D. Eros

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 (Supporting Material)

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 pockets 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.

Protein kinase inhibitor-induced endothelial cell cytotoxicity and its prediction based on calculated molecular descriptors

Protein kinase inhibitors (PKIs) as potent signal transduction therapeutic compounds represent a very rapidly expanding group of anticancer drugs. These agents may be toxic for endothelial cells, however, very few experimental data exist on the cytotoxicity of PKIs. The aim of this study was to set up an appropriate test system for endothelial cells and to assess the structure-related cytotoxic effects of a selected library of PKIs. The inhibitor library contains several lead molecules with different basic structures and a set of modified derivatives of the lead compounds. The toxicity of PKIs did not correlate directly with the structural features of the molecules. However, we successfully built up a model based on 15 calculated molecular descriptors, which is capable of predicting cytotoxicity with acceptable probability. Our results show that the cytotoxic effects of PKIs should be taken into account for optimal drug development to overcome endothelial cell-related side effects.

HPLC Analysis, Modeling, and Biological Studies of Antiproliferative Heterocyclic Carboxamides

Reversed phase HPLC and MEKC [1] provide excellent possibilities to measure the hydrophobic properties of compounds, characterizing them directly from the chromatographic retention time. The aim in this respect is to estimate the hydrophobic character of the molecules on the basis of their retention factors (k′) determined in various separation processes [1]. The expected biological activity of the compounds can be reliably predicted on the basis of the measured hydrophobicity data [2]. Another possibility is the use of highly sophisticated computer programs to calculate hydrophobicity on the basis of the structural moieties building up the molecule being investigated.