Maria Dichiara

Development of a Sigma-2 Receptor affinity filter through a Monte Carlo based QSAR analysis

Abstract For the first time in sigma‐2 (&sgr;2) receptor field, a quantitative structure–activity relationship (QSAR) model has been built using pKi values of the whole set of known selective &sgr;2 receptor ligands (548 compounds), taken from the Sigma‐2 Receptor Selective Ligands Database (S2RSLDB) (http://www.researchdsf.unict.it/S2RSLDB/), through the Monte Carlo technique and employing the software CORAL. The model has been developed by using a large and structurally diverse set of compounds, allowing for a prediction of different populations of chemical compounds endpoint (&sgr;2 receptor pKi). The statistical quality reached, suggested that model for pKi determination is robust and possesses a satisfactory predictive potential. The statistical quality is high for both visible and invisible sets. The screening of the FDA approved drugs, external to our dataset, suggested that sixteen compounds might be repositioned as &sgr;2 receptor ligands (predicted pKi ≥ 8). A literature check showed that six of these compounds have already been tested for affinity at &sgr;2 receptor and, of these, two (Flunarizine and Terbinafine) have shown an experimental &sgr;2 receptor pKi > 7. This suggests that this QSAR model may be used as focusing screening filter in order to prospectively find or repurpose new drugs with high affinity for the &sgr;2 receptor, and overall allowing for an enhanced hit rate respect to a random screening. Graphical abstract Figure. No Caption available.

Sigma-2 receptor ligands QSAR model dataset

The data have been obtained from the Sigma-2 Receptor Selective Ligands Database (S2RSLDB) and refined according to the QSAR requirements. These data provide information about a set of 548 Sigma-2 (σ2) receptor ligands selective over Sigma-1 (σ1) receptor. The development of the QSAR model has been undertaken with the use of CORAL software using SMILES, molecular graphs and hybrid descriptors (SMILES and graph together). Data here reported include the regression for σ2 receptor pKi QSAR models. The QSAR model was also employed to predict the σ2 receptor pKi values of the FDA approved drugs that are herewith included.

Recent advances in drug discovery of phototherapeutic non-porphyrinic anticancer agents

In the search of novel strategies for the treatment of cancer, photodynamic therapy (PDT) has emerged as an effective, safe for repeated use, and non-invasive method. This technique involves the use of two major non-toxic components, a photosensitizer (PS) and a visible or near-infrared (NIR) light source, combined to induce cellular damage in an oxygen-dependent or -independent manner. Macrocyclic compounds, involving porphyrin and their derivatives, represent the major class of PS agents used in PDT. However, due to the drawbacks associated with these PS, like photosensitivity, dark toxicity, and low wavelength absorbance, new classes of PS appear to be needed. This review summarizes over the recent advances in drug discovery of non-porphyrinic PS suitable as anticancer therapeutics in PDT. The different compounds are grouped by chemical classes and discussed in terms of phototoxicity, together with the critical aspects of design and structure-activity relationship.

Heme Oxygenase Database (HemeOxDB) and QSAR Analysis of Isoform 1 Inhibitors

Due to increasing interest in the field of heme oxygenases (HOs), we built a ligand database called HemeOxDB that includes the entire set of known HO‐1 and HO‐2 inhibitors, resulting in more than 400 compounds. The HemeOxDB is available online at http://www.researchdsf.unict.it/hemeoxdb/, and having a robust search engine allows end users to build complex queries, sort tabulated results, and generate color‐coded two‐ and three‐dimensional graphs. This database will grow to be a tool for the design of potent and selective HO‐1 or HO‐2 inhibitors. We were also interested in virtually searching for alternative inhibitors, and, for the first time in the field of HOs, a quantitative structure–activity relationship (QSAR) model was built using half‐maximal inhibitory concentration (IC50) values of the whole set of known HO‐1 inhibitors, taken from the HemeOxDB and employing the Monte Carlo technique. The statistical quality suggested that the model is robust and possesses desirable predictive potential. The screening of US Food and Drug Administration (FDA)‐approved drugs, external to our dataset, suggested new predicted inhibitors, opening the way for replacing imidazole groups. The HemeOxDB and the QSAR model reported herein may help in prospectively identifying or repurposing new drugs with optimal structural attributes for HO enzyme inhibition.

Comprehensive data on a 2D-QSAR model for Heme Oxygenase isoform 1 inhibitors

The data have been obtained from the Heme Oxygenase Database (HemeOxDB) and refined according to the 2D-QSAR requirements. These data provide information about a set of more than 380 Heme Oxygenase-1 (HO-1) inhibitors. The development of the 2D-QSAR model has been undertaken with the use of CORAL software using SMILES, molecular graphs and hybrid descriptors (SMILES and graph together). The 2D-QSAR model regressions for HO-1 half maximal inhibitory concentration (IC50) expressed as pIC50 (pIC50=−LogIC50) are here included. The 2D-QSAR model was also employed to predict the HO-1 pIC50values of the FDA approved drugs that are herewith reported.

Adipocyte fatty acid binding protein 4 (FABP4) inhibitors. A comprehensive systematic review

Small molecule inhibitors of adipocyte fatty acid binding protein 4 (FABP4) have attracted interest following the recent publications of beneficial pharmacological effects of these compounds. FABP4 is predominantly expressed in macrophages and adipose tissue where it regulates fatty acids (FAs) storage and lipolysis and is an important mediator of inflammation. In the past years, hundreds FABP4 inhibitors have been synthesized for effective atherosclerosis and diabetes treatments, including derivatives of niacin, quinoxaline, aryl-quinoline, bicyclic pyridine, urea, aromatic compounds and other novel heterocyclic compounds. This review provides an overview of the synthesized and discovered molecules as adipocyte fatty acid binding protein 4 inhibitors (FABP4is) since the synthesis of the putative FABP4i, BMS309403, highlighting the interactions of the different classes of inhibitors with the targets.

Hyphenated 3D-QSAR statistical model-scaffold hopping analysis for the identification of potentially potent and selective sigma-2 receptor ligands

A 3D quantitative structure-activity relationship (3D-QSAR) model for predicting the σ2 receptor affinity has been constructed with the aim of providing a useful tool for the identification, design, and optimization of novel σ2 receptor ligands. The model has been built using a set of 500 selective σ2 receptor ligands recovered from the sigma-2 receptor selective ligand database (S2RSLDB) and developed with the software Forge. The present model showed high statistical quality as confirmed by its robust predictive potential and satisfactory descriptive capability. The drawn up 3D map allows for a prompt visual comprehension of the electrostatic, hydrophobic, and shaping features underlying σ2 receptor ligands interaction. A theoretic approach for the generation of new lead compounds with optimized σ2 receptor affinity has been performed by means of scaffold hopping analysis. Obtained results further confirmed the validity of our model being some of the identified moieties have already been successfully employed in the development of potent σ2 receptor ligands. For the first time is herein reported a 3D-QSAR model which includes a number of chemically diverse σ2 receptor ligands and well accounts for the individual ligands affinities. These features will ensure prospectively advantageous applications to speed up the identification of new potent and selective σ2 receptor ligands.

Identification of Potentially Potent Heme Oxygenase 1 Inhibitors through 3D-QSAR Coupled to Scaffold-Hopping Analysis

A 3D quantitative structure–activity relationship (3D‐QSAR) model for predicting the activity of heme oxygenase 1 (HO‐1) inhibitors was constructed with the aim of providing a useful tool for the identification, design, and optimization of novel HO‐1 inhibitors. The model was built using a set of 222 HO‐1 inhibitors recovered from the Heme Oxygenase Database (HemeOxDB) and developed with the software Forge. The present model showed high statistical quality, as confirmed by its robust predictive potential and satisfactory descriptive capability. The drawn‐up 3D map enables prompt visual comprehension of the electrostatic, hydrophobic, and shaping features underlying the interactions with HO‐1 inhibitors. A theoretical approach for the generation of new lead compounds was performed by means of scaffold‐hopping analysis. For the first time, a 3D‐QSAR model is reported for this target, and was built with a number of chemically diverse HO‐1 inhibitors; the model also accounts well for individual ligand affinities. The new model contains all of the inhibitors published to date with high potency toward the selected target and contains a complete pharmacophore description of the binding cavity of HO‐1. These features will ensure application in accelerating the identification of new potent and selective HO‐1 inhibitors.

Repurposing of Human Kinase Inhibitors in Neglected Protozoan Diseases

Human African trypanosomiasis (HAT), Chagas disease, and leishmaniasis belong to a group of infectious diseases known as neglected tropical diseases and are induced by infection with protozoan parasites named trypanosomatids. Drugs in current use have several limitations, and therefore new candidate drugs are required. The majority of current therapeutic trypanosomatid targets are enzymes or cell‐surface receptors. Among these, eukaryotic protein kinases are a major group of protein targets whose modulation may be beneficial for the treatment of neglected tropical protozoan diseases. This review summarizes the finding of new hit compounds for neglected tropical protozoan diseases, by repurposing known human kinase inhibitors on trypanosomatids. Kinase inhibitors are grouped by human kinase family and discussed according to the screening (target‐based or phenotypic) reported for these compounds on trypanosomatids. This collection aims to provide insight into repurposed human kinase inhibitors and their importance in the development of new chemical entities with potential beneficial effects on the diseases caused by trypanosomatids.

(+)-Methyl (1R,2S)-2-{[4-(4-Chlorophenyl)-4-hydroxypiperidin-1-yl]methyl}-1-phenylcyclopropanecarboxylate [(+)-MR200] Derivatives as Potent and Selective Sigma Receptor Ligands: Stereochemistry and Pharmacological Properties

Methoxycarbonyl-1-phenyl-2-cyclopropylmethyl based derivatives cis-(+)-1a [cis-(+)-MR200], cis-(-)-1a [cis-(-)-MR201], and trans-(±)-1a [trans-(±)-MR204], have been identified as new potent sigma (σ) receptor ligands. In the present paper, novel enantiomerically pure analogues were synthesized and optimized for their σ receptor affinity and selectivity. Docking studies rationalized the results obtained in the radioligand binding assay. Absolute stereochemistry was unequivocally established by X-ray analysis of precursor trans-(+)-5a as camphorsulfonyl derivative 9. The most promising compound, trans-(+)-1d, showed remarkable selectivity over a panel of more than 15 receptors as well as good chemical and enzymatic stability in human plasma. An in vivo evaluation evidenced that trans-(+)-1d, in contrast to trans-(-)-1d, cis-(+)-1d, or cis-(-)-1d, which behave as σ1 antagonists, exhibited a σ1 agonist profile. These data clearly demonstrated that compound trans-(+)-1d, due to its σ1 agonist activity and favorable receptor selectivity and stability, provided an useful tool for the study of σ1 receptors.