Targeted drug combination therapy design based on driver genes.

Targeted therapies against cancer types with more than one driver gene hold bright but elusive promise, since approved drugs are not available for all driver mutations and monotherapies often result in resistance. Targeting multiple driver genes in different pathways at the same time may provide an impact extensive enough to fight resistance. Our goal was to find synergistic drug combinations based on the availability of targeted drugs and their biological activity profiles and created an associated compound library based on driver gene-related protein targets. In this study, we would like to show that driver gene pattern based customized combination therapies are more effective than monotherapies on six cell lines and patient-derived primary cell cultures. We tested 55-102 drug combinations targeting driver genes and driver pathways for each cell line and found 25-85% of these combinations highly synergistic. Blocking 2-5 cancer pathways using only 2-3 targeted drugs was sufficient to reach high rates of tumor cell eradication at remarkably low concentrations. Our results demonstrate that the efficiency of cancer treatment may be significantly improved by combining drugs against multiple tumor specific drivers.

Regulation of influenza A virus mRNA splicing by CLK1.

Influenza A virus carries eight negative single-stranded RNAs and uses spliced mRNAs to increase the number of proteins produced from them. Several genome-wide screens for essential host factors for influenza A virus replication revealed a necessity for splicing and splicing-related factors, including Cdc-like kinase 1 (CLK1). This CLK family kinase plays a role in alternative splicing regulation through phosphorylation of serine-arginine rich (SR) proteins. To examine the influence that modulation of splicing regulation has on influenza infection, we analyzed the effect of CLK1 knockdown and inhibition. CLK1 knockdown in A549 cells reduced influenza A/WSN/33 virus replication and increased the level of splicing of segment 7, which encodes the viral M1 and M2 proteins. CLK1-/- mice infected with influenza A/England/195/2009 (H1N1pdm09) virus supported lower levels of virus replication than wild-type mice. Screening of newly developed CLK inhibitors revealed several compounds that have an effect on the level of splicing of influenza A gene segment M in different models and decrease influenza A/WSN/33 virus replication in A549 cells. The promising inhibitor KH-CB19, an indole-based enaminonitrile with unique binding mode for CLK1, and its even more selective analogue NIH39 showed high specificity towards CLK1 and had a similar effect on influenza mRNA splicing regulation. Taken together, our findings indicate that targeting host factors that regulate splicing of influenza mRNAs may represent a novel therapeutic approach.

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.

Tyrosine kinase inhibitors - small molecular weight compounds inhibiting EGFR.

Abnormally elevated EGFR kinase activity can lead to various pathological states, including proliferative diseases such as cancer. The development of selective protein kinase inhibitors has become an important area of drug discovery for the potential treatment of a variety of solid tumors such as breast, ovarian and colorectal cancers, NSCLC, and carcinoma of the head and neck. There are three small molecule EGFR kinase inhibitor drugs in clinical use (gefitinib, erlotinib and lapatinib), and several others are currently undergoing clinical development. This review summarizes the development of EGFR kinase inhibitors, and includes descriptions of the binding modes, the importance of a multiple-targets strategy, the effects of sensitizing and resistance mutations in the EGFR, and molecular diagnostic approaches. In addition, the use of target fishing for selectivity profiling, off-target identification and quantitative structure-activity relationship modeling for the prediction of EGFR inhibition is discussed.

Binding specificity of the L-arginine transport systems in mouse macrophages and human cells overexpressing the cationic amino acid transporter hCAT-1.

The uptake of L-arginine into mouse peritoneal macrophages can be inhibited by numerous amino acids and derivatives. Kinetic studies showed an almost entirely competitive inhibition for both cationic and neutral amino acids and derivatives suggesting that the comparison of their binding specificity by using a quantitative structure-activity relationship (QSAR) study is reasonable. The properties of the most efficient inhibitors were the following: the length of the aliphatic side chain, a general structural similarity to L-arginine (>0.79), cationic character, L-configuration, the presence of an alpha-amino group (with a mean pK(a) of 9.41), the van der Waals volume (mean 225 A(3)) and a low logP value (mean: -2.99). The significance of four other descriptors (neutral character, presence and the pK(a) of an alpha-carboxyl group, and the presence of a modified guanidino group) is much lower. Similar results were obtained for the hCAT-1 cell line, but the significance of the descriptors was slightly different. The L-configuration, van der Waals volume, the low logP value and the length of aliphatic side chain were the most significant, while the pK(a) value of the side chain (mean pK(a)=11.6) was found to be more important than that of the alpha-amino group. In addition, the general similarity to L-arginine, the presence of an amino group in the terminal position of the side chain (Orn, Lys) and the basic character were significant descriptors, while the significance of the acidity is negligibly low. As a final conclusion, the following descriptors were found to be important generally for the cationic transporters: the van der Waals volume, hydrophobicity (log P); L-configuration; the size of the side chain; the general similarity to L-arginine; the presence of an alpha-amino group; the general basicity of the molecule; the pK(a) values of the alpha-amino group (in macrophages) or that of the side chain (in CAT-1 cells). These descriptors can be regarded as the general structurally important binding characteristics of the cationic amino transporters.

A novel drug discovery concept for tuberculosis: inhibition of bacterial and host cell signalling.

The Mycobacterium tuberculosis genome encodes for eleven eukaryotic-like Ser/Thr protein kinases. At least three of these (PknA, PknB and PknG) are essential for bacterial growth and survival. PknG is secreted by pathogenic mycobacteria, in macrophages to intervene with host cell signalling pathways and to block the fusion of the lysosomes with the phagosome by a still unknown mechanism. Based on our previously published results, we have initiated a drug discovery program, aiming to improve the potency against PknG and the physiochemical properties of the initially identified hit compound, AX20017, from the class of the tetrahydrobenzothiophenes. We have established a radioactive biochemical PknG kinase assay to test the novel analogues around AX20017. We have developed lead molecules with IC50 values in nanomolar range, and demonstrated their antituberculotic effects on human macrophages. Selected leads might ultimately serve the purpose of inducing phagosomal-lysosomal fusion and therefore destroy the residence of the intracellular mycobacteria. It is unclear at this time if these "homeless" mycobacteria are getting killed by the host, but they will be at least vulnerable to the activity of antimycobacterial agents. Released mycobacteria rely on the essential function of PknB for survival, which is our second molecular kinase target. PknB is a transmembrane protein, responsible for the cell growth and morphology. We have screened our library and synthesized novel compounds for the inhibition of PknB. A pharmacophore model was built and 70,000 molecules from our synthesizable virtual library have been screened to identify novel inhibitor scaffolds for the generation of templated compound libraries. Currently, we are using a radioactive kinase assay employing GarA as the putative, physiological substrate of PknB kinase. We have identified hits and generated optimised hit compounds with IC50 values for the inhibition of PknB in the nanomolar range. Yet those promising hits are not potent enough to yield meaningful "minimum inhibitory concentrations" in mycobacterial growth assays. In the course of our future work, we will increase the potency of the next generation of PknB inhibitors in order to improve their antibacterial activity.

Binding mode analysis and enrichment studies on homology models of the human histamine H4 receptor.

Ligand-supported homology models of the human histamine H4 receptor (hH4R) were developed based on the crystal structure of bovine rhodopsin and different known H4 ligands (histamine, OUP-16, JNJ7777120). Enrichment tests were performed to analyze whether our hH4R models can select known actives from random decoys. The impact of receptor conformation and the effect of different sets of random decoys, docking methods (FlexX, FlexX-Pharm) and scoring functions (FlexX-Score, D-Score, PMF-Score, G-Score, ChemScore) were investigated. We found that two agonists (histamine and OUP-16) form complementary interactions with Asp94 (3.32), Glu182 (5.46) and Thr323 (6.55), whereas JNJ7777120 interacts with Asp94 (3.32) and Glu182 (5.46) only. These results suggest a role of Thr323 (6.55) in ligand binding and presumably also in receptor activation. The models optimized in the presence of an agonist (histamine) and an antagonist (JNJ7777120) were compared in more detail. We conclude that the ligand used in the model building process can significantly influence the efficacy of virtual screening.

MIF tautomerase inhibitor potency of alpha,beta-unsaturated cyclic ketones.

The pro-inflammatory cytokine, macrophage migration inhibitory factor (MIF), is currently enjoying a renewed interest owing to its recently revealed functions. Among these its enzymatic tautomerase activity remains the most perplexing. There is a notion that some aspects of MIF signaling might involve its catalytic action. Though a true in vivo substrate for MIF has not been identified yet small molecule inhibitors of MIF are sought currently as potential anti-inflammatory agents. We have reported earlier that ketone bodies and some plant phenols feature acidic CH groups that appear to be good markers of their inhibitor potency toward MIF phenylpyruvate tautomerase. These molecules, like phenylpyruvate itself, belong to the keto-carboxylic acids or to the alpha,beta-unsaturated ketones. Some ketones of similar structure have earlier been reported to have anti-inflammatory effect. In this paper we report tautomerase inhibition by certain synthetic alpha,beta-unsaturated cyclic ketones, a novel class of small molecule MIF inhibitors.

Drug discovery in the kinase inhibitory field using the Nested Chemical Library technology.

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.

Synthesis of selective SRPK-1 inhibitors: novel tricyclic quinoxaline derivatives.

SR protein-specific kinase-1 (SRPK-1) has been identified as a validated target for hepatitis B virus (HBV). A series of novel tricyclic quinoxaline derivatives was designed and synthesised as potential kinase inhibitory antiviral agents and was found to be active and selective for SRPK-1 kinase. Most of these novel compounds have drug-like properties according to experimentally determined LogP and LogS values.

Comparison of predictive ability of water solubility QSPR models generated by MLR, PLS and ANN methods.

ADME/Tox computational screening is one of the most hot topics of modern drug research. About one half of the potential drug candidates fail because of poor ADME/Tox properties. Since the experimental determination of water solubility is time-consuming also, reliable computational predictions are needed for the pre-selection of acceptable "drug-like" compounds from diverse combinatorial libraries. Recently many successful attempts were made for predicting water solubility of compounds. A comprehensive review of previously developed water solubility calculation methods is presented here, followed by the description of the solubility prediction method designed and used in our laboratory. We have selected carefully 1381 compounds from scientific publications in a unified database and used this dataset in the calculations. The externally validated models were based on calculated descriptors only. The aim of model optimization was to improve repeated evaluations statistics of the predictions and effective descriptor scoring functions were used to facilitate quick generation of multiple linear regression analysis (MLR), partial least squares method (PLS) and artificial neural network (ANN) models with optimal predicting ability. Standard error of prediction of the best model generated with ANN (with 39-7-1 network structure) was 0.72 in logS units while the cross validated squared correlation coefficient (Q(2)) was better than 0.85. These values give a good chance for successful pre-selection of screening compounds from virtual libraries, based on the predicted water solubility.

Evaluation of lipophilicity and antitumour activity of parallel carboxamide libraries.

Searching for molecules possessing antitumour activity, a parallel molecule library of aromatic carboxamides has been designed and synthesised. This work resulted in a "thiophene" sub-library containing a thiophene core and of a "furoyl" sub-library with a furoyl core, respectively. In both sub-libraries substitutions were carried out with six different groups resulting in six pairs of compounds differing in only the heteroatom of aromatic ring of the cores. To study the importance of the type of cores and the specific substitutions in relation to their lipophilicity and antitumour activity, lipophilicity of carboxamides was determined by chromatographical data (log k') and by software calculated parameters (CLOGP). Pairs of compounds were tested for their ability to inhibit the proliferation of the A431 cells by MTT assay. The isosteric molecule pairs were successfully separated. Our results showed that the experimentally determined (log k') and the calculated (CLOGP) lipophilicity parameters correlated well with each other. Furthermore, lipophilicity values of the thiophene sub-library were always higher than those in the furoyl sub-library. Moreover, compounds of the thiophene sub-library were more active than their respective furoyl pairs in our MTT antiproliferative assay. From these observations we can conclude that the higher the lipophilicity values the higher the antitumour activity of the carboxamides synthesised. Therefore, determination of lipophilicity by measuring the log k' or by calculating the CLOGP values of the carboxamide sub-libraries may help to predict their biological activities.

Relationship between lipophilicity and antitumor activity of molecule library of Mannich ketones determined by high-performance liquid chromatography, clogP calculation and cytotoxicity test.

A series of Mannich ketones were synthesized in order to study the relative importance of structure and specific substitutions in relation to their lipophilicity and antitumor activity. Substitutions were carried out with morpholinyl, pirrolidinyl, piperidyl and tetrahydro-isoquinolyl groups in various positions on three different skeletons. Lipophilicity of Mannich ketones was characterised by chromatography data (log k') and by software calculated parameters (clogP). Compounds were tested on their ability to inhibit the proliferation of the A431 human adenocarcinoma cell line evaluated by MTT and apoptosis assays. The results suggest that the higher the lipophilicity values (log k' and clogP), the higher the antitumor and apoptotic activity of Mannich ketones. Determination of lipophilicity by measuring the log k' or by calculating the clogP values of the compounds may help to predict their biological activities.