Nonclinical and human pharmacology of the potent and selective topical retinoic acid receptor-γ agonist trifarotene.

BACKGROUND: First- and third-generation retinoids are the main treatment for acne. Even though efficacious, they lack full selectivity for retinoic acid receptor (RAR) γ, expressed in the epidermis and infundibulum. OBJECTIVES: To characterize the in vitro metabolism and the pharmacology of the novel retinoid trifarotene. MATERIALS AND METHODS: In vitro assays determined efficacy, potency and selectivity on RARs, as well as the activity on the expression of retinoid target genes in human keratinocytes and ex vivo cultured skin. In vivo studies investigated topical comedolytic, anti-inflammatory and depigmenting properties. The trifarotene-induced gene expression profile was investigated in nonlesional skin of patients with acne and compared with ex vivo and in vivo models. Finally, the metabolic stability in human keratinocytes and hepatic microsomes was established. RESULTS: Trifarotene is a selective RARγ agonist with > 20-fold selectivity over RARα and RARß. Trifarotene is active and stable in keratinocytes but rapidly metabolized by human hepatic microsomes, predicting improved safety. In vivo, trifarotene 0·01% applied topically is highly comedolytic and has anti-inflammatory and antipigmenting properties. Gene expression studies indicated potent activation of known retinoid-modulated processes (epidermal differentiation, proliferation, stress response, retinoic acid metabolism) and novel pathways (proteolysis, transport/skin hydration, cell adhesion) in ex vivo and in vivo models, as well as in human skin after 4 weeks of topical application of trifarotene 0·005% cream. CONCLUSIONS: Based on its RARγ selectivity, rapid degradation in human hepatic microsomes and pharmacological properties including potent modulation of epidermal processes, topical treatment with trifarotene could result in good efficacy and may present a favourable safety profile in acne and ichthyotic disorders.

A genetic algorithm for the automated generation of small organic molecules: drug design using an evolutionary algorithm.

Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a novel tool for the investigation of such problems. These are a class of algorithms that mimic some of the major characteristics of Darwinian evolution. LEA has been designed in order to conceive novel small organic molecules which satisfy quantitative structure-activity relationship based rules (fitness). The fitness consists of a sum of constraints that are range properties. The algorithm takes an initial set of fragments and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. The basis of the algorithm, its implementation and parameterization, are described together with an application in de novo molecular design of new retinoids. The results may be promising for chemical synthesis and show that this tool may find extensive applications in de novo drug design projects.

Critical role of the H6-H7 loop in the conformational adaptation of all-trans retinoic acid and synthetic retinoids within the ligand-binding site of RARalpha.

The pleiotropic effects of the natural and synthetic retinoids are mediated by the activation of the two subfamilies of nuclear receptors, the retinoic acid receptors (RARs) and the retinoic X receptors (RXRs). At the molecular level, these events begin with the specific ligand recognition by a nuclear receptor subtype. The adaptation of ligands to the receptor binding site leads to an optimal number of interactions for binding and selectivity which justifies elucidation of the structural requirements of the ligand binding pocket. To explore the contribution of H6-H7 loop folding in the ligand-induced conformational changes explained by the mouse-trap model, four RARalpha mutants were constructed. Ligand binding and transactivation studies revealed that three residues from the H6-H7 loop (Gly(301), Phe(302) and Gly(303)) are critical for the conformational adaptation of both synthetic agonists and antagonists. Model building and analysis of both RARalpha-ATRA and RARalpha-CD367 complexes demonstrate that accommodation of CD367 results in a less tight contact of the saturated ring of this ligand with the amino acid side chains of the receptor ligand-binding pocket compared with that of ATRA. According to the flexibility of the agonists tested (ATRA>TTNPB=Am580> CD367), we observed a decrease in binding that was dependent on ligand structure rigidity. In contrast, the binding and transactivating activities of the L266A mutant confirmed the structural constraints imposed by synthetic ligands on binding affinity for the receptor and revealed that subtle local rearrangements induced by specific conformational adaptation changes result in different binding affinities. Our results illustrate the dynamic nature of the interaction between RARalpha and its ligands and demonstrate the critical role of the H6-H7 loop in the binding of both synthetic retinoid agonists and antagonists.

Homology modeling of rabbit prolactin hormone complexed with its receptor.

The pituitary hormone prolactin (prl) is implicated in a number of biological functions, especially lactation, which is mediated through specific lactogenic receptors (PrlR). Human growth hormone (hGH) is also a pituitary hormone responsible for linear growth. While the growth hormone receptor (hGHR) binds only hGH, hPrlR can interact with both hGH and hPrl. Using structural information from the human growth hormone (hGH)/receptor (hGHR) complex, we modeled by homology a complex between rabbit prolactin hormone (rbPrl) and its receptor (rbPrlR). While the somatogenic hormone/somatogenic receptor (hGH/hGHR) and somatogenic hormone/lactogenic receptor (hGH/hPrlR) interactions are now known and well studied, here we propose a model for the interaction of the lactogenic hormone with its receptor (rbPrl/rbPrlR), and compare these three kinds of ligand/receptor interaction. We identified residues contributing to the active site and tested the potential dimerization of the receptor. Biochemical studies and information deduced from the modeled complex do not exclude a homodimeric form but point to a functional heterodimeric complex.

Putative dimeric organization of nuclear receptor hormone-binding domains, deduced from hydrophobic cluster analysis.

2D hydrophobic cluster analysis (HCA) protein sequence processing, efficient at low levels of sequence identity, leads to a coherent scheme for the structural organization of the hormone-binding domains (HBDs) of nuclear receptors. The typical serine protease inhibitor (serpin) fold, previously proposed, is confirmed as a likely framework for the hormone-binding domain and leads to a logical dimerization. Furthermore, homo- or hetero-dimerization creates sites where hormone could likely be bound, itself being an active component of the dimerization. This model fulfils many of the biochemical and biological data.

Comparison of three algorithms for the assignment of secondary structure in proteins: the advantages of a consensus assignment.

Accurate assignments of secondary structures in proteins are crucial for a useful comparison with theoretical predictions. Three major programs which automatically determine the location of helices and strands are used for this purpose, namely DSSP, P-Curve and Define. Their results have been compared for a non-redundant database of 154 proteins. On a residue per residue basis, the percentage match score is only 63% between the three methods. While these methods agree on the overall number of residues in each of the three states (helix, strand or coil), they differ on the number of helices or strands, thus implying a wide discrepancy in the length of assigned structural elements. Moreover, the length distribution of helices and strands points to the existence of artefacts inherent to each assignment algorithm. To overcome these difficulties a consensus assignment is proposed where each residue is assigned to the state determined by at least two of the three methods. With this assignment the artefacts of each algorithm are attenuated. The residues assigned in the same state by the three methods are better predicted than the others. This assignment will thus be useful for analysing the success rate of prediction methods more accurately.

Structural symmetry of the extracellular domain of the cytokine/growth hormone/prolactin receptor family and interferon receptors revealed by hydrophobic cluster analysis.

Sequence comparison based on Hydrophobic Cluster Analysis procedures shows that the extracellular approximately 200 amino acids domains of cytokines receptors belonging to the Cytokine/Growth hormone/Prolactin receptor family and to the Interferon one are organized in two homologous subdomains. Further, comparison of the subdomains of 32 independent sequences and of a lot of already recognized homologous domains with data bases could lead to the hypothesis that these approximately 100 amino acids subdomains could possess the overall fold of the constant immunoglobulin domains and so could belong to the immunoglobulin superfamily.