Section: New Results

Drug Targeting and Adverse Drug Side Effects

Identifying new molecular targets using comparative genomics and knowledge of disease mechanisms is a rational first step in the search for new preventative or therapeutic drug treatments [63]. We are mostly concerned with three global health problems, namely fungal and bacterial infections and hypertension. Through on-going collaborations with several Brazilian laboratories (at University of Mato Grosso State, University of Maringá, Embrapa, and University of Brasilia), we previously identified several novel small-molecule drug leads against Trypanosoma cruzi, a parasite responsible for Chagas disease [91]. With the University of Maringá, we subsequently found several active molecules against the flavoenzyme TRR1 in Candida albicans, and two manuscripts are in preparation. We also proposed several small-molecule inhibitors against Fusarium graminearum, a fungal threat to global wheat production [63], [43]. Two further manuscripts on this topic are currently in preparation. Concerning hypertension, we continued our collaboration with Prof. Catherine Llorens-Cortes at Collège de France to study the interaction between the apelin receptor (a transmembrane protein important for blood pressure regulation) and the aminopetidase A enzyme [47].

It is well known that many therapeutic drug molecules can have adverse side effects. However, when patients take several combinations of drugs it can be difficult to determine which drug is responsible for which side effect. In collaboration with Adrien Coulet (Orpailleur team co-supervisor of Gabin Personeni) and Prof. Michel Dumontier (Biomedical Informatics Research Laboratory, Stanford), we developed an approach which combines multiple ontologies such as the Anatomical Therapeutical Classification of Drugs, the ICD-9 classification of diseases, and the SNOMED-CT medical vocabulary together with the use of Pattern Structures (an extension of Formal Concept Analysis) in order to extract association rules to analyse the co-occurrence of adverse drug effects in patient records [74], [73]. A paper describing this work has been published in the Journal of Biomedical Semantics [70].