Prof Dame Carol Robinson, Dr Andrew Doré and Prof Paula Booth will deliver keynote presentations at the conference, touching on AI integration, challenging drug targets and the next generation of biologic medicines.
Three leading scientists in protein science, structural biology and artificial intelligence will headline this year’s Protein Sciences in Drug Discovery conference, bringing together experts from academia and industry to examine emerging approaches to modern drug discovery.
Prof Dame Carol Robinson DBE FRS FMedSci FRSC, Dr Andrew Doré and Prof Paula Booth will deliver keynote presentations at the event, which takes place at GSK Stevenage from 10–11 November 2026.
The conference is organised by ELRIG, a not-for-profit, volunteer-led organisation supporting the global drug discovery community, in partnership with The Protein Society, an international scholarly society focused on advancing research into protein structure, function, design and applications.
The Protein Society is excited to continue our partnership with ELRIG to bring together scientists from academia and industry around some of the most rapidly advancing areas of protein science.”
Professor Heather Pinkett, President of The Protein Society
AI and protein science in focus
The free-to-attend event will explore developments in AI and machine learning, challenging drug targets and complexes, antibody and biologic developability and quality control, as well as the production of non-standard binding proteins.
Dr Andrew Doré, Head of Structural Biology at Isomorphic Labs, will discuss the use of AI in drug discovery in his presentation, ‘Engineering the Future of Drug Discovery: Isomorphic Labs’ AI-First Approach’.
Dr Doré previously founded and led Structural Biology at Heptares Therapeutics, where his team delivered landmark GPCR structures that helped advance drug candidates into clinical development. At Isomorphic Labs, he is now applying AI alongside structural biology to the design of next-generation medicines.
From proteins to new medicines
Prof Dame Carol Robinson, Director of the Kavli Institute for Nanoscience Discovery at the University of Oxford, will open the scientific programme with a presentation on ‘Cell Surface Receptors and Transporters; Insights From Native MS’.
Prof Robinson is recognised for establishing mass spectrometry as a technology for investigating the structure, function and interactions of proteins and protein complexes. She founded OMass Technologies, now OMass Therapeutics, which uses native mass spectrometry in the development of therapies for immunological and genetic disorders.
Professor Paula Booth, Daniell Chair of Chemistry at King’s College London, will close the keynote programme with ‘Membrane Protein Tool-kit: Co-translational Folding in Native Lipid Environments’.
Her research examines how integral membrane proteins fold and interact with their surrounding lipid environment, with implications for understanding biological processes and developing new approaches in drug discovery.
Speaking of her appointment, Professor Booth said: “I’m delighted to participate in Protein Sciences in Drug Discovery 2026, and to have the chance to bring membrane protein folding – a critical but often overlooked process – into prevailing drug discovery conversations.”
Collaboration across the sector
The conference will also provide opportunities for scientists from academia, pharmaceutical companies, biotechnology firms and contract research organisations to share research, build collaborations and meet technology and service providers.
Early Career Professionals will be able to showcase their research through a poster programme, with an award recognising emerging scientific talent in drug discovery.
Speaking of the conference, Dr Del Trezise, Chair of ELRIG, said: “Protein science continues to play a critical role in modern drug discovery. This year’s Protein Sciences in Drug Discovery will provide leading scientists from academia and industry with a unique platform to share advances across rapidly developing areas in the field, particularly AI and machine learning.”
No comments yet