Partial Least Squares Discriminant Analysis and 3D Similarity Perspective Applied to Analyze Comprehensively the Selectivity of Glycogen Synthase Kinase 3 Inhibitors.

The current work was conducted to investigate the effectiveness of two conceptually distinct in silico ligand-based tools: Partial Least Squares Discriminant Analysis (PLS-DA) and 3D similarity, including shape, physico-chemical and electrostatics to classify target-specific pharmacophores with enrichment power for selective GSK-3 inhibitors against the phylogenetically related CDK-2, CDK-4, CDK-5 and PKC. All virtual screens were performed on four data sets of targets matched pairwise, including selective and nonselective inhibitors for GSK-3. The classification method PLS-DA results revealed that all obtained models are statistically robust according to the cross-validation and response permutation tests. Regarding selective GSK-3 inhibitors differentiation in terms of selectivity (Se), specificity (Sp), and accuracy (ACC), the PLS-DA models for CDK-4/GSK-3, and PKC/GSK-3 datasets are highly efficient discriminative. 3D similarity searches for CDK-4/GSK-3, PKC/GSK-3, and CDK-2/GSK-3 datasets using the most selective reference molecules lead to highest enrichments of selective GSK-3 inhibitors. EON yields excellent early and overall enrichments for ET_ST and ET_combo for most selective query for CDK-4/GSK-3. CDK-5/GSK-3 dataset didn't show consistent statistically significant enrichments for 3D similarity virtual screening. The current methodology is reliable and could be used as a powerful tool for the detection of potentially selective molecules targeting GSK-3.

Design, Synthesis and Biological Activity Evaluation of S-Substituted 1H-5-Mercapto-1,2,4-Triazole Derivatives as Antiproliferative Agents in Colorectal Cancer.

Colon cancer is a widespread pathology with complex biochemical etiology based on a significant number of intracellular signaling pathways that play important roles in carcinogenesis, tumor proliferation and metastasis. These pathways function due to the action of key enzymes that can be used as targets for new anticancer drug development. Herein we report the synthesis and biological antiproliferative evaluation of a series of novel S-substituted 1H-3-R-5-mercapto-1,2,4-triazoles, on a colorectal cancer cell line, HT-29. Synthesized compounds were designed by docking based virtual screening (DBVS) of a previous constructed compound library against protein targets, known for their important role in colorectal cancer signaling: MEK1, ERK2, PDK1, VEGFR2. Among all synthesized structures, TZ55.7, which was retained as a possible PDK1 (phospholipid-dependent kinase 1) inhibitor, exhibited the most significant cytotoxic activity against HT-29 tumor cell line. The same compound alongside other two, TZ53.7 and TZ3a.7, led to a significant cell cycle arrest in both sub G0/G1 and G0/G1 phase. This study provides future perspectives for the development of new agents containing the 1,2,4-mercapto triazole scaffold with antiproliferative activities in colorectal cancer.

Elemental Characterization of Romanian Crop Medicinal Plants by Neutron Activation Analysis.

The metallic elements concentrations of medicinal plants (coriander, dill, Echinacea, lavender, chamomile, mint, and plantain, used for phytopharmaceutical products), cultivated in unpolluted region, were analyzed by neutron activation analysis. The essential nutrients, macro-, micro-, and trace elements (K, Ca, Mg, Na, Fe, Mn, Rb, Sr, and Zn), potentially toxic elements (Al, As, Ba, Co, Sb, Cr, and V), and rare earth elements were monitored and were compared with those presented in the literature. An estimation of their contributions to intake and toxicity for a person was made, which revealed that (a) teas prepared from the examined plants represent useful contribution to the food provided intake of three essential macronutrients (K, Ca, and Mg); (b) the Cu, Mn, Rb, Sr, Zn, and rare earths levels are normal or low; (c) the quantities of As, Ba, Co, Sb, Cr, and V do not represent toxicological concerns; (d) the examination of the estimated Al and Fe quantities recovered in infusions in the conditions of usual daily tea consumption is below the Tolerable Daily Intake values. The strategy of cultivation of medicinal plants in unpolluted areas is efficient and beneficial. However, individual plants ability to concentrate preferentially certain elements suggests controlling the contamination level of raw materials.

Design, synthesis and pharmaco-toxicological assessment of 5-mercapto-1,2,4-triazole derivatives with antibacterial and antiproliferative activity.

The extensive biochemical research of multiple types of cancer has revealed important enzymatic signaling pathways responsible for tumor occurrence and progression, thus compelling the need for the discovery of new means with which to block these signaling cascades. The phosphoinositide 3-kinase/ protein kinase B (PI3K/AKT) pathway, which plays an important role in maintaining relevant cellular functions, exhibits various alterations in common human cancers, thus representing a suitable target in cancer treatment. Molecules bearing the 1,2,4-triazole moiety are known to possess multiple biological activities, including anticancer activity. The current study used molecular docking in the design of 5-mercapto-1,2,4-triazole derivatives with antiproliferative activity targeting the PI3K/AKT pathway. Three structures emerged as the result of this method, which indicated for these a highly favorable accommodation within the active binding site of PI3K protein, thus acting as potential PI3K inhibitors, and hence interfering with the above-mentioned pathway. The molecules were synthesized and their chemical structure was confirmed. The antiproliferative activity of these compounds was tested on 4 cancer cell lines (A375, B164A5, MDA-MB-231 and A549) and on normal human keratinocytes (HaCaT) by in vitro alamarBlue assay. The 3 compounds revealed antitumor activity against the breast cancer cell line (MDA-MB-231) and reduced toxicity on the normal cell line. The antibacterial activity of the compounds was also tested in vitro on Gram-positive and Gram-negative bacterial strains, revealing moderate activity.

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing.

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications.

ColBioS-FlavRC: a collection of bioselective flavonoids and related compounds filtered from high-throughput screening outcomes.

Flavonoids, the vastest class of natural polyphenols, are extensively investigated for their multiple benefits on human health. Due to their physicochemical or biological properties, many representatives are considered to exhibit low selectivity among various protein targets or to plague high-throughput screening (HTS) outcomes. The aim of this study is to highlight reliable, bioselective compounds sharing flavonoidic scaffolds in HTS experiments. A filtering scheme was applied to remove undesired flavonoids (and related compounds) from confirmatory PubChem bioassays. A number of 433 compounds addressing various protein targets form the core of the collection of bioselective flavonoids and related compounds (ColBioS-FlavRC). With an additional set of 2908 inactive related compounds, ColBioS-FlavRC offers the grounds for method optimization and validation. We exemplified the use of ColBioS-FlavRC by pharmacophore modeling, subsequently (externally) validated for virtual screening purposes. The early enrichment capabilities of the pharmacophore hypotheses were measured by means of the median exponential retriever operating curve enrichment (MeROCE), a suited metric in comparative evaluations of virtual screening methods. ColBioS-FlavRC is available in the Supporting Information and is freely accessible for further studies.

PLS and shape-based similarity analysis of maleimides--GSK-3 inhibitors.

CONTEXT: Glycogen synthase kinase-3 (GSK-3) overactivity was correlated with several pathologies including type 2 diabetes mellitus, Alzheimer's disease, cancer, inflammation, obesity, etc. OBJECTIVE: The aim of the current investigation was to model the inhibitory activity of maleimide derivatives--inhibitors of GSK-3, to evaluate the impact of alignment on statistical performances of the Quantitative Structure-Activity Relationship (QSAR) and the effect of the template on shape-similarity--binding affinity relationship. MATERIALS AND METHODS: Dragon descriptors were used to generate Projection to Latent Structures (PLS) models in order to identify the structural prerequisites of maleimides to inhibit GSK-3. Additionally, shape/volume structural analysis of binding site interactions was evaluated. RESULTS: Reliable statistics R(2)(Y(CUM)) = 0.938/0.920, Q((2)(Y)(CUM)) = 0.866/0.838 for aligned and alignment free QSAR models and significant (Pearson, Kendall and Spearman) correlations between shape/volume similarity and affinities were obtained. DISCUSSION AND CONCLUSIONS: The crucial structural features modulating the activity of maleimides include topology, charge, geometry, 2D autocorrelations, 3D-MoRSE as well as shape/volume and molecular flexibility.

Retrospective group fusion similarity search based on eROCE evaluation metric.

In this study, a simple evaluation metric, denoted as eROCE was proposed to measure the early enrichment of predictive methods. We demonstrated the superior robustness of eROCE compared to other known metrics throughout several active to inactive ratios ranging from 1:10 to 1:1000. Group fusion similarity search was investigated by varying 16 similarity coefficients, five molecular representations (binary and non-binary) and two group fusion rules using two reference structure set sizes. We used a dataset of 3478 actives and 43,938 inactive molecules and the enrichment was analyzed by means of eROCE. This retrospective study provides optimal similarity search parameters in the case of ALDH1A1 inhibitors.

PLS-DA - Docking Optimized Combined Energetic Terms (PLSDA-DOCET) protocol: a brief evaluation.

Docking studies have become popular approaches in drug design, where the binding energy of the ligand in the active site of the protein is estimated by a scoring function. Many promising techniques were developed to enhance the performance of scoring functions including the fusion of multiple scoring functions outcomes into a so-called consensus scoring function. Hereby, we evaluated the target oriented consensus technique using the energetic terms of several scoring functions. The approach was denoted PLSDA-DOCET. Optimization strategies for consensus energetic terms and scoring functions based on ROC metric were compared to classical rigid docking and to ligand-based similarity search methods comprising 2D fingerprints and ROCS. The ROCS results indicate large performance variations depending on the biological target. The AUC-based strategy of PLSDA-DOCET outperformed the other docking approaches regarding simple retrieval and scaffold-hopping. The superior performance of PLSDA-DOCET protocol relative to single and combined scoring functions was validated on an external test set. We found a relative low mean correlation of the ranks of the chemotypes retrieved by the PLSDA-DOCET protocol and all the other methods employed here.

Skin permeation rate as a function of chemical structure.

Multilinear and nonlinear QSAR models were built for the skin permeation rate (Log K(p)) of a set of 143 diverse compounds. Satisfactory models were obtained by three approaches applied: (i) CODESSA PRO, (ii) Neural Network modeling using large pools of theoretical molecular descriptors, and (iii) ISIDA modeling based on fragment descriptors. The predictive abilities of the models were assessed by internal and external validations. The descriptors involved in the equations are discussed from the physicochemical point of view to illuminate the factors that influence skin permeation.

MTD-PLS: a PLS variant of the minimal topologic difference method. III. Mapping interactions between estradiol derivatives and the alpha estrogenic receptor.

A homogeneous collection of 45 estrogen agonist derivatives with relative binding affinities measured to the estrogen receptor from Ratus norvegicus was used. The quantitative structure-activity relationships were derived using an improved minimal topologic difference (MTD) method in a partial least-squares (PLS) variant. The spatially assigned analysis of fragment properties can provide receptor site maps, within the limits of the existing series. A steric misfit was found for the steroidal position 2; benefic hydrophobic and van der Waals (enhanced by high polarizability) interactions were found for the 17alpha-CH=CH-X group. MTD-PLS mapping results are confirmed by the experimentally derived estradiol-estrogen receptor binding site contacts (based on X-ray crystallography). Our results suggest that this MTD-PLS method can yield useful results for interactions with receptors of unknown 3D structure and, generally, for the steric rigidity of receptor sites.

MTD-PLS: A PLS-based variant of the MTD method. 2. Mapping ligand-receptor interactions. Enzymatic acetic acid esters hydrolysis.

The PLS variant of the MTD method (T. I. Oprea et al., SAR QSAR Environ. Res. 2001, 12, 75-92) was applied to a series of 25 acetylcholinesterase hydrolysis substrates. Statistically significant MTD-PLS models (q(2) between 0.7 and 0.8) are in agreement with previous MTD models, with the advantage that local contributions are understood beyond the occupancy/nonoccupancy interpretation in MTD. A "chemically intuitive" approach further forces MTD-PLS coefficients to assume only negative (or zero) values for fragmental volume descriptors and positive (or zero) values for fragmental hydrophobicity descriptors. This further separates the various kinds of local interactions at each vertex of the MTD hypermolecule, making this method suitable for medicinal chemistry synthesis planning.