Resistive intrarenal index: myth or reality?

In renal diagnosis, the B-mode ultrasound is used to provide an accurate study of the renal morphology, whereas the colour and power Doppler are of strategic importance in providing qualitative and quantitative information about the renal vasculature, which can also be obtained through the assessment of the resistive index (RI). To date, this is one of the most sensitive parameters in the study of kidney diseases and allows us to quantify the changes in renal plasma flow. If a proper Doppler ultrasound examination is carried out and a critical analysis of the values obtained is performed, the RI measurement at the interlobar artery level has been suggested in the differential diagnosis between nephropathies. The aim of this review is to highlight the pathological conditions in which the study of intrarenal RI provides useful information about the pathophysiology of renal diseases in both the native and the transplanted kidneys.

Diagnostic and prognostic value of alpha-fetoprotein, des-γ-carboxy prothrombin and squamous cell carcinoma antigen immunoglobulin M complexes in hepatocellular carcinoma.

The hepatocellular carcinoma (HCC) is one of the most common malignant tumors. It carries a poor survival rate and has an increasing incidence worldwide. In most cases, HCC is diagnosed at a late stage. Therefore, the prognosis of patients with HCC is generally poor and has a less than 5% 5-year survival rate. The aim of this study was compare the accuracy of α-fetoprotein (AFP), des-γ- carboxy prothrombin (DCP), squamous cell carcinoma antigen-immunoglobulin M complexes (SCCA-IgM Cs) in the early diagnosis and in the prognosis of HCC. A literature search identified the markers for hepatocellular carcinoma. A search of the literature was made using cancer literature and the PubMed database for the following keywords: "markers and HCC", "α-fetoprotein (AFP) and HCC", "Des-γ-carboxy prothrombin"(DCP) and HCC, "squamous cell carcinoma antigen-immunoglobulin M complexes" (SCCA-IgM Cs). Despite the large number of studies devoted to the immunohistochemistry of HCC, at the present time, the absolute positive and negative markers for HCC are still lacking, and even those characterized by very high sensitivity and specificity do not have an universal diagnostic usefulness. In conclusion none of the three biomarkers (AFP, DCP, SCCA-IgM Cs) is optimal. According to recent reviews, these biomarkers should be measured simultaneously and in combination with imaging techniques to increase the sensitivity, specificity, diagnostic accuracy and to make a reliable prognosis. Currently the recommended screening strategy for patients with cirrhosis includes the determination of serum AFP levels and an abdominal ultrasound every six months to detect HCC at an earlier stage.

GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors.

Traditional methods for performing 3D-QSAR rely upon an alignment step that is often time-consuming and can introduce user bias, the resultant model being dependent upon and sensitive to the alignment used. There are several methods which overcome this problem, but in general the necessary transformations prevent a simple interpretation of the resultant models in the original descriptor space (i.e. 3D molecular coordinates). Here we present a novel class of molecular descriptors which we have termed GRid-INdependent Descriptors (GRIND). They are derived in such a way as to be highly relevant for describing biological properties of compounds while being alignment-independent, chemically interpretable, and easy to compute. GRIND are obtained starting from a set of molecular interaction fields, computed by the program GRID or by other programs. The procedure for computing the descriptors involves a first step, in which the fields are simplified, and a second step, in which the results are encoded into alignment-independent variables using a particular type of autocorrelation transform. The molecular descriptors so obtained can be used to obtain graphical diagrams called "correlograms" and can be used in different chemometric analyses, such as principal component analysis or partial least-squares. An important feature of GRIND is that, with the use of appropriate software, the original descriptors (molecular interaction fields) can be regenerated from the autocorrelation transform and, thus, the results of the analysis represented graphically, together with the original molecular structures, in 3D plots. In this respect, the article introduces the program ALMOND, a software package developed in our group for the computation, analysis, and interpretation of GRIND. The use of the methodology is illustrated using some examples from the field of 3D-QSAR. Highly predictive and interpretable models are obtained showing the promising potential of the novel descriptors in drug design.

Chemometric methodologies in a quantitative structure-activity relationship study: the antibacterial activity of 6-aminoquinolones.

The paper illustrates the chemometric strategies appropriate for extracting information from a large amount of biological data regarding the antibiotic activity of 6-aminoquinolones. The unique framework based on principal component analysis, projection onto latent structures, and response surface methodologies permits the structure-activity correlations to be shown and to suggest new compounds for further testing. The low activity of the suggested molecules points out the limitations of quantitative structure-activity relationship models when the training set is not properly designed in order to balance all the structural variations taken into account.

Smart region definition: a new way to improve the predictive ability and interpretability of three-dimensional quantitative structure-activity relationships.

This report describes a new methodology aimed at grouping 3D-QSAR interaction energy descriptors into regions of neighbor variables bearing the same chemical and statistical information. These regions represent the structural variability of the series better than individual descriptor variables and can advantageously replace them in the chemometric analysis. The algorithm used to generate such regions is described, together with their application for improving the quality of GOLPE variable selection. The method is illustrated on a series of 47 glucose analogues, inhibitors of glycogen phosphorylase b, and is shown to improve both the predictive ability and the interpretability of the 3D-QSAR models obtained, comparing favorably with other methods previously described.

GRID/GOLPE 3D quantitative structure-activity relationship study on a set of benzamides and naphthamides, with affinity for the dopamine D3 receptor subtype.

In the search for drugs against schizophrenia and depression without extrapyramidal side effects, compounds that selectively antagonize the dopamine D3 receptor subtype are thought to be a solution. In order to create a model with which the D3 activity can be predicted and that can generate new ideas for future synthesis, we performed a comparative molecular field analysis (CoMFA). In our model 30 ligands were described quantitatively in the GRID program, and the model was optimized by selecting only the most informative variables in the GOLPE program. We found the predictive ability of the model to increase significantly when the number of variables was reduced from 25110 to 784. A Q2 of 0.65 was obtained with the final model, confirming the predictive ability of the model. By studying the PLS coefficients in informative 3D contour plots, ideas for the synthesis of new compounds can be generated.

6-Aminoquinolones: a new class of quinolone antibacterials?

A series of quinolone- and 1,8-naphthyridone-3-carboxylic acids, designed by previous QSAR studies and characterized by an amino group at the C-6 position instead of the usual fluorine atom, were synthesized for the first time and evaluated for in vitro antibacterial activity. All of the synthesized compounds maintain good activity against Gram-negative bacteria (Pseudomonas aeruginosa excluded), and those compounds having a thiomorpholine group as the C-7 substituent also have good activity against Gram-positive bacteria. Some aspects of structure-activity relationships associated with the C-1, C-5, C-7, and C-8 substituents are also discussed. Derivatives 18g and 38g displayed the best activity with geometric mean MICs of 0.45 and 0.66-0.76 micrograms/mL against Gram-negative and Gram-positive bacteria, respectively. This antimicrobial activity reflects their ability to inhibit bacterial DNA-gyrase. The results of this study show that, while the C-6 fluorine is still the preferred substituent, good activity can still be obtained by replacing it with an amino group.

The importance of secondary anchor residue motifs of HLA class I proteins: a chemometric approach.

In this paper we report a chemometric approach to Quantitative Structure-Activity Relationship (QSAR) analysis applied to a study of the binding of peptides to Major Histocompatibility Complex (MHC) class I proteins. Peptides which possess the known primary anchor residue motif for HLA-B27 binding do not necessarily bind to HLA-B27 proteins. Secondary anchor residues are also involved, but it is not yet clear which amino acids are required or in which positions. A classic approach to this problem would be to synthesize multiple peptides each varying by a single amino acid from a starting peptide, and test them for their binding properties. Not only is this approach inefficient, but it is essentially unable to provide information about possible mutual interactions of amino acid residues in different positions. Using a statistical design to select the most informative compounds to use in the QSAR study, it was possible to analyse the effects on HLA-B27 peptide binding of different amino acids in four positions by means of only nine peptides. The relative binding activity of these peptides could then be modeled mathematically to provide information about the relative contribution of each of the four positions and to suggest a new peptide with high binding affinity. Our results demonstrate the usefulness of the chemometric strategy for studying peptides of interest in molecular immunology.

A comparative chemometric study of QSAR descriptors.

Traditional descriptors for Qsar models are compared with two alternative blocks obtained by computer chemistry tools: electronic densities and principal properties. All three sets show similar prediction abilities by PLS modelling.

Chemometric approach in a QSAR study: the antibacterial and antimicotic activities of benzofused heteroaromatic derivatives.

In order to establish quantitative relationships between the antibacterial activities of a number of thienyl- and furyl-benzimidazoles and benzoxazoles, the biological data were measured homogeneously for a selected set of 16 representative compounds of the available set of 103. The data were analyzed by the PLS method. The results of linear PLS modelling and PLS response surface modelling permitted a straightforward interpretation of the structural features relevant to the activities and the prediction of a possible optimal structure.

Response surfaces for modelling biological activities by principal properties of substituents: the CARSO procedure.

Three literature data sets are modelled by PLS response surfaces in terms of the principal properties of organic substituents by means of the CARSO procedure. The models permit one to rationalize the biological data, to predict new activities, and to detect optimal structures.

QSARs and pesticides design.

A multivariate analysis of phytotoxicity and measured ecotoxicity data of a set of 30 herbicidal triazines was carried out. Results indicate that it is feasible to design triazines that combine limited ecotoxicity with high herbicidal potency.

Qualitative organic analysis. Part 2. Identification of drugs by principal components analysis of standardized TLC data in four eluent systems and of retention indices on SE 30.

The principal components (PC) analysis of standardized Rf values in four eluent systems [ethyl acetate/methanol/30% ammonia (85:10:15), cyclohexane/toluene/diethylamine (65:25:10), ethyl acetate/chloroform (50:50), and acetone with the plate dipped in potassium hydroxide solution] and of gas chromatographic retention indices in SE 30 for 277 compounds provided a two-principal-components model that explains 82% of the total variance. The scores plot allowed identification of unknowns or restriction of the range of inquiry to very few candidates. Comparison of these candidates with those selected from another PC model derived from TLC data only allowed identification of the drug in all the examined cases.

Qualitative organic analysis. I. Identification of drugs by principal components analysis of standardized thin-layer chromatographic data in four eluent systems.

Principal component analysis of standardized RF values in four eluent systems [ethyl acetate-methanol-30% ammonia (85:10:15), cyclohexane-toluene-diethylamine (65:25:10), ethyl acetate-chloroform (50:50) and acetone, with the plate dipped in potassium hydroxide solution] provided a two-component model which accounts for 73% of the total variance. The "scores" plot allowed the restriction of the range of inquiry to a few candidates. This result is of great practical significance in analytical toxicology, especially when account is taken of the cost, the time, the analytical instrumentation and the simplicity of the calculations required by the method.

Identification of drugs by principal components analysis of Rf data obtained by TLC in different eluent systems.

The retention factor of 54 drugs in eight eluent mixtures is reported. Principal component analysis (PCA) of these data provided a significant two-components model. These two parameters characteristic for each drug allowed an objective identification of unknown samples, provided they were included in the considered set. The analysis showed that the eluent mixtures cluster into three groups. The PCA model, using only three eluents (one for each group), was also able to restrict the range of inquiry to a few "candidates" and, in some cases, to allow unambiguous identification of the drug. These results, based on a simple and quick analytical determination (thin layer chromatography) and a reliable statistical procedure (PCA), appear to be of significant practical importance in the field of analytical toxicology.