Current Pharmaceutical Design - Volume 22, Issue 33, 2016

In this work we report the first attempt to study the effect of activity cliffs over the generalization ability of machine learning (ML) based QSAR classifiers, using as study case a previously reported diverse and noisy dataset focused on drug induced liver injury (DILI) and more than 40 ML classification algorithms. Here, the hypothesis of structure-activity relationship (SAR) continuity restoration by activity cliffs removal is tested as a potential solution to overcome such limitation. Previously, a parallelism was established between activity cliffs generators (ACGs) and instances that should be misclassified (ISMs), a related concept from the field of machine learning. Based on this concept we comparatively studied the classification performance of multiple machine learning classifiers as well as the consensus classifier derived from predictive classifiers obtained from training sets including or excluding ACGs. The influence of the removal of ACGs from the training set over the virtual screening performance was also studied for the respective consensus classifiers algorithms. In general terms, the removal of the ACGs from the training process slightly decreased the overall accuracy of the ML classifiers and multi-classifiers, improving their sensitivity (the weakest feature of ML classifiers trained with ACGs) but decreasing their specificity. Although these results do not support a positive effect of the removal of ACGs over the classification performance of ML classifiers, the “balancing effect” of ACG removal demonstrated to positively influence the virtual screening performance of multi-classifiers based on valid base ML classifiers. Specially, the early recognition ability was significantly favored after ACGs removal. The results presented and discussed in this work represent the first step towards the application of a remedial solution to the activity cliffs problem in QSAR studies.

Background: Chronic myelogenous leukemia is associated with hematopoietic stem cells that are manifested primarily with expansion myelopoiesis. It is the first cancer directly associated with a genetic abnormality. Specifically, it is associated to a particular cytogenetic abnormality, known as Philadelphia chromosome (Ph), which results from a fusion between part of the BCR (“breakpoint cluster region”) gene from chromosome 22 and the Abelson (ABL) gene on chromosome 9 and leads to the formation a new gene leukemia-specific, the BCR-ABL. Since 2011, there are several tyrosine-kinase inhibitors in the market. Due to mutations in the tyrosine-kinase domain, these inhibitors are becoming less effective in the leukemia treatment, and then there is a need for new more effective inhibitors. Methods: The aim of this work is to obtain new tyrosine-kinase inhibitors using in silico tools like de novo drug design, docking and absorption, distribution, metabolism and excretion studies. Results: Using the proposed methodology, an initial library of more than 6000 molecules was obtained. This library was then filtered out using the Tanimoto metric to compute the similarity between the molecules using as parameter the 2D linear hashed fingerprint with a 64-bit address space. The resulting library was then used to run docking studies together with the reference market drugs and their ADME (absorption, distribution, metabolism and excretion) properties were determined. Three compounds with better inhibition capacity and better ADME properties that the commercially available not only for the wild form of enzymes under study but also to its mutated forms were obtained. Conclusion: The fragment based drug design method used in this work turns to be a good alternative to create new drugs that can control this neoplasm. Based on the calculated GScore, the de novo designed molecules have better inhibitor capacity than the tyrosine-kinase inhibitors most used in the market. These molecules shown strong potential to become drugs capable to inhibit all mutations, mainly the T315I mutation, now the leading cause of deaths due to the difficulty of inhibitors to control it.

Background: The Ribonuclease III (RNase III) enzymatic class is involved in many important biological processes from bacteria to higher eukaryotes. Consequently, they have been useful as drug-target candidates for drug development. Despite their high molecular diversity, RNases III share common structural and catalytic features and some degree of enzymatic activity. However, the role of accessory domains as key determinants of substrate selectivity and over the biological function of each RNase III type is still under study. Results: The in vitro enzymatic activity of three RNase III members from class I (Escherichia coli RNase III, Schizosaccharomyces pombe Pac1 and Saccharomyces cerevisiae Rntp1) and the human Drosha placed in class II was revisited against four different substrates. These two RNase III classes comprise members showing different domain organization. Enzymatic activity differences were found among members of the class I, which were even higher when the human Drosha (class II) was tested. The substrate promiscuity of the E. coli RNase III was corroborated in vivo through its expression in S. cerevisiae, as reported previously, but was extended here to Pichia pastoris. The putative molecular mechanisms contributing for the lethal effect of the heterologous RNase III on the yeast lives were deeply discussed. Conclusion: The new generated biochemical data integrated with previous available information affirmed that RNases III substrate specificity as well as their cellular biological role is highly influenced by its protein structure architecture. This fact also allowed drawing evolutionary links between RNase III members from their structural and substrate specificity differences.

Background: Dysregulation of HDACs has been associated with tumour development and therefore inhibiting HDAC’s have surfaced as promising therapeutic strategy in malignancy. Methods: Vorinostat analogues with different biological activities were investigated for underlying structure-activity relationship. Results: Out of six activities and their multiple QSAR models, HDAC1 and HDAC8 produced statistically fit, stable and predictive linear (MLR) and non-linear (SVM) QSAR models. In case of HDAC1 activity as end point, linear (R2=0.8089, R2 CV=0.7343) and non-linear (R2=0.9801, R2 CV=0.8952) QSAR models turned reliable to investigate SAR. Similarly, HDAC8 activity based linear (R2=0.9454, R2 CV=0.9049) and non-linear (R2=0.9899, R2 CV=0.9232) QSAR models produced statistically improved and stable models. Conclusion: Molecular descriptors derived from 3-D Morse and Radial Distribution Function indices were found to be selective in all the models. These molecular descriptors which encode common SAR among Vorinostat derivatives were evaluated for their potent HDAC inhibition activity.

Background: The emergence of reduced susceptibility to fluoroquinolones among Salmonella enterica serotype Typhimurium isolates leading to clinical failure of treatment poses a great therapeutic challenge. Methods: The current study is focused on the evaluation of the minimum inhibitory concentration (MIC) of quinolones in 29 Salmonella typhimurium of 86 Salmonella spp. strains, obtained from pigs from the State of Mexico. The MIC was performed with the Kirby-Bauer method. On the other hand, the GyrA gene was sequenced. The present study was undertaken to describe the resistance profiles and fluoroquinolone resistance mechanism of Salmonella Typhimurium. Results: The DNA sequence of the gyrA genes from Salmonella enterica serovar typhimurium revealed strong similarity between gyrA and its counterpart in Escherichia coli. The sequencing of quinolone resistance-determining region (QRDR) of the gyrA gene showed the presence of mutation at either S83 or at D87 in almost all the Salmonella typhimurium isolates. Conclusion: This mutation, although phenotypically expressed as decreased susceptibility to fluoroquinolones goes undetected by the disk diffusion method using the present method of Kirby-Bauer. Hence, it can increase morbidity and mortality due to delay in appropriate antibiotic treatment.

Background: Many QSAR studies have been developed to predict acute toxicity over several biomarkers like Pimephales promelas, Daphnia magna and Tetrahymena pyriformis. Regardless of the progress made in this field there are still some gaps to be resolved such as the prediction of aquatic toxicity over the protozoan T. pyriformis still lack a QSAR study focused in accomplish the OECD principles. Methods: Atom-based quadratic indices are used to obtain quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity. Our models agree with the principles required by the OECD for QSAR models to regulatory purposes. The database employed consists of 392 substituted benzenes with toxicity values measured in T. pyriformis (defined endpoint), was divided using cluster analysis in two series (training and test sets). Results: We obtain (with an unambiguous algorithm) two good multiple linear regression models for non-stochastic (R2=0.807 and s=0.334) and stochastic (R2=0.817 and s=0.321), quadratic indices. The models were internally validated using leave-one-out, bootstrapping as well as Y-scrambling experiments. We also perform an external validation using the test set, achieving values of R2 pred values of 0.754 and 0.760, showing that our models have appropriate measures of goodness- of-fit, robustness and predictivity. Moreover, we define a domain of applicability for our best models. Conclusion: The achieved results demonstrated that, the atom-based quadratic indices could provide an attractive alternative to the experiments currently used for determining toxicity, which are costly and time-consuming.

In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22- 24), an unique event, named connected subgraphs, (based on the Kier-Hall’s subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach’s subgraphs), fingerprints (MACCs, E-state and substructure fingerprints) and atomic contributions (Ghose and Crippen atom-types for hydrophobicity and refractivity) for F generation. The events are intended to capture diverse information by the generation or search of different kinds of substructures from the graph representation of a molecule. The discrete derivative over duplex atom relations are calculated for each event, and the resulting derivatives, local vertex invariants (LOVIs) are finally obtained. These LOVIs are subsequently employed as the basis for the calculation of global and local indices over groups of atoms (heteroatoms, halogens, methyl carbons, etc.), by using norms, means, statistics and classical algorithms as aggregator (fusion) operators. These indices were implemented in our house software DIVATI (Derivative Type Indices, a new module of TOMOCOMDCARDD system). DIVATI provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http: //www.tomocomd.com. Factor analysis shows that the presented events are rather orthogonal and collect diverse information about the chemical structure. Finally, QSPR models were built to describe the logP and logK of 34 furylethylenes derivatives using the eleven events. Generally, the equations obtained according to these events showed high correlations, with the Sach’s sub-graphs and Multiplicity events showing the best behavior in the description of logK (Q2 LOO value of 99.06%) and logP (Q2 LOO value of 98.1 %), respectively. These results show that these new eventbased indices constitute a powerful approach for chemoinformatics studies.

We can combine experimental techniques like Flow Cytometry Analysis (FCA) with Chemoinformatics methods to predict the complex networks of interactions between organic compounds and targets in the immune system. In this work, we determined experimentally the values of EC50 = 17.82 μg/mL and Cytotoxicity = 20.6 % for the anti-microbial / anti-parasite drug Dermofural over Balb/C CD9 lymphocytes using flow cytometry. After that, we developed a new Perturbation-theory model for Drug-Cell Target Interactome in Lymphocytes based on dispersion-polarization moments of drug structure. The models correctly classifies 34591 out of 42715 (Accuracy = 80.9%) cases of perturbations in assay endpoints of 11492 drugs (including both train and validation series). Each endpoint correspond to one out of 2616 assays, 38 molecular and cellular targets, 77 standard type measures, in four possible (human and rodents).

It is still not clear whether intact lipid vesicles can cross the human skin. Some reports in the literature indicate that transfersomes® can cross the skin. Other reports suggest that intact liposomes cannot cross the skin. Of course, the composition of the various formulations has to be taken into consideration before making such assertions. The present review examines the use of vesicles- elastic liposomes and ethosomes- for transdermal drug delivery. Liposomes are micro- or nano-structures formed from a bilayer of lipid surrounding an aqueous core. Elastic liposomes differ from conventional liposomes because they contain edge activators (surfactants) which impart elasticity and deformability. Ethosomes are efficient in facilitating percutaneous drug penetration. They are structurally similar to conventional liposomes in the sense that they are prepared from phospholipids but different because they contain a high concentration of ethanol. Both elastic liposomes and ethosomes are increasingly being used for delivering low and high molecular weight drugs. In this review, several reports are presented showing the usefulness of these vesicles and mechanistic insight sought as to why they may be effective in certain cases.

Chemotherapy is one of the most frequently employed and reliable treatment options for the management of a variety of cancers. Taxanes (paclitaxel, docetaxel and cabazitaxel) are frequently prescribed to treat breast cancer, hormone refractory prostate cancer, non-small cell lung cancer and ovarian cancer. Most of the commercial products of taxanes are available as injectables, which are not patient compliant and are associated with frequent side effects like ototoxicity, baldness and neurotoxicity. Most of these concerns are ascribable to the presence of toxic solvents in these commercial formulations, which are used to solubilize these drug(s). However, there have been several attempts to develop toxic solvent free taxane formulations, especially employing novel drug delivery systems (NDDS). These systems have been reported to result in the advancement of anticancer activity, therapeutic index, stability, biocompatibility, tissue or organ targeting, encapsulation capacity, tissue permeability, oral bioavailability, reduced toxicity and reduced incidences of abnormal reactions, sustained and controlled release in comparison to the conventional solvent-based formulations. The review is an attempt to analyze the potential of NDDS-mediated taxane delivery for safer and effective cancer chemotherapy.

Cariprazine (RGH-188) is a novel antipsychotic drug that exerts partial agonism of dopamine D2/D3 receptors with preferential binding to D3 receptor, antagonism of 5HT2B receptors and partial agonism of 5HT1A. Currently, cariprazine is in late-stage clinical development (phase III clinical trials) in patients with schizophrenia (S) and in patients with bipolar disorder (BD), as well as an adjunctive treatment in patients with Major Depressive Disorder (MDD) and drug-resistant MDD. Cariprazine has completed phase III trials for the acute treatment of schizophrenia and bipolar mania, phase II trials for the bipolar depression and MDD whilst it is undergoing phase III trials as an adjunct to antidepressants. The present review aims at proving a comprehensive summary of the current evidence on the safety, tolerability and efficacy of cariprazine in the treatment of schizophrenia, BD (manic/mixed/ depressive episode) and MDD. A systematic search was conducted on PubMed/Medline/ Scopus and the database on Clinical Trials from inception until April 2015 by typing a set of specified keywords. Available evidence seems to support cariprazine efficacy in the treatment of cognitive and negative symptoms of schizophrenia. Preliminary findings suggest its antimanic activity whilst it is still under investigation its efficacy in the treatment of bipolar depression and MDD. Furthermore, the available data seems not to allow judgements about its antipsychotic potential in comparison with currently prescribed antipsychotics. Further studies should be carried out to better investigate its pharmacodynamic and clinical potential, particularly as alternative to current antipsychotic drugs.

Blood hemostasis is attained with two sophisticated interconnected network systems, a coagulation cascade and a platelet activation system. Multiple inhibitors were developed to various components of both systems to prevent thrombosis-related morbid events that are of extremely high frequency in the human population. Antithrombotic inhibitors possess both positive and negative aspects. One of the essential modern requirements is a controllable mode of action for both anticoagulants and antiplatelets that could be achieved due to the high affinity and specificity of the inhibitor, as well as a possibility to apply an antidote, which quickly annihilates activity of the inhibitor and restores the proper hemostasis. Aptamers are DNA or RNA oligonucleotides with particular tertiary structure, such as DNA guanine quadruplex. Besides antibodies and other peptides/proteins, aptamers are one more example of the molecular recognizing elements that specifically bind to the target. Therefore, aptamers could be developed into a promising novel class of the drugs with high affinity, specificity, innate low toxicity, and rational antidote. Several aptamers with prospective antithrombotic activity have been reviewed; some of them are in preclinical and clinical trials.