Alpay Seven
Head of Structural Biology Deep Apple Therapeutics
Alpay Seven is Director at Deep Apple Therapeutics, where he helps drive the integration of artificial intelligence, large-scale molecular docking, cryo-electron microscopy, and deep learning to accelerate drug discovery. As a founding scientist and former Head of Structural Biology, he has played a key role in building the company’s structure-guided drug discovery platform. Prior to Deep Apple, Alpay conducted pioneering research at Stanford University and the University of Michigan, focusing on GPCRs, cytokine receptors, and protein signaling pathways. He earned his PhD from UT Southwestern Medical Center, where his work on neurotransmitter release and membrane fusion contributed to publications in leading scientific journals.
Seminars
- Leveraging structural information to establish computational screening methods
- Disclosure of an inactive state structure of MRGPRX2 in complex with multiple ligands
- Identification of a clinical candidate DA003 as a potent selective antagonist of MRGPRX2
As cryo-EM becomes increasingly important for structure-based drug discovery, the field is facing a fundamental throughput challenge. Long data collection times, limited microscope access, difficult sample preparation, computationally intensive analysis, and manual structure building can restrict the number of structures that can be delivered to discovery teams. Join structural biology leaders, cryo-EM specialists, and technology developers as they discuss how to scale cryo-EM workflows to meet the growing demands of modern drug discovery by:
- Overcoming access and throughput limitations, examining how companies are managing constrained microscope capacity, external facilities, CRO access, and the need to generate sufficient structures to support increasingly large discovery pipelines
- Improving sample preparation and data quality, discussing how grid development, alternative sample preparation approaches, additives, and better understanding of sample-specific behaviour can reduce failed experiments and increase the probability of obtaining high-quality structures
- Automating the cryo-EM workflow, exploring how advances in instrumentation, AI-enabled data processing, automated structure building, and improved computational infrastructure can reduce manual intervention and increase the number of actionable structures delivered to drug discovery teams
