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.
Somatostatin released from the capsaicin-sensitive sensory nerves mediates analgesic and anti-inflammatory effects via the somatostatin sst 4 receptor without endocrine actions. Therefore, sst 4 is considered to be a novel target for drug development in pain including chronic neuropathy, which is an emerging unmet medical need. Here, we examined the in silico binding, the sst 4 -linked G-protein activation on stable receptor expressing cells (1 nM to 10 µM), and the effects of our novel pyrrolo-pyrimidine molecules in mouse inflammatory and neuropathic pain models. All four of the tested compounds (C1-C4) bind to the same binding site of the sst 4 receptor with similar interaction energy to high-affinity reference sst 4 agonists, and they all induce G-protein activation. C1 is the more efficacious (γ-GTP-binding: 218.2% ± 36.5%) and most potent (EC 50 : 37 nM) ligand. In vivo testing of the actions of orally administered C1 and C2 (500 µg/kg) showed that only C1 decreased the resiniferatoxin-induced acute neurogenic inflammatory thermal allodynia and mechanical hyperalgesia significantly. Meanwhile, both of them remarkably reduced partial sciatic nerve ligation-induced chronic neuropathic mechanical hyperalgesia after a single oral administration of the 500 µg/kg dose. These orally active novel sst 4 agonists exert potent anti-hyperalgesic effect in a chronic neuropathy model, and therefore, they can open promising drug developmental perspectives. strongly limited by its diverse effects and rapid degradation and consequently short elimination half-life (<3 min) [9]. However, stable and potent synthetic analogs could be potential analgesic candidates.A wide range of somatostatin effects are mediated via five inhibitory G-protein-coupled receptor subtypes (GPCRs) [10,11] which have seven transmembrane domains (TMDs). They are divided into two classes on the basis of their phylogeny, structural homologies and pharmacological properties. The somatotropin release-inhibiting factor 1 (SRIF1) receptor class involves sst 2 , sst 3 and sst 5 mediating important endocrine actions of somatostatin (e.g., inhibition of growth hormone, insulin, glucagon secretion), and the SRIF2 class includes sst 1 and sst 4 [10]. It is well known that sst 4 receptor is present in the dorsal root ganglia cells and spinal cord dorsal horn, and can also mediate analgesic effects along with the δ-opioid receptor [12,13]. We provided several lines of evidence that the broad anti-inflammatory, antinociceptive and anti-hyperalgesic effects of somatostatin are mediated by the sst 4 receptor without influencing endocrine functions [1,4,[14][15][16][17]. Therefore, the sst 4 receptor has become a well-established novel drug target and the development of sst 4 agonists has recently been included in the scope of several pharmaceutical companies [13,[18][19][20][21][22][23].Several hepta-and octapeptide somatostatin analogs, such as 25], were shown to induce anti-inflammatory and antinociceptive effects [13,[26][27][28][29], predominantly via sst 4 activ...
Kinase inhibitors are at the forefront of modern drug research, where mostly three technologies are used for hit-and-lead finding: high throughput screening of random libraries, three-dimensional structure-based drug design based on X-ray data, and focused libraries around limited number of new cores. Our novel Nested Chemical Library (NCL) (Vichem Chemie Research Ltd., Budapest, Hungary) technology is based on a knowledge base approach, where focused libraries around selected cores are used to generate pharmacophore models. NCL was designed on the platform of a diverse kinase inhibitory library organized around 97 core structures. We have established a unique, proprietary kinase inhibitory chemistry around these core structures with small focused sublibraries around each core. All the compounds in our NCL library are stored in a big unified Structured Query Language database along with their measured and calculated physicochemical and ADME/toxicity (ADMET) properties, together with thousands of molecular descriptors calculated for each compound. Biochemical kinase inhibitory assays on selected, cloned kinase enzymes for a few hundred NCL compound sets can provide sufficient biological data for rational computerized design of new analogues, based on our pharmacophore model-generating 3DNET4W QSPAR (quantitative structure-property/activity relationships) approach. Using this pharmacophore modeling approach and the ADMET filters, we can preselect synthesizable compounds for hit-and-lead optimization. Starting from this point and integrating the information from QSPAR, high-quality leads can be generated within a small number of optimization cycles. Applying NCL technology we have developed lead compounds for several validated kinase targets.
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