Foreigners, naturalized people and the problems of a realistic integration stock-taking

Wilkening F, Salentin K. Ausländer, Eingebürgerte und das Problem einer realistischen Zuwanderer-Integrationsbilanz. Kölner Zeitschrift für Soziologie und Sozialpsychologie. 2003;55(2):278-298.The use of the legal term "foreigner" in German official statistics and in sociological research on migration and integration is questioned. During the 1990s, naturalization has created a gap between the numbers of migrants and of foreigners. Legal and administrative factors cause an unobserved selectivity in the process of naturalization and increasingly blur the meaning of citizenship for social science purposes. Drawing on two German survey samples, the article reveals a considerably more favorable socio-economic placement of naturalized persons compared with foreigners of the same origin. Any stock-taking based on foreigners alone would exclude the most successful migrants in terms of education, labor market participation and income, and depict the participation of the immigrated population as overly deficient. An appropriate representation of naturalized people in official statistics is called for

Computational drug repositioning for chagas disease using protein-ligand interaction profiling.

Chagas disease, caused byTrypanosoma cruzi(T. cruzi), affects nearly eight million people worldwide. There are currently only limited treatment options, which cause several side effects and have drug resistance. Thus, there is a great need for a novel, improved Chagas treatment. Bifunctional enzyme dihydrofolate reductase-thymidylate synthase (DHFR-TS) has emerged as a promising pharmacological target. Moreover, some human dihydrofolate reductase (HsDHFR) inhibitors such as trimetrexate also inhibitT. cruziDHFR-TS (TcDHFR-TS). These compounds serve as a starting point and a reference in a screening campaign to search for newTcDHFR-TS inhibitors. In this paper, a novel virtual screening approach was developed that combines classical docking with protein-ligand interaction profiling to identify drug repositioning opportunities againstT. cruziinfection. In this approach, some food and drug administration (FDA)-approved drugs that were predicted to bind with high affinity toTcDHFR-TS and whose predicted molecular interactions are conserved among known inhibitors were selected. Overall, ten putativeTcDHFR-TS inhibitors were identified. These exhibited a similar interaction profile and a higher computed binding affinity, compared to trimetrexate. Nilotinib, glipizide, glyburide and gliquidone were tested onT. cruziepimastigotes and showed growth inhibitory activity in the micromolar range. Therefore, these compounds could lead to the development of new treatment options for Chagas disease

Structure-based drug repositioning explains ibrutinib as VEGFR2 inhibitor

Many drugs are promiscuous and bind to multiple targets. On the one hand, these targets may be linked to unwanted side effects, but on the other, they may achieve a combined desired effect (polypharmacology) or represent multiple diseases (drug repositioning). With the growth of 3D structures of drug-target complexes, it is today possible to study drug promiscuity at the structural level and to screen vast amounts of drug-target interactions to predict side effects, polypharmacological potential, and repositioning opportunities. Here, we pursue such an approach to identify drugs inactivating B-cells, whose dysregulation can function as a driver of autoimmune diseases. Screening over 500 kinases, we identified 22 candidate targets, whose knock out impeded the activation of B-cells. Among these 22 is the gene KDR, whose gene product VEGFR2 is a prominent cancer target with anti-VEGFR2 drugs on the market for over a decade. The main result of this paper is that structure-based drug repositioning for the identified kinase targets identified the cancer drug ibrutinib as micromolar VEGFR2 inhibitor with a very high therapeutic index in B-cell inactivation. These findings prove that ibrutinib is not only acting on the Bruton's tyrosine kinase BTK, against which it was designed. Instead, it may be a polypharmacological drug, which additionally targets angiogenesis via inhibition of VEGFR2. Therefore ibrutinib carries potential to treat other VEGFR2 associated disease. Structure-based drug repositioning explains ibrutinib's anti VEGFR2 action through the conservation of a specific pattern of interactions of the drug with BTK and VEGFR2. Overall, structure-based drug repositioning was able to predict these findings at a fraction of the time and cost of a conventional screen.status: publishe

Structural Database for Lectins and the UniLectin Web Platform

The search for new biomolecules requires a clear understanding of biosynthesis and degradation pathways. This view applies to most metabolites as well as other molecule types such as glycans whose repertoire is still poorly characterized. Lectins are proteins that recognize specifically and interact noncovalently with glycans. This particular class of proteins is considered as playing a major role in biology. Glycan-binding is based on multivalence, which gives lectins a unique capacity to interact with surface glycans and significantly contribute to cell-cell recognition and interactions. Lectins have been studied for many years using multiple technologies and part of the resulting information is available online in databases. Unfortunately, the connectivity of these databases with the most popular omics databases (genomics, proteomics, and glycomics) remains limited. Moreover, lectin diversity is extended and requires setting out a flexible classification that remains compatible with new sequences and 3D structures that are continuously released. We have designed UniLectin as a new insight into the knowledge of lectins, their classification, and their biological role. This platform encompasses UniLectin3D, a curated database of lectin 3D structures that follows a periodically updated classification, a set of comparative and visualizing tools and gradually released modules dedicated to specific lectins predicted in sequence databases. The second module is PropLec, focused on β-propeller lectin prediction in all species based on five distinct family profiles. This chapter describes how UniLectin can be used to explore the diversity of lectins, their 3D structures, and associated functional information as well as to perform reliable predictions of β-propeller lectins