. In regressed tumors, a negative correlation was seen at depth tumors between the number of Ki67+ cells and the number of CD8+ lymphocytes (r=-0.48). The findings indicated a strict antitumor effect of vaccination with the soluble low-molecular-mass TAA, which prevents the development of insufficiency of the immune system when an intensive immune reaction takes place.
Int J Mol Med 2001 Feb
PMID:Effects of the soluble low-molecular-mass proteins on spleen activity and cellular composition of infiltrates in rat mammary gland tumors. 1117 29

This study describes the generation of a three-dimensional quantitative structure activity relationship (3D-QSAR) model for 29 structurally diverse, competitive CYP2C9 inhibitors defined experimentally from an initial data set of 73 compounds. In parallel, a homology model for CYP2C9 using the rabbit CYP2C5 coordinates was built. For molecules with a known interaction mode with CYP2C9, this homology model, in combination with the docking program GOLD, was used to select conformers to use in the 3D-QSAR analysis. The remaining molecules were docked, and the GRID interaction energies for all conformers proposed by GOLD were calculated. This was followed by a principal component analysis (PCA) of the GRID energies for all conformers of all compounds. Based on the similarity in the PCA plot to the inhibitors with a known interaction mode, the conformer to be used in the 3D-QSAR analysis was selected. The compounds were randomly divided into two groups, the training data set (n = 21) to build the model and the external validation set (n = 8). The PLS (partial least-squares) analysis of the interaction energies against the K(i) values generated a model with r(2) = 0.947 and a cross-validation of q(2) = 0.730. The model was able to predict the entire external data set within 0.5 log units of the experimental K(i) values. The amino acids in the active site showed complementary features to the grid interaction energies in the 3D-QSAR model and were also in agreement with mutagenesis studies.
Mol Pharmacol 2001 Apr
PMID:Competitive CYP2C9 inhibitors: enzyme inhibition studies, protein homology modeling, and three-dimensional quantitative structure-activity relationship analysis. 1125 37

Antiviral quinolones are promising compounds in the search for new therapeutically effective agents for the treatment of AIDS. To rationalize the SAR for this new interesting class of anti-HIV derivatives, we performed a 3D-QSAR study on a library of 101 6-fluoro and 6-desfluoroquinolones, taken either from the literature or synthesized by us. The chemometric procedure involved a fully semiempirical minimization of the molecular structures by the AMSOL program, which takes into account the solvatation effect, and their 3D characterization by the VolSurf/GRID program. The QSAR analysis, based on PCA and PLS methods, shows the key structural features responsible for the antiviral activity.
J Comput Aided Mol Des 2001 Mar
PMID:QSAR study and VolSurf characterization of anti-HIV quinolone library. 1128 75

Hydrogen bonding has been identified as an important parameter for describing drug permeability. Recently, we derived models for predicting intestinal permeability using the hydrogen bonding descriptors polar surface area (PSA) and number of hydrogen bond donors (HBD), and a lipophilicity descriptor [J. Med. Chem. 41 (1998) 4939]. We have now explored other types of hydrogen bonding descriptors to see if these improve the models. Both an experimental hydrogen bonding descriptor, deltalogP, and calculated descriptors, based either on semiempirical calculations or on experimentally derived hydrogen bond strength values of small molecules, were used. Principal component analyses (PCA) were performed in order to characterize the different parameters, using both a drug data set and a data set of small non-drug-like molecules for which deltalogP-values had been published. For a set of diverse drug molecules, for which human intestinal permeability data was available, a PLS-analysis was performed to study the correlation of permeability to the different hydrogen bonding parameters. No correlation could be identified between deltalogP and human intestinal permeability in this data set. However, the combination of a hydrogen bond donor descriptor, a general hydrogen bonding descriptor and a lipophilicity descriptor enabled the prediction of human intestinal permeability, whereas hydrogen bond acceptor descriptors were found to be less important. The obtained models successfully predicted the intestinal permeability values of two external data sets.
J Mol Graph Model 2003 Jan
PMID:Hydrogen bonding descriptors in the prediction of human in vivo intestinal permeability. 1247 27

This study describes the use of alignment-independent descriptors for obtaining qualitative and quantitative predictions of the competitive inhibition of CYP2C9 on a serie of highly structurally diverse compounds. This was accomplished by calculating alignment independent descriptors in ALMOND. These GRid INdependent Descriptors (GRIND) represent the most important GRID-interactions as a function of the distance instead of the actual position of each grid-point. The experimental data was determined under uniform conditions. The inhibitor data set consists of 35 structurally diverse competitive stereospecific inhibitors of the cytochrome P450 2C9 and the non -inhibitor data set of 46 compounds. In a PLS discriminant analysis 21 inhibitors and 21 non-inhibitors (1 and 0 as activities) were analyzed using the ALMOND program obtaining a model with an r2 of 0.74 and a cross-validation value (q2) of 0.64. The model was externally validated with 39 compounds (14 inhibitors/25 non-inhibitors). 74% of the compounds were correctly predicted and an additional 13% was assigned to a borderline cluster. Thereafter, a model for quantitative predictions was generated by a PLS analysis of the GRIND descriptors using the experimental Ki-value for 21 of the competitive inhibitors (r2 = 0.77, q2 = 0.60). The model was externally validated using 12 compounds and predicted 11 out of 12 of the Ki-values within 0.5 log units. The discriminant model will be useful in screening for CYP2C9 inhibitors from large compound collections. The 3D-QSAR model will be used during lead optimization to avoid chemistry that result in inhibition of CYP2C9.
J Comput Aided Mol Des 2002 Jul
PMID:Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors. 1251 Aug 79

Multivariate PCA- and PLS-models involving many variables are often difficult to interpret, because plots and lists of loadings, coefficients, VIPs, etc, rapidly become messy and hard to overview. There may then be a strong temptation to eliminate variables to obtain a smaller data set. Such a reduction of variables, however, often removes information and makes the modelling efforts less reliable. Model interpretation may be misleading and predictive power may deteriorate. A better alternative is usually to partition the variables into blocks of logically related variables and apply hierarchical data analysis. Such blocked data may be analyzed by PCA and PLS. This modelling forms the base-level of the hierarchical modelling set-up. On the base-level in-depth information is extracted for the different blocks. The score vectors formed on the base-level, here called 'super variables', may be linked together in new matrices on the top-level. On the top-level superficial relationships between the X- and the Y-data are investigated. In this paper the basic principles of hierarchical modelling by means of PCA and PLS are reviewed. One objective of the paper is to disseminate this concept to a broader QSAR audience. The hierarchical methods are used to analyze a set of 10 haloalkanes for which K = 30 chemical descriptors and M = 255 biological responses have been gathered. Due to the complexity of the biological data, they are sub-divided in four blocks. All the modelling steps on the base-level and the top-level are reported and the final QSAR model is interpreted thoroughly.
J Comput Aided Mol Des 2002 Oct
PMID:Megavariate analysis of hierarchical QSAR data. 1265 May 89

Estimation of bioavailability and toxicity at the very beginning of the drug development process is one of the big challenges in drug discovery. Most of the processes involved in ADME are driven by rather unspecific interactions between drugs and biological macromolecules. Within the past decade, drug transport pumps such as P-glycoprotein (Pgp) have gained increasing interest in the early ADME profiling process. Due to the high structural diversity of ligands of Pgp, traditional QSAR methods were only successful within analogous series of compounds. We used an approach based on similarity calculations to predict Pgp-inhibitory activity of a series of propafenone analogues. This SIBAR approach is based on selection of a highly diverse reference compound set and calculation of similarity values to these reference compounds. The similarity values (denoted as SIBAR descriptors) are then used for PLS analysis. Our results show, that for a set of 131 propafenone type compounds, models with good predictivity were obtained both in cross validation procedures and with a 31-compound external test set. Thus, these new descriptors might be a versatile tool for generation of predictive ADME models.
J Comput Aided Mol Des 2002 Nov
PMID:Similarity based SAR (SIBAR) as tool for early ADME profiling. 1282 90


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