Botanical drugs, synergy, and network pharmacology: forth and back to intelligent mixtures

For centuries the science of pharmacognosy has dominated rational drug development until it was gradually substituted by target-based drug discovery in the last fifty years. Pharmacognosy stems from the different systems of traditional herbal medicine and its "reverse pharmacology" approach has led to the discovery of numerous pharmacologically active molecules and drug leads for humankind. But do botanical drugs also provide effective mixtures? Nature has evolved distinct strategies to modulate biological processes, either by selectively targeting biological macromolecules or by creating molecular promiscuity or polypharmacology (one molecule binds to different targets). Widely claimed to be superior over monosubstances, mixtures of bioactive compounds in botanical drugs allegedly exert synergistic therapeutic effects. Despite evolutionary clues to molecular synergism in nature, sound experimental data are still widely lacking to support this assumption. In this short review, the emerging concept of network pharmacology is highlighted, and the importance of studying ligand-target networks for botanical drugs is emphasized. Furthermore, problems associated with studying mixtures of molecules with distinctly different pharmacodynamic properties are addressed. It is concluded that a better understanding of the polypharmacology and potential network pharmacology of botanical drugs is fundamental in the ongoing rationalization of phytotherapy.

Long-lasting protection of activity of nucleoside reverse transcriptase inhibitors and protease inhibitors (PIs) by boosted PI containing regimens

Background The accumulation of mutations after long-lasting exposure to a failing combination antiretroviral therapy (cART) is problematic and severely reduces the options for further successful treatments. Methods We studied patients from the Swiss HIV Cohort Study who failed cART with nucleoside reverse transcriptase inhibitors (NRTIs) and either a ritonavir-boosted PI (PI/r) or a non-nucleoside reverse transcriptase inhibitor (NNRTI). The loss of genotypic activity <3, 3–6, >6 months after virological failure was analyzed with Stanford algorithm. Risk factors associated with early emergence of drug resistance mutations (<6 months after failure) were identified with multivariable logistic regression. Results Ninety-nine genotypic resistance tests from PI/r-treated and 129 from NNRTI-treated patients were analyzed. The risk of losing the activity of ≥1 NRTIs was lower among PI/r- compared to NNRTI-treated individuals <3, 3–6, and >6 months after failure: 8.8% vs. 38.2% (p = 0.009), 7.1% vs. 46.9% (p<0.001) and 18.9% vs. 60.9% (p<0.001). The percentages of patients who have lost PI/r activity were 2.9%, 3.6% and 5.4% <3, 3–6, >6 months after failure compared to 41.2%, 49.0% and 63.0% of those who have lost NNRTI activity (all p<0.001). The risk to accumulate an early NRTI mutation was strongly associated with NNRTI-containing cART (adjusted odds ratio: 13.3 (95% CI: 4.1–42.8), p<0.001). Conclusions The loss of activity of PIs and NRTIs was low among patients treated with PI/r, even after long-lasting exposure to a failing cART. Thus, more options remain for second-line therapy. This finding is potentially of high relevance, in particular for settings with poor or lacking virological monitoring.

First results from a Swiss level I trauma centre participating in the UK Trauma Audit and Research Network (TARN): Prospective cohort study

QUESTIONS UNDER STUDY: Patient characteristics and risk factors for death of Swiss trauma patients in the Trauma Audit and Research Network (TARN). METHODS: Descriptive analysis of trauma patients (≥16 years) admitted to a level I trauma centre in Switzerland (September 1, 2009 to August 31, 2010) and entered into TARN. Multivariable logistic regression analysis was used to identify predictors of 30-day mortality. RESULTS: Of 458 patients 71% were male. The median age was 50.5 years (inter-quartile range [IQR] 32.2-67.7), median Injury Severity Score (ISS) was 14 (IQR 9-20) and median Glasgow Coma Score (GCS) was 15 (IQR 14-15). The ISS was >15 for 47%, and 14% had an ISS >25. A total of 17 patients (3.7%) died within 30 days of trauma. All deaths were in patients with ISS >15. Most injuries were due to falls <2 m (35%) or road traffic accidents (29%). Injuries to the head (39%) were followed by injuries to the lower limbs (33%), spine (28%) and chest (27%). The time of admission peaked between 12:00 and 22:00, with a second peak between 00:00 and 02:00. A total of 64% of patients were admitted directly to our trauma centre. The median time to CT was 30 min (IQR 18-54 min). Using multivariable regression analysis, the predictors of mortality were older age, higher ISS and lower GCS. CONCLUSIONS: Characteristics of Swiss trauma patients derived from TARN were described for the first time, providing a detailed overview of the institutional trauma population. Based on these results, patient management and hospital resources (e.g. triage of patients, time to CT, staffing during night shifts) could be evaluated as a further step.

In vivo TCR Signaling in CD4(+) T Cells Imprints a Cell-Intrinsic, Transient Low-Motility Pattern Independent of Chemokine Receptor Expression Levels, or Microtubular Network, Integrin, and Protein Kinase C Activity

Intravital imaging has revealed that T cells change their migratory behavior during physiological activation inside lymphoid tissue. Yet, it remains less well investigated how the intrinsic migratory capacity of activated T cells is regulated by chemokine receptor levels or other regulatory elements. Here, we used an adjuvant-driven inflammation model to examine how motility patterns corresponded with CCR7, CXCR4, and CXCR5 expression levels on ovalbumin-specific DO11.10 CD4(+) T cells in draining lymph nodes. We found that while CCR7 and CXCR4 surface levels remained essentially unaltered during the first 48-72 h after activation of CD4(+) T cells, their in vitro chemokinetic and directed migratory capacity to the respective ligands, CCL19, CCL21, and CXCL12, was substantially reduced during this time window. Activated T cells recovered from this temporary decrease in motility on day 6 post immunization, coinciding with increased migration to the CXCR5 ligand CXCL13. The transiently impaired CD4(+) T cell motility pattern correlated with increased LFA-1 expression and augmented phosphorylation of the microtubule regulator Stathmin on day 3 post immunization, yet neither microtubule destabilization nor integrin blocking could reverse TCR-imprinted unresponsiveness. Furthermore, protein kinase C (PKC) inhibition did not restore chemotactic activity, ruling out PKC-mediated receptor desensitization as mechanism for reduced migration in activated T cells. Thus, we identify a cell-intrinsic, chemokine receptor level-uncoupled decrease in motility in CD4(+) T cells shortly after activation, coinciding with clonal expansion. The transiently reduced ability to react to chemokinetic and chemotactic stimuli may contribute to the sequestering of activated CD4(+) T cells in reactive peripheral lymph nodes, allowing for integration of costimulatory signals required for full activation.