Understanding the Limitations, Possibilities & Complementarity of Computational & Medicinal Chemistry Advancements to Predict Peptide Structure & Function
Time: 9:15 am
day: Pre-Conference Workshop Day
Details:
Currently, one of the biggest bottlenecks holding the peptide therapeutic space back from success is the lack of crystal structure data for peptides, making it difficult to understand the 3D nature of interactions of peptides with themselves, other proteins, and ligands. There is a need to advance computational technologies that will help with peptide structure prediction. Additionally, limitations in current medicinal chemistry techniques and a disconnect in understanding the potential of computational and biochemistry approaches in deciphering peptide structure and function further complicate the process.
This workshop provides a deep dive opportunity to learn about:
- The possibilities and challenges of peptide drug prediction and design from a computational, medicinal chemistry and experimental perspective
- Discussing how to help design datasets that are retractable for machine learning, fine tune models and process high volume datasets in an expedited manner
- Using AI/ML-powered algorithms to predict peptide structures, permeability and potency
- Sharing optimized software developments that are turbocharging peptide drug discovery forward
- Utilizing sequence/structure-activity relationships (SAR) studies for lead selection and optimisation
