Postdoctoral Position in Computer-Aided Drug Design
Postdoctoral Position in Computer-Aided Drug Design
Institut Pasteur
Paris, France
A 30-month postdoctoral position in Computer-Aided Drug Design is available at Institut Pasteur in Paris within the Chemoinformatics and Proteochemometrics group of Olivier Sperandio and the Structural Bioinformatics unit of Pr Michael Nilges.
Project background
Among the various molecular mechanisms of antibiotic resistance, changes in antibiotic target by mutation, and reduced access to the target (reduced membrane permeability or increased efflux) are of major importance. Therefore, the development of novel antimicrobial chemical entities with innovative mechanisms of action is a top priority to fuel the shrinking antibacterial pipeline and circumvent those issues. To address this challenge, this project proposes to explore an original path to identify compounds that could interfere with the assembly of essential molecular machineries that are specifically present in bacteria. Thus, this project will target the Protein-Protein Interactions (PPIs) that are the pillars of these molecular machineries using a combination of in vivo and in silico screening.
Job Responsibilities
- Responsible for drug discovery project support:
- Virtual Screening (docking, pharmacophore modeling)
- Structure- and ligand-based drug design
- Machine learning
- Molecular dynamics
- HTS data and SAR analysis
- Communicate with project teams and other departments:
- Interact with other experts in the project in various experimental methodologies.
Candidates Requirements
- PhD and Postdoc in Computational Chemistry or a related discipline with a demonstrated track record in Modeling, Computer Aided Drug Design (CADD) is required
- Expertise in structure- and ligand-based drug design is essential and a former experience of deep learning on the topic would be a plus
- Knowledge of designing chemical probes against protein-protein interactions is a plus
- Profound scientific knowledge and experience in:
- protein crystal structure analysis
- virtual screening, ensemble docking, molecular dynamics simulations
- ligand-protein interactions, protein-protein interactions
- Machine Learning and deep learning
- Familiar with repositories such as AlphaFold Protein Structure Database
- Comfortable under Linux command-line environment
- Experience with a workflow tool (e.g. KNIME, Pipeline Pilot, or Jupyter notebooks) and a programming or scripting language (e.g. python or similar) is a plus
- Good organizational skills: dealing with multiple projects, setting priorities, and meeting deadlines
- Profound communication skills in English as well as experience in dealing with multidisciplinary and multicultural teams
- An enthusiastic, self-motivating and committed approach to delivering high quality results in a demanding environment is essential
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