Société Française de Bioinformatique

Mots-Clés

fragment-based drug design benchmark datasets protein-ligand complex

Description

ICOA brings together more than 120 people, including lecturers, researchers, postdoctoral researchers, doctoral students, engineers, technicians, and administrative staff. One of the institute’s main activities focuses on the discovery of new bioactive molecules with potential applications as drugs, imaging probes, or as ingredients in cosmetic products. The internship will be conducted within the Structural Bioinformatics and Chemoinformatics (SB&C, https://www.icoa.fr/fr/bioinformatique-structurale-et-chemoinformatique-sbc/ ) team led by Pr. Pascal Bonnet and Dr. Samia Aci-Sèche, focusing on the development and application of new in silico methods to understand biomolecular structures and design new innovative compounds for the fields of therapeutic innovation, cosmetics and analytical chemistry.

Project proposal:
The search for drug candidates has greatly improved over the past several years, thanks to numerous innovative strategies. Among them, Fragment-Based Drug Design (FBDD) has emerged as a powerful approach, of which 8 drugs have already received FDA approval. In this context, we first introduced Frags2Drugs (F2D), an innovative in silico FBDD tool for the design of novel protein kinase inhibitors. More recently, the tool has been undergoing progressive extension to the entire proteome through a comprehensive revision of the underlying methodology. However, evaluating the performance of such a tool remains challenging because of the lack of dedicated, structurally curated and annotated validation datasets.
The objective of this internship will focus on the development of benchmark datasets. The project will build on an existing collection of curated protein-ligand complexes and established workflows for structural file preparation. The work will involve the selection and filtering of relevant complexes, structural comparison, preparation and standardization of the selected systems, and their organization into validation subsets. The resulting datasets will then be used to assess the performance and limitations of the tool.

Qualifications:
• Master 2 or engineering student in bioinformatics, computational chemistry, structural
• biology or a related field.
• Basic knowledge of bioinformatics and/or computational biology
• Experience with programming (Python)
• Familiarity with Linux environments
• Strong analytical and communication skills