@ Course Aims and synopsis
Drug discovery is the process through which potential new therapeutic entities are identified, using a combination of computational, experimental, translational, and clinical models. Hence this course will initiate to the participants the main computational techniques used in drug design.
@ Topics:
Biomolecular Modeling and Molecular Dynamics
Drug-likeness and Multi-Parameter Optimization (MPO) methods
Molecular Structure and Biological Activity Dependency: From SAR to QSAR/QSPR Approaches
Molecular Docking and Pharmacokinetics Properties (ADMET)
Machine & Deep Learning Applications in Drug Discovery and Repositioning
Scientific English: Drug Design, a Case in Point
@ The Scientific Programme will be published online soon.
The spring school is organized as a thematic conference supported by workshops. After an introduction from the CRSP Director Chair, experts will present the most popular classes of biomodeling methods, including the use of high-performance computing. Then, we will provide an overview of the opportunities that in silico Computed Aided Drug Design (CADD) approaches offer in some cases a powerful predictive tool to new drug discovery.
The spring school will also cover both structure-based drug design (molecular docking, molecular dynamics, structural bioinformatics tools) and ligand-based drug design (QSAR, ADMET, pharmacophores, deep learning) with lectures and on-hands tutorials. Last day you can try your skills on the ligand selection challenge.
