ADME-Space: a new tool for medicinal chemists to explore ADME properties.

We introduce a new chemical space for drugs and drug-like molecules, exclusively based on their in silico ADME behaviour. This ADME-Space is based on self-organizing map (SOM) applied to 26,000 molecules. Twenty accurate QSPR models, describing important ADME properties, were developed and, successively, used as new molecular descriptors not related to molecular structure. Applications include permeability, active transport, metabolism and bioavailability studies, but the method can be even used to discuss drug-drug interactions (DDIs) or it can be extended to additional ADME properties. Thus, the ADME-Space opens a new framework for the multi-parametric data analysis in drug discovery where all ADME behaviours of molecules are condensed in one map: it allows medicinal chemists to simultaneously monitor several ADME properties, to rapidly select optimal ADME profiles, retrieve warning on potential ADME problems and DDIs or select proper in vitro experiments.

Mining collections of compounds with Screening Assistant 2.

BACKGROUND: High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. RESULTS: We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. CONCLUSIONS: Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/.

QSAR Modelling of CYP3A4 Inhibition as a Screening Tool in the Context of DrugDrug Interaction Studies.

Drugdrug interaction potential (DDI), especially cytochrome P450 (CYP) 3A4 inhibition potential, is one of the most important parameters to be optimized before preclinical and clinical pharmaceutical development as regard to the number of marketed drug metabolized mainly by this CYP and potentially co-administered with the future drug. The present study aims to develop in silico models for CYP3A4 inhibition prediction to help medicinal chemists during the discovery phase and even before the synthesis of new chemical entities (NCEs), focusing on NCEs devoid of any inhibitory potential toward this CYP. In order to find a relevant relationship between CYP3A4 inhibition and chemical features of the screened compounds, we applied a genetic-algorithm-based QSAR exploratory tool SQS (Stochastic QSAR Sampler) in combination with different description approaches comprising alignment-independent Volsurf descriptors, ISIDA fragments and Topological Fuzzy Pharmacophore Triplets. The experimental data used to build models were extracted from an in-house database. We derived a model with good prediction ability that was confirmed on both newly synthesized compound and public dataset retrieved from Pubchem database. This model is a promising efficient tool for filtering out potentially problematic compounds.

[Chemoinformatics and virtual screening of molecules for therapeutic use]. / Apports de la chémo-informatique dans la recherche et l'optimisation des molécules d'intérêt thérapeutique.

Successful identification of new chemical entities with drug-like properties in pharmaceutical and academic research groups involves an early screen and the use of a large number of public and proprietary chemical libraries. Before applying high-throughput experimental screening approaches, virtual screening strategies have been put in place in order to sort and filter this massive amount of compounds and data available at these very early stages. Chemoinformatic tools have a crucial role in this selection process and enable therapeutic chemists to focus very early on promising candidates. Virtual screening has conventionally been based either on models of the target or the ligand (molecule), but today these models include biopharmaceutical filters addressing right from the start of the project the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the molecules. Above all, chemoinformatic tools help chemists understand better the chemical diversity they can work with, especially when comparing chemical libraries. This paper will focus on exemples of the day-to-day use of chemoinformatics in screening programs. A large part will be dedicated to new tools (chemographic and pharmacographic approaches) being developed for the representation and analysis of chemical diversity, but also for combining chemical and biological information to expedite research programs.

Synthesis and biological evaluation of cis-locked vinylogous combretastatin-A4 analogues: derivatives with a cyclopropyl-vinyl or a cyclopropyl-amide bridge.

A series of novel combretastatin A4 analogues, in which the cis-olefinic bridge is replaced by a cyclopropyl-vinyl or a cyclopropyl-amide moiety, were synthesized and evaluated for inhibition of tubulin polymerization and antiproliferative activity. The derivative 9a with a (cis,E)-cyclopropyl-vinyl unit is the most promising compound. As expected, molecular docking of 9a has shown that only one of the cis-cyclopropyl enantiomers is a good ligand for tubulin.

A short series of antidiabetic sulfonylureas exhibit multiple ligand PPARgamma-binding patterns.

The present work explores the PPARgamma-activating properties of a series of eight sulfonylureas, using transfection experiments with 293T cells, and rosiglitazone as a reference PPARgamma agonist. In the same time, results from these in vitro experiments are compared to those generated by a sound in silico PPARgamma-ligand docking procedure combined to a simple and astute strategy analysis. The latter consists of building up a dendrogram (decision tree-like diagram) by applying three successive criteria, namely stability, conformational shape and H-binding strength of the docked sulfonylurea or rosiglitazone. This original dendrogram approach avers to be a successful way to account for our biochemical data. It discriminates also various PPARgamma-binding patterns from our small series of compounds. The recognition of these patterns is extremely important because of the extraordinary potentialities of PPARgamma ligands as therapeutic agents in diabetes, cancer, cardiovascular and neurological disorders.

Managing, profiling and analyzing a library of 2.6 million compounds gathered from 32 chemical providers.

The data for 3.8 million compounds from structural databases of 32 providers were gathered and stored in a single chemical database. Duplicates are removed using the IUPAC International Chemical Identifier. After this, 2.6 million compounds remain. Each database and the final one were studied in term of uniqueness, diversity, frameworks, 'drug-like' and 'lead-like' properties. This study also shows that there are more than 87 000 frameworks in the database. It contains 2.1 million 'drug-like' molecules among which, more than one million are 'lead-like'. This study has been carried out using 'ScreeningAssistant', a software dedicated to chemical databases management and screening sets generation. Compounds are stored in a MySQL database and all the operations on this database are carried out by Java code. The druglikeness and leadlikeness are estimated with 'in-house' scores using functions to estimate convenience to properties; unicity using the InChI code and diversity using molecular frameworks and fingerprints. The software has been conceived in order to facilitate the update of the database. 'ScreeningAssistant' is freely available under the GPL license.

Meroterpenes from the ascidian Aplidium aff. densum.

Chemical investigation of the ascidian Aplidium aff. densum collected at Masirah Island, Oman, has resulted in the isolation of five meroterpenes: two new ones, methoxyconidiol (1) and didehydroconicol (2), and three related, known compounds, 3-5. The structures of 1 and 2 were determined by a combination of mass spectrometry and one- and two-dimensional high-field NMR techniques. Their biological activities against bacteria and human lymphoblastic cell lines were evaluated.