Signalling inhibitors against Mycobacterium tuberculosis--early days of a new therapeutic concept in tuberculosis.

Tuberculosis causes nearly two million deaths per year world-wide. In addition multidrug-resistant mycobacterial strains rapidly emerge so novel therapeutic approaches are needed. Recently, several promising mycobacterial target molecules were identified, which are involved in bacterial or host cell signalling e.g. the serine/threonine protein kinases, PknB and PknG, NAD kinase and the NAD synthetase. Here we describe some early efforts in the development of novel signal transduction inhibitory anti-mycobacterial drugs using a multiple target approach, with special emphasis on the kinase inhibitory field. Initially, we are using the Nested Chemical Library (NCL) technology and pharmacophore modelling. A hit-finding library, consisting of approximately 19000 small molecules with a bias for prototypic kinase inhibitors from our NCL library and commercial sources was virtually screened against these validated target molecules. Protein structures for the virtual screening were taken from the published three dimensional crystal structures of the enzymes. The hits from the virtual screening were subsequently tested in enzymatic assay systems. Potent hits were then tested for biological activity in macrophages, infected with mycobacteria. The final goal of this exercise is not only to identify potent anti-mycobacterial substances, but also a common pharmacophore for the mycobacterial target PknG in combination with PknB, NAD kinase and/or NAD synthetase. This common pharmacophore still needs to be a unique pharmacophore for the mycobacterial target proteins over human off-targets. Such a pharmacophore might then drive the optimization of a completely new profile of an antibiotic agent with activity against latent mycobacteria and resistance mycobacterial strains.

Structure -activity relationships of PDE5 inhibitors.

cGMP has a short-term effect on smooth muscle tone and a longer-term effect on responses to chronic drug treatment or proliferative signals. cGMP-Phosphodiesterase type 5 (PDE5) hydrolizes cGMP, and the result is smooth muscle contraction. PDE5 is a relatively novel therapeutic target of various diseases, such as erectile dysfunction and pulmonary hypertension. The most intensively examined and marketed PDE5 inhibitor was sildenafil (Viagra) but recently vardenafil (Levitra) and tadalafil (Cialis) were launched with beneficial ADME parameters and PDE5 selectivity. The increasing interest in PDE5 inhibition made it reasonable to collect the available inhibitory data from the scientific literature and set up a structure-activity relationship study. Chemical structures of 438 compounds and their cGMP-PDE5 inhibitory data (IC50) were collected from recently published articles. In this paper physiology, regulation and inhibition of PDE5 (and briefly other PDE-s) are discussed and inhibitors are tabulated by the core structures. Finally, a general QSAR model built from these data is presented. All data used in the QSAR study were summarized in a Supplement (for description please see the online version of the article).

Prediction oriented QSAR modelling of EGFR inhibition.

Epidermal Growth Factor Receptor (EGFR) is a high priority target in anticancer drug research. Thousands of very effective EGFR inhibitors have been developed in the last decade. The known inhibitors are originated from a very diverse chemical space but--without exception--all of them act at the Adenosine TriPhosphate (ATP) binding site of the enzyme. We have collected all of the diverse inhibitor structures and the relevant biological data obtained from comparable assays and built prediction oriented Quantitative Structure-Activity Relationship (QSAR) which models the ATP binding pocket's interactive surface from the ligand side. We describe a QSAR method with automatic Variable Subset Selection (VSS) by Genetic Algorithm (GA) and goodness-of-prediction driven QSAR model building, resulting an externally validated EGFR inhibitory model built from pIC50 values of a diverse structural set of 623 EGFR inhibitors. Repeated Trainings/Evaluations (RTE) were used to obtain model fitness values and the effectiveness of VSS is amplified by using predictive ability scores of descriptors. Numerous models were generated by different methods and viable models were collected. Then, intensive RTE were applied to identify ultimate models for external validations. Finally, suitable models were validated by statistical tests. Since we use calculated molecular descriptors in the modeling, these models are suitable for virtual screening for obtaining novel potential EGFR inhibitors.

Characterization of lipophilicity and antiproliferative activity of E-2-arylmethylene-1-tetralones and their heteroanalogues.

A molecular library based on E-2-arylmethylene-1-tetralone has been designed and synthesized. A reversed phase high performance liquid chromatographic (RP-HPLC) method has been developed and applied to separate them and to characterize their lipophilicity. The chromatographic method applied here was suitable to separate the structural (ortho and para) isomers of compounds and was sensitive enough to differentiate their lipophilicities. The measured (k') and computer calculated (CLOGP) lipophilicity values has been compared. Good linear correlation has been found in the case of these structurally related molecules. In vitro biological assay has been performed with Methylene blue dying to investigate the antiproliferative potency of the compounds synthesized in this work. The measured (k') and calculated (CLOGP) lipophilicities of the compounds were compared with the antiproliferative activities and an optimum value of lipophilicity has been found for these compounds.

Comparison of measured and calculated lipophilicity of substituted aurones and related compounds.

A molecule library containing 55 aurone- and thioaurone-type structures has been designed and synthesised. Reversed phase high performance liquid chromatographic (RP-HPLC) method has been developed to separate these compounds and to characterise their lipophilicity by experimental method (k'). The experimental lipophilicity data have been compared with the computer calculated lipophilicity parameters (CLOGPs) of the same molecules. In general, good correlations between the measured and calculated lipophilicities have been found with the exception of structure isomers and compounds capable for hydrogen bonding. The chromatographic method was suitable to separate the structure (ortho and para) isomers of aurone and thioaurones and was sensitive enough to differentiate their lipophilicities. Our findings suggest the usefulness of the chromatographic method in fast characterisation of the lipophilicity of structurally closely related molecules.

Determination of the basicity of Mannich ketones by capillary electrophoresis.

Capillary electrophoretic (CE) method to characterise Mannich ketones (MKs) containing morpholine moiety was developed. Basicity (pKa,exp) of the MKs was characterised by measured data derived from the electrophoretic mobility values obtained in the CE separation. The MKs were found to be weaker bases than the parent morpholine molecule itself and the experimentally determined basicity values proved to be dependent on the chemical structure of the MKs. Since the basicity of the MKs has an influence on their reactivity and biological activity it seems to be useful to determine experimentally the pKa,exp values of the newly synthesised compounds to support rational drug design or screening of the molecule libraries.

Reliability of logP predictions based on calculated molecular descriptors: a critical review.

Correct QSAR analysis requires reliable measured or calculated logP values, being logP the most frequently utilized and most important physico-chemical parameter in such studies. Since the publication of theoretical fundamentals of logP prediction, many commercial software solutions are available. These programs are all based on experimental data of huge databases therefore the predicted logP values are mostly acceptable - especially for known structures and their derivatives. In this study we critically reviewed the published methods and compared the predictive power of commercial softwares (CLOGP, KOWWIN, SciLogP/ULTRA) to each other and to our recently developed automatic QS(P)AR program. We have selected a very diverse set of 625 known drugs (98%) and drug-like molecules with experimentally validated logP values. We have collected 78 reported "outliers" as well, which could not be predicted by the "traditional" methods. We used these data in the model building and validation. Finally, we used an external validation set of compounds missing from public databases. We emphasized the importance of data quality, descriptor calculation and selection, and presented a general, reliable descriptor selection and validation technique for such kind of studies. Our method is based on the strictest mathematical and statistical rules, fully automatic and after the initial settings there is no option for user intervention. Three approaches were applied: multiple linear regression, partial least squares analysis and artificial neural network. LogP predictions with a multiple linear regression model showed acceptable accuracy for new compounds therefore it can be used for "in-silico-screening" and/or planning virtual/combinatorial libraries.

[Biological activity and structure of antitumor compounds from Plantago media L]. / Plantago media L antitumor hatóanyagainak szerkezete és biológiai aktivitása.

Tyrosine kinase inhibition and tumor growth inhibition activity of verbascoside and homoplantaginin are described. Both molecules proved to be equally significant inhibitors of isolated EGF-R tyrosine kinases, nevertheless their in vitro antiproliferative activity was variable in cellular assays. Their different inhibitory efficacies could be interpreted on the basis of conformational analysis and lipophilicity evaluation.