Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands.

Telomeres and telomerase are key players in tumorogenesis. Among the various strategies proposed for telomerase inhibition or telomere uncapping, the stabilization of telomeric G-quadruplex (G4) structures is a very promising one. Additionally, G4 stabilizing ligands also act over tumors mediated by the alternative elongation of telomeres. Accordingly, the discovery of novel compounds able to act on telomeres and/or inhibit the telomerase enzyme by stabilizing DNA telomeric G4 structures as well as the development of approaches efficiently prioritizing such compounds constitute active areas of research in computational medicinal chemistry and anticancer drug discovery. In this direction, we applied a virtual screening strategy based on the rigorous application of QSAR best practices and its harmonized integration with structure-based methods. More than 600,000 compounds from commercial databases were screened, the first 99 compounds were prioritized, and 21 commercially available and structurally diverse candidates were purchased and submitted to experimental assays. Such strategy proved to be highly efficient in the prioritization of G4 stabilizer hits, with a hit rate of 23.5%. The best G4 stabilizer hit found exhibited a shift in melting temperature from FRET assay of +7.3 °C at 5 µM, while three other candidates also exhibited a promising stabilizing profile. The two most promising candidates also exhibited a good telomerase inhibitory ability and a mild inhibition of HeLa cells growth. None of these candidates showed antiproliferative effects in normal fibroblasts. Finally, the proposed virtual screening strategy proved to be a practical and reliable tool for the discovery of novel G4 ligands which can be used as starting points of further optimization campaigns.

Inactivation of the glutamine/amino acid transporter ASCT2 by 1,2,3-dithiazoles: proteoliposomes as a tool to gain insights in the molecular mechanism of action and of antitumor activity.

The ASCT2 transport system catalyses a sodium-dependent antiport of glutamine and other neutral amino acids which is involved in amino acid metabolism. A library of 1,2,3-dithiazoles was designed, synthesized and evaluated as inhibitors of the glutamine/amino acid ASCT2 transporter in the model system of proteoliposomes reconstituted with the rat liver transporter. Fifteen of the tested compounds at concentration of 20µM or below, inhibited more than 50% the glutamine/glutamine antiport catalysed by the reconstituted transporter. These good inhibitors bear a phenyl ring with electron withdrawing substituents. The inhibition was reversed by 1,4-dithioerythritol indicating that the effect was likely owed to the formation of mixed sulfides with the protein's Cys residue(s). A dose-response analysis of the most active compounds gave IC(50) values in the range of 3-30µM. Kinetic inhibition studies indicated a non-competitive inhibition, presumably because of a potential covalent interaction of the dithiazoles with cysteine thiol groups that are not located at the substrate binding site. Indeed, computational studies using a homology structural model of ASCT2 transporter, suggested as possible binding targets, Cys-207 or Cys-210, that belong to the CXXC motif of the protein.

Discovery, biological evaluation, and structure-activity and -selectivity relationships of 6'-substituted (E)-2-(benzofuran-3(2H)-ylidene)-N-methylacetamides, a novel class of potent and selective monoamine oxidase inhibitors.

The use of selective inhibitors of monoamine oxidase A (MAO-A) and B (MAO-B) holds a therapeutic relevance in the treatment of depressive disorders and Parkinson's disease (PD), respectively. Here, the discovery of a new class of compounds acting as monoamine oxidase inhibitors (MAO-Is) and bearing a 6'-substituted (E)-2-(benzofuran-3(2H)-ylidene)-N-alkylacetamide skeleton is reported. 6'-Sulfonyloxy derivatives exhibited outstanding affinities to MAO-A (7.0 nM < IC50 < 49 nM, much higher than moclobemide) and a pronounced MAO-A/B selectivity. The corresponding 6'-benzyloxy derivatives showed potent MAO-B inhibition and inverted selectivity profile. The rigid E-geometry of the exocyclic double bond allowed a more efficient binding conformation compared to more flexible and less active 2-(1-benzofuran-3-yl)-N-methylacetamide isomers and 4-N-methylcarboxamidomethylcoumarin analogues. Focused structural modifications and docking simulations enabled the identification of key molecular determinants for high affinity toward both MAO isoforms. These novel MAO-Is may represent promising hits for the development of safer therapeutic agents with a potential against depression, PD, and other age-related neurodegenerative pathologies.

Strategies of multi-objective optimization in drug discovery and development.

INTRODUCTION: Drug discovery and development is a typical multi-objective problem and its successes or failures depend on the simultaneous control of numerous, often conflicting, molecular and pharmacological properties. Multi-objective optimization strategies represent a new approach to capture the occurrence of varying optimal solutions based on trade-offs among the objectives taken into account. In view of this, multi-objective optimization aims to discover a set of satisfactory compromises that may in turn be used to find the global optimal solution by optimizing numerous dependent properties simultaneously. AREAS COVERED: The authors review the potential of multi-objective strategies in a number of fields including: drug library design; substructure mining; the derivation of quantitative structure-activity relationship models; ranking of docking poses. The authors also discuss the potential of multi-objective strategies in controlling competing properties for absorption, distribution, metabolism and elimination/toxicity optimization. EXPERT OPINION: It is very clear to those who work in drug discovery and development that the success of rational drug design is largely dependent on the control of a number of, often conflicting, objectives. Therefore, multi-objective optimization methods, which have recently been introduced to the field of molecular discovery, represent the ultimate frontier in chemoinformatics. The widespread use of these multi-objective techniques has provided new opportunities in medicinal chemistry as seen through its use in a number of applications for chemoinformatics both within academia and the pharmaceutical industry.