創薬情報システムのパトコア

Exploration of Pharmacological, Metabolism and hERG Profiles of Antipsychotic Drugs

by François PETITET, Ismail IJJAAli, Elodie DUBUS,

In this study, pharmacological, biopharmaceutical and toxicological information regarding several antipsychotic drugs have been retrieved from AurSCOPE's knowledge databases in order to explore their pharmacological activity as well as their ADMET properties focused on metabolic characteristics and cardiac hERG channel blockage.

QSAR modeling of ErbB1 inhibitors

by François PETITET, Elodie DUBUS, Ismail IJJAALI,

In this application note, we illustrate the use of the AurSCOPE Kinase knowledge database to build efficient QSAR models. ErbB1 kinase will used as an example.

Revisiting traditional medicinal chemistry scaffolds by mining AurSCOPE

by Aureus Sciences,

The presented applications demonstrate that in silico profiling based on a thorough knowledge database is a fast and effective method to assess the polypharmacology of compounds and further useful for revisiting the mechanisms of action associated with traditional motives of medicinal chemistry.

Use of AurSCOPE hERG knowledgebase and Microsoft data mining tools

by François PETITET, Ismail IJJAALI, Elodie DUBUS, Olivier BOURDIN,

Herein, using a large validated dataset retrieved from Aureus' AurSCOPE hERG knowledge database and diverse two-dimensional (2D) molecular descriptors, we propose novel in silico models based upon Microsoft data mining tools to rapidly screen out potential hERG blockers.

Assessing the chemical diversity of an hsp90 database

by François PETITET, Elodie DUBUS, Ismail IJJAALI,

The 90-kDa heat shock protein (hsp90) has emerged as a new, promising target for cancer drug discovery. With the simultaneous disruption of a large range of oncogenic pathways, hsp90 inhibition results in either cytostasis or cell death. Diverse inhibitors of this molecular chaperone are currently under intensive study, and several have reached clinical trials. In the present work, patented and published structure-activity relationships on hsp90 inhibitors were organised in a database format that associates chemical structures with their biological activities.

In Vitro/In Vivo Correlation for Drug-Drug Interactions

by Xavier BOULENC, Wolfgang SCHMIDER, Olivier BARBERAN,

Simulations or predictions of DDI, bridging the gap between in vitro outcomes and clinical situation are challenging for the pharmaceutical industry, fueled by recent growth of knowledge in molecular biology, computer-based simulation/predictions, and a better understanding of the inhibition and induction mechanisms.

Prediction of in vivo drug-drug interactions involving UDP glucuronosyltranferase

by Olivier BARBERAN, Cristina LOPEZ, Estelle RAPINE, Patrice DEHANNE,

Drug-drug interactions (DDIs) can lead to severe side effects, drug toxicities and have resulted in refusal of approval, severe prescribing restrictions, and withdrawal of drugs from the market. Many DDIs are due to the co-administration of drugs that can alter drug metabolism. Glucuronidation is a major metabolism pathway, representing fifteen percent of the cleared drugs. Significant advances have been made in the last years in the identification of UDP-glucuronosyltransferases (UGT) involved in the metabolism of compounds.

Boosted regression trees to predict blood brain barrier passage

by Ismail IJJAALI, Elodie DUBUS, François PETITET,

The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules.

Assessing the Chemical and Biological Diversity of an Ion Channels Database

by François PETITET, Emmanuel BOURINET, Elodie DUBUS, Ismail IJJAALI,

The aim of the present work is to assess the chemical and biological diversity of ligands reported in scientific articles or patents to be active against ion channels targets.

In Silico Classification of hERG Channel Blockers

by André MICHEL, François PETITET, Ismail IJJAALI, Elodie DUBUS,

The blockage of the hERG potassium channel by a wide number of diverse compounds has become a major pharmacological safety concern as it can lead to sudden cardiac death. In silico models can be potent tools to screen out potential hERG blockers as early as possible during the drug-discovery process. In this study, predictive models developed using the recursive partitioning method and created using diverse datasets from 203 molecules tested on the hERG channel are described.

GPR55 as a New Cannabinoid Receptor

by André MICHEL, Mary DONLAN, François PETITET,

A recent report indicates that GPR55 may be a new cannabinoid receptor sensitive to CP55940, a rather classical cannabinoid-like structure, and not to the alkylindole WIN55212-2 as previously thought. This analysis was made on the basis of sequence similarity between a number of GPR55 subdomains and the corresponding sequences of 'classic' cannabinoid receptors, CB1 and CB, and reinforced by the patent issued by AstraZeneca showing that GPR55 is, indeed, pharmacologically a cannabinoid receptor. While the existence of additional cannabinoid receptors was suggested by several non-classical pharmacological responses (3-6), this was never clearly demonstrated.

Streamlining In Silico Compound Profiling

by Aureus Sciences,

New tools have application in drug repurposing and investigation of off-target effects.

Knowledge Management-driven Drug Discovery

by Aureus Sciences,

In all drug discovery programmes, a key for success is the ability of an organisation to take advantage of the synergies among scientists and to maximally utilise their expertise. The ability of all the discovery actors to speak (and understand) a common language and to share the same knowledge in an integrated platform is of tremendous importance.

AurSCOPE Kinase Knowledge Database: Higher Chemical Diversity for Robust Predictive Models

by François PETITET, Mary DONLAN, Nathalie LACOSTE, Elodie DUBUS, Ismail IJJAALI,

-Protein kinases are important therapeutic targets for today's drug discovery as they are implicated in many diseases including cancer and metabolic disorders.-AurSCOPE Kinase is an exhaustively annotated knowledgebase containing pertinent biological and chemical information relating to molecules tested on kinase targets.-Bemis & Murcko frameworks were used to assess the chemical diversity of AurSCOPE knowledgebases.-Different classification or regression predictive models have been generated using information extracted from AurSCOPE Kinase knowledgebase.

Can Fluorinated Molecules Influence Metabolism and Bioavailability of Drugs?

by Danièle BONNET-DELPON, Benoit CROUSSE, François PETITET, Olivier BARBERAN, Ismail IJJAALI, Elodie DUBUS, Lidia DUMITRESCU,

-Fluorinated compounds have shown an increased interest and are well recognized in medicinal chemistry and drug discovery.-20% of all marketed drugs are fluorinated compounds.-The incorporation of fluorine into drugs can modify their physico-chemicals properties such as lipophilicity, solubility, stability. All of which can influence both the pharmacodynamic and pharmacokinetic properties of drugs.-Comparation of fluorinated molecules with other halogenated molecules from Aureus database.

Hsp90 Ligands Chemical Diversity of Known Molecules and Discovery of New Potential Hits by Virtual Screening

by François PETITET, Elodie DUBUS, Mouâd ALAMI, Jean-Daniel BRION, Jean-François PEYRAT, Ismail IJJAALI, Samir MESSAOUDI, Davide AUDISIO,

The molecular chaperone Heat shock protein 90 (Hsp90) is emerging as a new exciting target for the treatment of cancer. Hsp90 plays a key role for protein regulation in cells, such as protecting proteins against aggregation, assisting refolding of damaged proteins and facilitates the folding of nascent proteins. Inhibition of Hsp90 leads to destabilization and degradation by the proteasome of various oncogenic client proteins, including Akt, Her-2, c-Met, Flt3, Raf1, Bcr-Abl, and the estrogen receptor (ER), associated to the chaperone.

Improved Strategies to Enrich Focused Libraries in Active Compounds Using Target-Oriented Databases.

by André MICHEL, François PETITET, Sophie OLLIVIER, Mary DONLAN, Isabelle GIRAUD, Ismail IJJAALI,

• Neurokinin (NK) receptor ligands represent an attractive family for validating a virtual screening strategy due to the large chemical diversity of non-peptide antagonists reported.• An extensive biological knowledge has been recorded in AurSCOPE GPCR database on neurokinin ligands allowing precise selection of compounds according to their activity or selectivity profile.• Virtual screening output is highly dependent of the pertinence of the query set chosen and the molecular fingerprints used.• Two data sets validated by experts in the field of modeling and neurokinin pharmacology as well as a dataset retrieved from AurSCOPE GPCR database have been compared.• The main purpose of this work was to study the improvement of a virtual screening strategy by enriching the chemical diversity of query sets.

Ligand selectivity on mutated human protein kinases. A literature knowledge-based approach.

by Olivier BARBERAN, Christelle MORLIERE, Ismail IJJAALI, Elodie DUBUS, Frédéric SOUVAY,

Protein kinases are a family of enzymes able to transfer an ATP phosphate to a substrate protein. Kinases are common players in cellular signaling and are particularly involved in cell differentiation, proliferation and apoptosis regulation. Protein kinases represent 2% of the proteins coded by the human genome and, approximately, 518 genes constitute the human "kinome".

Molecular Properties-Based Functional Radars for GPCR ligands

by François PETITET, Dominique NEAUD, Stéphane MARCEL, Elodie DUBUS, Ismail IJJAALI, Benjamin MORLON,

-Approximately 45 % of current pharmacopoeia acts on GPCRs and 45 % of GPCR sequences still lack of functional knowledge.-Large diversity panel for chemical entities targeting GPCRs exists but comprehension of chemical space associated with target sub-families still needs to be defined.-Navigation in the GPCR-associated chemical space benefits from the analysis of a comprehensive knowledgebase constructed from published documents.

Prediction of Drug-Drug Interactions Caused by Metabolism-Based Inhibition of CYPs using a Mechanistic Static Model

by Estelle RAPINE, Patrice DEHANNE, Olivier BARBERAN,

oThe mechanistic static model (MSM) has been well defined and used to predict drug-drug interactions (DDI) resulting from mechanism-based inhibition (MBI) via an in vitro to in vivo extrapolation (IVIVE) process. o However, a general tendency to overpredict DDIs caused by inactivators was observed when using MSM model. o Uncertainties remain not only in which parameters (kinact, KI, kdeg, [I], fm, Fg) are most important in the prediction but also which parameters values should be used. o The purpose of this study was to evaluate the impact of in vitro parameters variability on prediction caused by inactivators. DDI Predict 2009, was used to predict DDIs.

Predictions of metabolic DDIs after Intravenous administration

by Olivier BARBERAN, Xavier BOULENC, Estelle RAPINE, Patrice DEHANNE, Cristina LOPEZ,

Drug-drug interactions (DDI) caused by inhibition of cytochrome P450 have been an area of intense research. However, most of these investigations focus on the most widely used administration route : oral route. Administration of victim drug trough intravenous (IV) route is paradoxically more complex as basal clearance value (Eh without inhibitor) has to be taken into account for DDI prediction.

Scaling data from recombinant cytochromes to human liver microsomes

by Olivier BARBERAN, Estelle RAPINE, Patrice DEHANNE,

Many DDIs are due to the co-administration of another drug that can alter the drug metabolism, in particular by the inhibition of cytochromes P450 (CYP).Recombinant P450 systems are routinely used in the industry to determine the intrinsic clearances of each isozyme for a drug candidate. Anticipating potential issues through the identification and contribution of P450 isozymes implied in the metabolism of this drug at an early stage of development is a great challenge for the pharmaceutical industry.-The purpose of this study was to evaluate :• Scaling factors (abundance, RAF, ISEF) on different expression systems (baculovirus, Lymphoblastoid, E; Coli, Yeast)• Intrinsic clearance on HLM from recombinant intrinsic clearance and contribution of isoenzymes to the overall metabolism (fm(E))• Drug-drug interactions using DDI predict 2009

A Knowledge-Based Scheme for Building Efficient ADME-Tox Predictive Tools

by Aureus Sciences,

Applications of an ADME Knowledge Database for ADMET Predictive Models

by Ismail IJJAALI,

Oral presentation at ADMET Europe, 19-20 February 2008, Stockholm.

DMPK Solutions

by Aureus Sciences,

Solutions to address drug candidate DMPK issues.

AurPASS

by Aureus Sciences,

AurPASS instantly predicts biological activity profiles for your selected compounds.

AurSCOPE ADME DDI

by Aureus Sciences,

The ADME database provides the latest and most comprehensive data for structurally diverse compounds associated with known ADME properties, including human oral bioavailability, enzymes metabolism, inhibition and induction, transport, plasma protein binding and bloodbrain barrier.

AurSCOPE Ion Channel

by Aureus Sciences,

The Ion Channel database is the Aureus Sciences' knowledge base containing voltage and ligand-gated ion channels, ligand-relevant chemical information associated with quantitative biological activities and mechanisms of action.

AurSCOPE Nuclear Receptors

by Aureus Sciences,

Nuclear receptors form a family of ligand-activated transcription factors that regulate a wide variety of biological processes and are thus considered relevant targets in drug discovery.