Brief history and administrative status

The Computational Drug Discovery group is part of the Pharmaceutical Design and Discovery Unit, one of the Faculty of Pharmacy nine Units involved in the Drug Research Program. It was created in 2008 as part of the Centre for Drug Research (reorganized in 2014) and since then is led by Dr Henri Xhaard. For administrative and teaching purpose, personal and related activities in the Faculty are also transversally assigned to divisions: members of the CDD group are mostly attached to the Division of Pharmaceutical Chemistry and Technology, but some activities (Drug Discovery and Chemical Biology consortium) are attached to the Division of Pharmaceutical Biosciences..


We are a problem-oriented group, i.e. we select the most suitable methods used to the problem at hand. we have an extremily broad scope that covers many aspects of chemoinformatics and structural biology. Our projects are conducted taking advantage on a network of

Target-based applications

Molecular modeling and protein exploration. We use a combination of commercial state of art tools under academic licences (DiscoveryStudio Ldt, Schrödinger Ldt packages), Modeller. We have also acess to the moldiscovery suites (MOKA, Volsurf+, GRID).

Most chemoinformatics application. Secondly virtual screening . we have experienc ein pharmacophore modeling (Turku et al., 2016).

Targets favor membrane proteins, GPCRs, transporters, membrane-bound enzymes.

Data mining and analysis

We have acquire experience in data mining at different level. Data is further stored and processed in databases :

  • Structural 3D data (essentially from the PDB). See for example Borrel at al., 2016; Borrel at al., 2017.
  • Genomic data. See Rinne et al., 2019.
  • Chemogenomic data (small molecule-target-activities). See Legehar et al., 2016.

Data is procesed using machine learning applications for predictive modeling. including deep learning.

QSAR and QSPR modeling, including CoMFA/CoMSIA

Computational tool development

Scripts in Python and other advanced programming langages. We follow good programming practices (code annotation, code-sharing and backups).