In this work, we report the development of a novel QSAR technique combining genetic algorithms and neural networks for selecting a subset of relevant descriptors and building the optimal neural network architecture for QSAR studies. This technique uses a neural network to map the dependent property of interest with the descriptors preselected by the genetic algorithm. This technique differs from other variable selection techniques combining genetic algorithms to neural networks by two main features: (1) The variable selection search performed by the genetic algorithm is not constrained to a defined number of descriptors. (2) The optimal neural network architecture is explored in parallel with the variable selection by dynamically modifying the size of the hidden layer. By using both artificial data and real biological data, we show that this technique can be used to build both classification and regression models and outperforms simpler variable selection techniques mainly for nonlinear data sets. The results obtained on real data are compared to previous work using other modeling techniques. We also discuss some important issues in building QSAR models and good practices for QSAR studies.

This study aimed to investigate the chemical composition, and evaluate the antioxidant, anti-inflammatory, anti-pyretic, and the analgesic properties of methanol extracts from the leaves of Thymus algeriensis and Thymus fontanesii (Lamiaceae). Thirty-five secondary metabolites were characterized in both extracts using HPLC-PDA-ESI-MS/MS. Phenolic acids, mainly rosmarinic acid and its derivatives, dominated the T. algeriensis extract, while the phenolic diterpene carnosol and the methylated flavonoid salvigenin, prevailed in T. fontanesii extract. Molecular docking study was carried out to estimate the anti-inflammatory potential and the binding affinities of some individual secondary metabolites from both extracts to the main enzymes involved in the inflammation pathway. In vitro enzyme inhibitory assays and in vivo assays were used to investigate the antioxidant and anti-inflammatory activities of the extracts. Results revealed that both studied Thymus species exhibited antioxidant, anti-inflammatory, analgesic, and antipyretic effects. They showed to be a more potent antioxidant than ascorbic acid and more selective against cyclooxygenase (COX-2) than diclofenac and indomethacin. Relatively, the T. fontanesii extract was more potent as COX-2 inhibitor than T. algeriensis. In conclusion, Thymus algeriensis and Thymus fontanesii may be interesting candidates for the treatment of inflammation and oxidative stress-related disorders.

We describe the rational design of immunosuppressive peptides without relying on information regarding their receptors or mechanisms of action. The design strategy uses a variety of topological and shape descriptors in combination with an analysis of molecular dynamics trajectories for the identification of potential drug candidates. This strategy was applied to the development of immunosuppressive peptides with enhanced potency. The lead compounds were peptides, derived from the heavy chain of HLA class I, that modulate immune responses in vitro and in vivo. In particular, a peptide derived from HLA-B2702, amino acids 75-84 (2702.75-84) prolonged skin and heart allograft survival in mice. The biological activity of the rationally designed peptides was tested in a heterotopic mouse heart allograft model. The molecule predicted to be most potent displayed an immunosuppressive activity approximately 100 times higher than the lead compound.

Receptor tyrosine kinases (RTK) are transmembrane receptors that regulate signal transduction in cells. As a member of the TAM (Tyro-3, Axl, Mer) RTK subfamily, Axl regulates key processes such as cell growth, migration, aggregation, and apoptosis through several pathways. Its overexpression/overactivation has been underlined in several conditions, especially cancers, and in both chemotherapy and targeted therapy sensitivity loss. In this review, we propose to highlight the therapeutic implication of Axl, starting with the pathways it regulates, validating its interest as a therapeutic target, and defining the tools available to develop strategies for its inhibition. We especially focus on small molecule inhibitors, their structure, inhibition profile, and development stages. Mol Cancer Ther; 13(9); 2141-8. Ó2014 AACR.

Saponins are an important group found in Chenopodium quinoa. They represent an obstacle for the use of quinoa as food for humans and animal feeds because of their bitter taste and toxic effects, which necessitates their elimination. Several saponins elimination methods have been examined to leach the saponins from the quinoa seeds; the wet technique remains the most used at both laboratory and industrial levels. Dry methods (heat treatment, extrusion, roasting, or mechanical abrasion) and genetic methods have also been evaluated. The extraction of quinoa saponins can be carried out by several methods; conventional technologies such as maceration and Soxhlet are the most utilized methods. However, recent research has focused on technologies to improve the efficiency of extraction. At least 40 saponin structures from quinoa have been isolated in the past 30 years, the derived molecular entities essentially being phytolaccagenic, oleanolic and serjanic acids, hederagenin, 3β,23,30 trihydroxy olean-12-en-28-oic acid, 3β-hydroxy-27-oxo-olean-12en-28-oic acid, and 3β,23,30 trihydroxy olean-12-en-28-oic acid. These metabolites exhibit a wide range of biological activities, such as molluscicidal, antifungal, anti-inflammatory, hemolytic, and cytotoxic properties.