Computational methods can significantly shorten the drug discovery process, accelerating the identification of hit compounds against a therapeutic target and the progression into promising pre-clinical candidates. When used effectively, computational approaches help predicting the molecules that are most likely to succeed, preventing unnecessary wet chemistry and saving time, money, and resources.
In this webinar, we will show how computational tools help research chemists discover and optimize novel small molecules more efficiently and effectively through the synergistic application of ligand-based and structure-based methods. These include cutting-edge methods such as Free Energy Perturbation (FEP) for accurately predicting the biological activity of new compounds before synthesis, and tools for understanding the structure-activity relationships of ligand series to inform new molecule design.
Key Learning Objectives:
- Understand how to synergistically apply different computational methods to analyze the information available in a drug discovery project, obtaining valuable information on what to do next.
- Learn the benefits and limitations of different methods for predicting the activity of new compounds and find the best molecules to progress.
Who Should Attend:
- Computational chemists
- Medicinal and synthetic chemists
- Drug discovery scientists in academia
- Drug discovery scientists in biotechnology, pharmaceutical, agrochemical, flavor and fragrance industry
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