Synthesis, biological evaluation and molecular modeling of a novel series of 7-azaindole based tri-heterocyclic compounds as potent CDK2/Cyclin E inhibitors.

From four molecules, inspired by the structural features of fascaplysin, with an interesting potential to inhibit cyclin-dependent kinases (CDKs), we designed a new series of tri-heterocyclic derivatives based on 1H-pyrrolo[2,3-b]pyridine (7-azaindole) and triazole heterocycles. Using a Huisgen type [3 + 2] cycloaddition as the convergent key step, 24 derivatives were synthesized and their biological activities were evaluated. Comparative molecular field analysis (CoMFA), based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies, was conducted on a series of 30 compounds from the literature with high to low known inhibitory activity towards CDK2/cyclin E and was validated by a test set of 5 compounds giving satisfactory predictive r(2) value of 0.92. Remarkably, it also gave a good prediction of pIC50 for our tri-heterocyclic series which reinforce the validation of this model for the pIC50 prediction of external set compounds. The most promising compound, 43, showed a micro-molar range inhibitory activity against CDK2/cyclin E and also an antiproliferative and proapoptotic activity against a panel of cancer cell lines.

Optimization and validation of a docking-scoring protocol; application to virtual screening for COX-2 inhibitors.

To exploit available structural information about the cyclooxygenase enzyme for the virtual screening of large chemical libraries, a docking-scoring protocol was tuned and validated. The screening accuracy was assessed using a series of known inhibitors and a set of diverse a priori inactive compounds that was seeded with known active ligands. The major parameters of the DOCK algorithm were investigated. A large improvement of the results was obtained on tweaking some of them. The generated complexes were rescored using six scoring functions. In this way, the striking importance of this step was demonstrated, as well as the good performances of DOCK energy and SCORE for this target. The results were further improved via a consensus approach. As a first application, a subset of a large compound library was screened using this protocol. Among the compounds that were selected for biological testing, a third of them turned out to have a significant enzyme inhibition.

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.

2D QSAR consensus prediction for high-throughput virtual screening. An application to COX-2 inhibition modeling and screening of the NCI database.

Using classification (SOM, LVQ, Binary, Decision Tree) and regression algorithms (PLS, BRANN, k-NN, Linear), this paper details the building of eight 2D-QSAR models from a 266 COX-2 inhibitor training set. The predictive performances of these eight models were subsequently compared using an 88 COX-2 inhibitor test set. Each ligand is described by 52 2D descriptors expressed as van der Waals Surface Areas (P_VSA) and its COX-2 binding IC50. One of our best predictive models is the neural network model (BRANN), which is able to select a subset, from the 88 ligand test set, that contains 94% COX-2 active inhibitors (pIC50>7.5) and detects 71% of all the actives. We then introduce a QSAR consensus prediction protocol that is shown to be more predictive than any single QSAR model: our C3 consensus approach is able to select a subset from the 88 ligand test set that contains 94% active inhibitors and 83% of all the actives. The 2D QSAR consensus protocol was finally applied to the high-throughput virtual screening of the NCI database, containing 193,477 organic compounds.

Synthesis and hypoglycemic evaluation of substituted pyrazole-4-carboxylic acids.

The synthesis and in vivo activities of a series of substituted pyrazole-4-carboxylic acids as hypoglycemic agents are described. Modelization of some potent compounds, comparatively to the metformine, presents certain analogies permitting to predict the design of some novel antidiabetic drugs.