Navigating pharmacophore space to identify activity discontinuities: a case study with BCR-ABL.

The exploration of chemical space is a fundamental aspect of chemoinformatics, particularly when one explores a large compound data set to relate chemical structures with molecular properties. In this study, we extend our previous work on chemical space visualization at the pharmacophoric level. Instead of using conventional binary classification of affinity (active vs inactive), we introduce a refined approach that categorizes compounds into four distinct classes based on their activity levels: super active, very active, active, and inactive. This classification enriches the color scheme applied to pharmacophore space, where the color representation of a pharmacophore hypothesis is driven by the associated compounds. Using the BCR-ABL tyrosine kinase as a case study, we identified intriguing regions corresponding to pharmacophore activity discontinuities, providing valuable insights for structure-activity relationships analysis.

Towards a partial order graph for interactive pharmacophore exploration: extraction of pharmacophores activity delta.

This paper presents a novel approach called Pharmacophore Activity Delta for extracting outstanding pharmacophores from a chemogenomic dataset, with a specific focus on a kinase target known as BCR-ABL. The method involves constructing a Hasse diagram, referred to as the pharmacophore network, by utilizing the subgraph partial order as an initial step, leading to the identification of pharmacophores for further evaluation. A pharmacophore is classified as a 'Pharmacophore Activity Delta' if its capability to effectively discriminate between active vs inactive molecules significantly deviates (by at least δ standard deviations) from the mean capability of its related pharmacophores. Among the 1479 molecules associated to BCR-ABL binding data, 130 Pharmacophore Activity Delta were identified. The pharmacophore network reveals distinct regions associated with active and inactive molecules. The study includes a discussion on representative key areas linked to different pharmacophores, emphasizing structure-activity relationships.

New Pharmacophore Fingerprints and Weight-matrix Learning for Virtual Screening. Application to Bcr-Abl Data.

In this work, we propose to analyze the potential of a new type of pharmacophoric descriptors coupled to a novel feature transformation technique, called Weight-Matrix Learning (WML, based on a feed-forward neural network). The application concerns virtual screening on a tyrosine kinase named BCR-ABL. First, the compounds were described using three different families of descriptors: our new pharmacophoric descriptors, and two circular fingerprints, ECFP4 and FCFP4. Afterwards, each of these original molecular representations were transformed using either an unsupervised WML method or a supervised one. Finally, using these transformed representations, K-Means clustering algorithm was applied to automatically partition the molecules. Combining our pharmacophoric descriptors with supervised Weight-Matrix Learning (SWMLR ) leads to clearly superior results in terms of several quality measures.

Deciphering a Pharmacophore Network: A Case Study Using BCR-ABL Data.

This paper introduces a general method that can be used to create groups of pharmacophores to support their further in-depth analysis. A BCR-ABL molecular dataset was used to calculate graph edit distances between pharmacophores and led to their organization into a novel pharmacophore network. The application of a graph layout algorithm allowed us to discriminate between the pharmacophores associated with active compounds and those associated with inactive compounds. A clustering approach was used to refine the partitioning by grouping the pharmacophores based on their structures, activities, and binding modes. Analysis of a newly spatialized pharmacophore network provided us with critical insight into structure-activity relationships, most notably those that revealed distinctions between activity classes and chemical families. As shown, this method permits us to identify families of structurally homogeneous pharmacophores.

Hot-Spots of Mcl-1 Protein.

Protein-protein interactions (PPIs) control many important physiological processes within human cells. Apoptosis or programmed cell death is closely regulated by pro- and antiapoptotic signals. Dysregulation of this homeostasis is implicated in tumorigenesis and acquired resistance to treatments. The emerging importance of Mcl-1 protein in chemotherapeutic resistance makes it a high priority therapeutic target. Targeting PPIs associated with Mcl-1 presents many challenges for the design of inhibitors. This review focuses on the characterization of the Mcl-1 hot-spots which are related to four hydrophobic pockets P1-P4 and one major electrostatic interaction. Analysis of structural data highlights the high importance of the P2/P3 pockets for the binding of nonpeptide ligands. In order to guide medicinal chemists into making more selective and potent Mcl-1 inhibitors, the Mcl-1 protein is compared to other antiapoptotic proteins.

Structure-guided design of pyridoclax derivatives based on Noxa / Mcl-1 interaction mode.

Protein-protein interactions are attractive targets because they control numerous cellular processes. In oncology, apoptosis regulating Bcl-2 family proteins are of particular interest. Apoptotic cell death is controlled via PPIs between the anti-apoptotic proteins hydrophobic groove and the pro-apoptotic proteins BH3 domain. In ovarian carcinoma, it has been previously demonstrated that Bcl-xL and Mcl-1 cooperate to protect tumor cells against apoptosis. Moreover, Mcl-1 is a key regulator of cancer cell survival and is a known resistance factor to Bcl-2/Bcl-xL pharmacological inhibitors making it an attractive therapeutic target. Here, using a structure-guided design from the oligopyridine lead Pyridoclax based on Noxa/Mcl-1 interaction we identified a new derivative, active at lower concentration as compared to Pyridoclax. This new derivative selectively binds to the Mcl-1 hydrophobic groove and releases Bak and Bim from Mcl-1 to induce cell death and sensitize cancer cells to Bcl-2/Bcl-xL targeting strategies.

The Pharmacophore Network: A Computational Method for Exploring Structure-Activity Relationships from a Large Chemical Data Set.

Historically, structure-activity relationship (SAR) analysis has focused on small sets of molecules, but in recent years, there has been increasing efforts to analyze the growing amount of data stored in public databases like ChEMBL. The pharmacophore network introduced herein is dedicated to the organization of a set of pharmacophores automatically discovered from a large data set of molecules. The network navigation allows to derive essential tasks of a drug discovery process, including the study of the relations between different chemical series, the analysis of the influence of additional chemical features on the compounds' activity, and the identification of diverse binding modes. This paper describes the method used to construct the pharmacophore network, and a case study dealing with BCR-ABL exemplifies its usage for large-scale SAR analysis. Thanks to a benchmarking study, we also demonstrate that the selection of a subset of representative pharmacophores can be used to conduct classification tasks.

Toward Understanding Mcl-1 Promiscuous and Specific Binding Mode.

Mcl-1, which is an anti-apoptotic member of the Bcl-2 protein family, is overexpressed in various cancers and promotes the aberrant survival of tumor cells. To inhibit Mcl-1, and initiate apoptosis, an interaction between BH3-only proteins and Mcl-1 anti-apoptotic protein is necessary. These protein-protein interactions exhibit some selectivity: Mcl-1 binds specifically to Noxa, whereas Bim and Puma bind strongly to all anti-apoptotic proteins. Even if the three-dimensional (3D) structures of several Mcl-1/BH3-only complexes have been solved, the BH3-only binding specificity to Mcl-1 is still not completely understood. In this study, molecular dynamics simulations were used to elucidate the molecular basis of the interactions with Mcl-1. Our results corroborate the importance of four conserved hydrophobic residues and a conserved aspartic acid on BH3-only as a common binding pattern. Furthermore, our results highlight the contribution of the fifth hydrophobic residue in the C-terminal part and a negatively charged patch in the N-terminal of BH3-only peptides as important for their fixation to Mcl-1. We hypothesize that this negatively charged patch will be an Mcl-1 specific binding pattern.

The Arg-Phe-amide peptide 26RFa/glutamine RF-amide peptide and its receptor: IUPHAR Review 24.

The RFamide neuropeptide 26RFa was first isolated from the brain of the European green frog on the basis of cross-reactivity with antibodies raised against bovine neuropeptide FF (NPFF). 26RFa and its N-terminally extended form glutamine RF-amide peptide (QRFP) have been identified as cognate ligands of the former orphan receptor GPR103, now renamed glutamine RF-amide peptide receptor (QRFP receptor). The 26RFa/QRFP precursor has been characterized in various mammalian and non-mammalian species. In the brain of mammals, including humans, 26RFa/QRFP mRNA is almost exclusively expressed in hypothalamic nuclei. The 26RFa/QRFP transcript is also present in various organs especially in endocrine glands. While humans express only one QRFP receptor, two isoforms are present in rodents. The QRFP receptor genes are widely expressed in the CNS and in peripheral tissues, notably in bone, heart, kidney, pancreas and testis. Structure-activity relationship studies have led to the identification of low MW peptidergic agonists and antagonists of QRFP receptor. Concurrently, several selective non-peptidic antagonists have been designed from high-throughput screening hit optimization. Consistent with the widespread distribution of QRFP receptor mRNA and 26RFa binding sites, 26RFa/QRFP exerts a large range of biological activities, notably in the control of energy homeostasis, bone formation and nociception that are mediated by QRFP receptor or NPFF2. The present report reviews the current knowledge concerning the 26RFa/QRFP-QRFP receptor system and discusses the potential use of selective QRFP receptor ligands for therapeutic applications.

Non a Priori Automatic Discovery of 3D Chemical Patterns: Application to Mutagenicity.

This article introduces a new type of structural fragment called a geometrical pattern. Such geometrical patterns are defined as molecular graphs that include a labelling of atoms together with constraints on interatomic distances. The discovery of geometrical patterns in a chemical dataset relies on the induction of multiple decision trees combined in random forests. Each computational step corresponds to a refinement of a preceding set of constraints, extending a previous geometrical pattern. This paper focuses on the mutagenicity of chemicals via the definition of structural alerts in relation with these geometrical patterns. It follows an experimental assessment of the main geometrical patterns to show how they can efficiently originate the definition of a chemical feature related to a chemical function or a chemical property. Geometrical patterns have provided a valuable and innovative approach to bring new pieces of information for discovering and assessing structural characteristics in relation to a particular biological phenotype.

A Computational Selection of Metabolite Biomarkers Using Emerging Pattern Mining: A Case Study in Human Hepatocellular Carcinoma.

The biomarker development in metabolomics aims at discriminating diseased from normal subjects and at creating a predictive model that can be used to diagnose new subjects. From a case study on human hepatocellular carcinoma (HCC), we studied for the first time the potential usefulness of the emerging patterns (EPs) that come from the data mining domain. When applied to a metabolomics data set labeled with two classes (e.g., HCC patients vs healthy subjects), EP mining can capture differentiating combinations of metabolites between the two classes. We observed that the so-called jumping emerging patterns (JEPs), which correspond to the combinations of metabolites that occur in only one of the two classes, achieved better performance than individual biomarkers. Particularly, the implementation of the JEPs in a rules-based diagnostic tool drastically reduced the false positive rate, i.e., the rate of healthy subjects predicted as HCC patients.

Conformation and Dynamics of Human Urotensin II and Urotensin Related Peptide in Aqueous Solution.

Conformation and dynamics of the vasoconstrictive peptides human urotensin II (UII) and urotensin related peptide (URP) have been investigated by both unrestrained and enhanced-sampling molecular-dynamics (MD) simulations and NMR spectroscopy. These peptides are natural ligands of the G-protein coupled urotensin II receptor (UTR) and have been linked to mammalian pathophysiology. UII and URP cannot be characterized by a single structure but exist as an equilibrium of two main classes of ring conformations, open and folded, with rapidly interchanging subtypes. The open states are characterized by turns of various types centered at K8Y9 or F6W7 predominantly with no or only sparsely populated transannular hydrogen bonds. The folded conformations show multiple turns stabilized by highly populated transannular hydrogen bonds comprising centers F6W7K8 or W7K8Y9. Some of these conformations have not been characterized previously. The equilibrium populations that are experimentally difficult to access were estimated by replica-exchange MD simulations and validated by comparison of experimental NMR data with chemical shifts calculated with density-functional theory. UII exhibits approximately 72% open:28% folded conformations in aqueous solution. URP shows very similar ring conformations as UII but differs in an open:folded equilibrium shifted further toward open conformations (86:14) possibly arising from the absence of folded N-terminal tail-ring interaction. The results suggest that the different biological effects of UII and URP are not caused by differences in ring conformations but rather by different interactions with UTR.

First evidence that oligopyridines, α-helix foldamers, inhibit Mcl-1 and sensitize ovarian carcinoma cells to Bcl-xL-targeting strategies.

Apoptosis control defects such as the deregulation of Bcl-2 family member expression are frequently involved in chemoresistance. In ovarian carcinoma, we previously demonstrated that Bcl-xL and Mcl-1 cooperate to protect cancer cells against apoptosis and their concomitant inhibition leads to massive apoptosis even in the absence of chemotherapy. Whereas Bcl-xL inhibitors are now available, Mcl-1 inhibition, required to sensitize cells to Bcl-xL-targeting strategies, remains problematic. In this context, we designed and synthesized oligopyridines potentially targeting the Mcl-1 hydrophobic pocket, evaluated their capacity to inhibit Mcl-1 in live cells, and implemented a functional screening assay to evaluate their ability to sensitize ovarian carcinoma cells to Bcl-xL-targeting strategies. We established structure-activity relationships and focused our attention on MR29072, named Pyridoclax. Surface plasmon resonance assay demonstrated that pyridoclax directly binds to Mcl-1. Without cytotoxic activity when administered as a single agent, pyridoclax induced apoptosis in combination with Bcl-xL-targeting siRNA or with ABT-737 in ovarian, lung, and mesothelioma cancer cells.

Dual histamine H3R/serotonin 5-HT4R ligands with antiamnesic properties: pharmacophore-based virtual screening and polypharmacology.

In recent years, preclinical and clinical studies have generated considerable interest in the development of histamine H3 receptor (H3R) antagonists as novel treatment for degenerative disorders associated with impaired cholinergic function. To identify novel scaffolds for H3R antagonism, a common feature-based pharmacophore model was developed and used to screen the 17,194 compounds of the CERMN (Centre d'Etudes et de Recherche sur le Médicament de Normandie) chemical library. Out of 268 virtual hits which have been gathered in 34 clusters, we were particularly interested in tricyclic derivatives also exhibiting a potent 5HT4R affinity. Benzo[h][1,6]naphthyridine derivatives showed the highest H3R affinity, and compound 17 (H3R Ki = 41.6 nM; 5-HT4R Ki = 208 nM) completely reversed the amnesiant effect of scopolamine at 3 mg/kg in a spatial working memory experiment. For the first time we demonstrated the feasibility to combine H3R and 5-HT4R activities in a single molecule, raising the exciting possibility that dual H3R antagonist/5HT4R agonist have potential for the treatment of neurodegenerative diseases such as Alzheimer's disease.

Assessment of the genotoxic and carcinogenic potentials of 3-aminothiophene derivatives using in vitro and in silico methodologies.

Thiophene derivatives, a class of compounds widely used in products such as pharmaceuticals, agrochemicals or dyestuffs, represent chemicals of concern. Indeed, the thiophene ring is often considered as a structural moiety that may be involved in toxic effects in humans. We primarily focus on the genotoxic/mutagenic and carcinogenic potentials of the methyl 3-amino-4-methylthiophene-2-carboxylate (1), a precursor of the articaine local anesthetic (4) which falls within the scope of the European REACH (Registration, Evaluation, Authorisation and restriction of CHemicals) legislation. To discern some structure-toxicity relationships, we also studied two related compounds, namely the 3-amino 4-methylthiophene (2) and the 2-acetyl 4-chlorothiophene (3). Techniques employed to assess mutagenic and DNA-damaging effects involved the Salmonella mutagenicity assay (or Ames test) and the single-cell gel electrophoresis assay (or Comet assay). In the range of tested doses, none of these derivatives led to a positive response in the Ames tests and DNA damage was only observed in the Comet assay after high concentration exposure of 2. The study of their carcinogenic potential using the in vitro SHE (Syrian Hamster Embryo) cell transformation assay (CTA) highlighted the activity of compound 2. A combination of experimental data with in silico predictions of the reactivity of thiophene derivatives towards cytochrome P450 (CYP450), enabled us to hypothesize possible pathways leading to these toxicological profiles.

Prediction of acute toxicity in fish by using QSAR methods and chemical modes of action.

Three quantitative structure-activity relationship (QSAR) models were evaluated for their power to predict the toxicity of chemicals in two datasets: (1) EPAFHM (US Environmental Protection Agency-Fathead Minnow) and (2) derivatives having a high production volume (HPV), as compiled by the European Chemical Bureau. For all three QSAR models, the quality of the predictions was found to be highly dependent on the mode of action of the chemicals. An analysis of outliers from the three models gives some clues for improving the QSAR models. Two classification methods, Toxtree and a Bayesian approach with fingerprints as descriptors, were also analyzed. Predictions following the Toxtree classification for narcosis were good, especially for the HPV set. The learning model (Bayesian approach) produced interesting results for the EPAFHM dataset but gave lower quality predictions for the HPV set.

Definition of new pharmacophores for nonpeptide antagonists of human urotensin-II. Comparison with the 3D-structure of human urotensin-II and URP.

Starting from nonpeptide agonists and antagonists of human urotensin-II (hU-II), several pharmacophores were designed and compared to the structure of hU-II. NMR and dynamic studies were realized on hU-II and urotensin-II-related peptide to check the conformation flexibilities of these peptides and the relationships between their potential 3D structures and the pharmacophores. In parallel, a virtual screening was carried out, leading to the discovery of six new derivatives with micromolar affinities. This last result shows the interest of these pharmacophores for the discovery of new ligands.

Synthesis and biological evaluation of five-membered heterocycles fused to cyclopenta[c]thiophene as new antitumor agents.

A series of 10 derivatives 2-6 issued from the fusion of various five-membered heterocycles to cyclopenta[c]thiophene were evaluated for potential anticancer activity in the NCI's in vitro human disease-oriented tumor cell line screening panel that consisted of 60 human tumor cell lines arranged in nine subpanels, representing diverse histologies. Among these tested compounds, four were found to be cytotoxic allowing us to point out some structure-activity relationships. The oxazolidinone derivatives 2a-c displayed further in vivo antitumor activity in the hollow fiber assay and standard xenograft testing developed at the NCI.

New benzo[h][1,6]naphthyridine and azepino[3,2-c]quinoline derivatives as selective antagonists of 5-HT4 receptors: binding profile and pharmacological characterization.

A series of benzo[h][1,6]naphthyridine and azepino[3,2-c]quinoline derivatives were prepared and evaluated to determine the necessary requirements for high affinity on the 5-HT(4) receptors and high selectivity versus other receptors. The compounds were synthesized by substituting the chlorine atom of benzonaphthyridines and azepinoquinolines with various N-alkyl-4-piperidinylmethanolates. They were evaluated in binding assays with [(3)H]GR 113808 as the 5-HT(4) receptor radioligand. The affinity values (K(i) or inhibition percentages) depended upon the substituent on the aromatic ring on one hand and the substituent on the lateral piperidine chain on the other hand. A chlorine atom produced a marked drop in activity while a N-propyl or N-butyl group gave compounds with nanomolar affinities (1 < K(i) < 10 nM). Among the most potent ligands (3a, 4a, 5a), 4a was selected on the basis of its high affinity and selectivity for pharmacological screening and was evaluated in vivo in specific tests. This compound reveals itself as an antagonist/low partial agonist in the COS-7 cells stably expressing the 5-HT(4(a)) receptor. Derivative 4a also showed in vivo potent analgesic activity in the writhing test at very low doses.

Synthesis and biological evaluation of cyclopenta[c]thiophene related compounds as new antitumor agents.

A series of 22 cyclopenta[c]thiophene related compounds was obtained by the pharmacomodulation of 6-amino-5,6-dihydro-4H-cyclopenta[c]thiophen-4-ones 1a-g. All compounds were evaluated for potential anticancer activity in the NCI's in vitro human disease-oriented tumor cell line screening panel that consisted of 60 human tumor cell lines arranged in nine subpanels, representing diverse histologies. Among these tested compounds, seven were found to be cytotoxic, especially against leukemia cell lines, allowing us to point out some structure-activity relationships. These derivatives were further evaluated for potential in vivo anticancer activity in the hollow fiber assay developed at the NCI, which selected two compounds, 1f and 3a for standard xenograft testing.