Development of Hinoline® as a natural preservative for cosmetic product using bioinspiration and Greenpharma Database.

AIMS: The cosmetic industry needs new preservatives that are effective, natural, safe, cost effective, sustainable and compliant with regulatory standards. This necessity has posed challenges requiring obligations, bioinformatics and bioinspiration as driving forces. METHODS AND RESULTS: Twenty natural extracts were selected from the Greenpharma Database with parameter filters corresponding to development constraints and antimicrobial properties. We confirmed using minimum inhibition concentration (MIC) assays that eight of the extracts have good bactericidal properties and that one has a high antifungal activity. The latter was purified hinokitiol, a bioproduct from Aomori Hiba wood. This substance provides high resistance against putrefaction; for instance, old Japanese temples were made of Aomori Hiba wood. The combination of hinokitiol with levulinic acid, another bioproduct, demonstrated complementary antimicrobial activities and synergistic effects in MIC studies and measurements according to Kull synergy index. Further, the mixture Hinoline® was tested at 2% in challenge tests and fulfilled criteria A of different standards. It also exerted complementary preservative effects with potassium sorbate and beneficial effects in unbalanced skin microbiota. CONCLUSION: Hinoline, a new effective preservative from renewable bioresources, was developed. SIGNIFICANCE AND IMPACT OF THE STUDY: This study accelerates the development of a preservative solution for cosmetics selected from Greenpharma Database, through bioinspiration and the identification of cost-effective investments and resources.

Reverse pharmacognosy: another way to harness the generosity of nature.

A huge amount of data has been generated by decades of pharmacognosy supported by the rapid evolution of chemical, biological and computational techniques. How can we cope with this overwhelming mass of information? Reverse pharmacognosy was introduced with this aim in view. It proceeds from natural molecules to organisms that contain them via biological assays in order to identify an activity. In silico techniques and particularly inverse screening are key technologies to achieve this goal efficiently. Reverse pharmacognosy allows us to identify which molecule(s) from an organism is(are) responsible for the biological activity and the biological pathway(s) involved. An exciting outcome of this approach is that it not only provides evidence of the therapeutic properties of plants used in traditional medicine for instance, but may also position other plants containing the same active compounds for the same usage, thus increasing the curative arsenal e.g. development of new botanicals. This is particularly interesting in countries where western medicines are still not affordable. At the molecular level, in organisms, families of metabolites are synthesized and seldom have a single structure. Hence, when a natural compound has an interesting activity, it may be desirable to check whether there are more active and/or less toxic derivatives in organisms containing the hit - this corresponds to a kind of "natural combinatorial" chemistry. At a time when the pharmaceutical industry is lacking drug candidates in clinical trials, drug repositioning - i.e. exploiting existing knowledge for innovation - has never been so critical. Reverse pharmacognosy can contribute to addressing certain issues in current drug discovery - such as the lack of clinical candidates, toxicity... - by exploiting existing data from pharmacognosy. This review will focus on recent advances in computer science applied to natural substance research that consolidate the new concept of reverse pharmacognosy.

How to recognize and workaround pitfalls in QSAR studies: a critical review.

Quantitative Structure-Activity Relationships (QSAR) are based on the hypothesis that changes in molecular structure reflect proportional changes in the observed response or biological activity. In order to successfully conduct QSAR studies certain conditions have to be met that are not frequently reported in the literature. This suggests that some authors are not aware of the principle flaws, occasional shortcomings, and circumstantial downsides of QSAR methods. The present paper focuses on prerequisites to set up correct models and on limitations of model applications. Their implications are systematically described and illustrated as pitfalls that have strong implications in QSAR, and possible solutions are suggested. The paper is focused on small scale 2D- and 3D-QSAR studies for lead optimization. The work is enriched with comprehensive comments and non-mathematical explanations for the computer practitioner in Medicinal Chemistry.

Application of drug repositioning strategy to TOFISOPAM.

Drug repositioning strategy is an interesting approach for pharmaceutical companies; especially to increase their productivity. SELNERGY(tm) is a reverse docking based-program able to virtually screen thousands of compounds on more than 2000 3D biological targets. This program was successfully applied to tofisopam and revealed that the isomers of tofisopam are able to fit with phosphodiesterase 4. This old drug was used as a racemic mixture to treat anxiety in the eighties and was recently shown to act as a PDE4 inhibitor. Thanks to this strategy we demonstrated that tofisopam acts via the inhibition of PDE4 in the submicromolar range. Moreover, we firstly showed that the S-enantiomer of tofisopam is ten times more active than R-enantiomer. The identification of the biochemical mechanism of tofisopam isomers now allows to reposition this drug in new therapeutic indications where modulation of cAMP via PDE4 inhibitors are possible.

Preliminary screening of some tropical plants for anti-tyrosinase activity.

In our efforts to find new active tyrosinase inhibitors for skin-whitening or antibrowning preparations, we investigated 67 tropical plants belonging to 38 families, which were evaluated for their anti-tyrosinase activity. The results of our investigation show that extracts of 5 plants, Stryphnodendron barbatimao, Portulaca pilosa, Cariniana brasiliensis, Entada africana and Prosopis africana present interesting in vitro mushroom tyrosinase inhibition (over 90%), similar to a positive control: Morus alba. These 5 plants will be studied in order to isolate and identify phytochemical compounds, involved in this biological activity.

Mapping the active site of factor Xa by selective inhibitors: an NMR and MD study.

The structure of two selective inhibitors, Ac-Tyr-Ile-Arg-Ile-Pro-NH2 and Ac-(4-Amino-Phe)-(Cyclohexyl-Gly)-Arg-NH2, in the active site of the blood clotting enzyme factor Xa was determined by using transferred nuclear Overhauser effect nuclear magnetic resonance (NMR) spectroscopy. They represent a family of peptidic inhibitors obtained by the screening of a vast combinatorial library. Each structure was first calculated by using standard computational procedures (distance geometry, simulated annealing, energy minimization) and then further refined by systematic search of the conformation of the inhibitor docked in the active site and repeating the simulated annealing and energy minimization. The final structure was optimized by molecular dynamics simulations of the inhibitor-complex in water. The NMR restraints were kept throughout the refinement. The inhibitors assume a compact, very well defined conformation, embedded into the substrate binding site not in the same way as a substrate, blocking thus the catalysis. The model allows to explain the mode of action, affinity, and specificity of the peptides and to map the active site.

7Li nuclear-magnetic-resonance study of lithium binding to myo-inositolmonophosphatase.

The interaction of Li+ with myo-inositol monophosphatase was studied by 7Li-NMR spectroscopy. Li+ binding to the enzyme induces a downfield shift and broadening of the 7Li-NMR signal. Changes of the chemical shift were used to follow the titration of the enzyme with lithium and to determine a dissociation constant, Kd = (1.0 +/- 0.1) mM. Only one major binding site/enzyme subunit was inferred. The complex forms independently of the presence of inorganic phosphate. Metals from the group IIa of the periodic table compete with Li+ binding with the affinity increasing in the order Mg2+ < Ca2+ < Be2+. In contrast to lithium, their binding is enhanced by phosphate.