The peptide global market is rapidly expanding with its value estimated at $14.4 billion, accounting for 1.5% of the total worldwide pharmaceutical market. These peptides are usually between 5 and 40 amino acids and have a diverse range of applications and many advantages, including their ability to be produced at a large scale. Significant advancements in synthetic and recombination technologies have been a driving force in bringing bio-active peptides back to center stage as therapeutic and diagnostic tools. However, similar advances in artificial intelligence (AI) and data analytics methods for peptides are needed.
Recent advances in structural protein prediction have enabled rapid design of proteins with desired structural properties. However, understanding how to design proteins with specific functional or multi-functional properties is still challenging. This is critically important for smaller proteins – peptides – where there is often less secondary or tertiary structure to predict, and the functionality has a great dependence on extrinsically bound factors.
It is clear that new computational technology is needed to meet the requirements of the community that leverages the AI advances seen in protein modelling. However, peptide datasets are generally much smaller than protein training datasets, make it harder to build relevant AI representations, especially for non-canonical amino acids. To successfully scale AI in peptide studies, collaboration is necessary that integrates activities of data collection, software development, transfer learning and implementation.
This workshop seeks to bring together experts currently working in AI and peptide research. The workshop will highlight current state of the art machine learning techniques, including large language models (LLMs) and explainable AI being applied to peptide analysis and prediction. There will be a focus on establishing open-source guidelines and best practices in light of the recent EU AI act. This workshop has been approved as a CECAM flagship workshop.