Explore the Agenda
8:30 am Check-in
Check In & Light Refreshments
8:55 am Chair’s Opening Remarks
Expanding the Impact of Structural Insight by Translating Experimental Findings into Novel Modalities & Dynamic Target Systems Kasia Handing Associate Director of Structural Biology & Biophysics Tango Therapeutics 9.00 Hit Finding & Assay Enablement fo
9:00 am Hit Finding & Assay Enablement for MGAT1, a Novel Glycosyl Transferase Involved in Cancer Cell Immune Evasion
- Identification of novel MGAT1 binders and inhibitors using two orthogonal discovery strategies: a UDPGlo™–based highthroughput enzymatic screen to identify functional inhibitors, and a DNAencoded library (DEL) screen to uncover compounds that bind MGAT1
- Mechanistic characterization of compound binding through the implementation of SPR competition assays, enabling direct interrogation of binding mode and target engagement
- Structural elucidation of ligand–MGAT1 interactions via highresolution crystal structures, revealing a welldefined binding site distinct from the active site and providing strong structural support for the proposed mechanism of action
9:30 am Targeting the SK2 Potassium Channel: Enabling Structure-Based Drug Discovery of Membrane Proteins Through an Integrated Cryo EM Pipeline
- Integrating rapid construct screening approaches to optimize design, expression, and protein yield
- Developing robust biophysical assays to validate screening hits and prioritize targets for structural studies
- Implementing end-to-end cryo-EM workflows including grid preparation and screening, data processing, model building, and structure interpretation
10:00 am Stabilizing Functional GPCR States Using ConfoBodies to Enable Structure-Guided Discovery
- Case study demonstrating how structural insights led to De Novo Nanobody discovery
- Addressing the challenge of isolating GPCRs from the membrane while preserving functional folding and conformational integrity for structural analysis
- Applying complementary structural and biophysical techniques to distinguish functionally relevant GPCR States from preparation-induced or non-productive conformations
10:30 am Morning Break
11:30 am Reframing Structure-Based Drug Design for Induced Proximity Modalities in Multi-Protein Systems
- Designing constructs, stabilization strategies, and binding partners to bias multi-protein assemblies toward structurally tractable states without distorting biology
- Determining when cryo-EM, crystallography, HDX-MS, or native MS are best suited to resolve induced proximity complexes with partial or dynamic occupancy
- Evaluating where co-folding, docking and modelling of multi-protein assemblies have aligned with function
- Strategies for managing scale and throughput when programs demand repeated structural readouts
12:00 pm Resolving an Allosteric Binding Pocket in the HSV H-P Complex to Inform Antiviral Drug Design
- Optimizing Cryo-EM data acquisition and processing strategies to resolve ligand-bound states in conformationally heterogenous, multi-subunit viral complex
- Applying cryo-EM and complementary biophysical experiments to reveal ligand-stabilised allosteric binding sites that were absent in apo structures and not predictable from homology or co-folding models
- Recognizing limits of computational and biophysical methods, and utilizing mutational and omics data to validate binding sites
12:30 pm Lunch Break & Networking
1:30 pm Harnessing the Strength of Structural Analysis to Reveal Hidden Binding Opportunities in Complex Targets
- Comparing apo versus ligand-bound structures across cryo-EM and crystallography datasets to detect induced-fit or cryptic pocket formation which enable alternate binding sites
- Addressing experimental challenges in resolving low-occupancy or transient pockets, including sample heterogeneity, preferred orientation, and conformational averaging in cryo-EM datasets
- Reviewing computational strategies for predicting and optimizing binding modes, and retrospectively benchmarking against internal structural data sets to drive confidence in predictive models
2:00 pm AI-Enabled Structural Vaccinology Using Gemini to Accelerate Antigen Discovery
- Sharing a case-study on the development of an AI/ML tool that pairs structural similarity and functional features to identify novel vaccine targets
- Understanding how structure-based epitope mapping is revolutionizing the design of antibodies by identifying key binding sites on complex antigens, leading to higher affinity and specificity in vaccine development
- Exploring how high-resolution structural data can be applied to design vaccines with enhanced stability, reduced immunogenicity, and improved pharmacokinetic properties
2:30 pm Afternoon Break
Facilitating Collaboration, Streamlining Workflows & Integrating Structural Biology Across Discovery Functions to Strengthen Cross-Functional Alignment & Developability Decisions
3:00 pm Evolving AI-Enabled Hit Discovery: Balancing Prediction, Screening & Data Collaboration
- Providing a strategic perspective on how virtual screening and generative AI are reshaping hit identification and early optimization across global discovery programs
- Highlighting the interface between structural biology with hit discovery to validate binding hypotheses and guide early series expansion
- Outlining data strategy priorities, including expanding experimentally validated binding datasets through internal coordination and pre-competitive collaboration
3:30 pm Impact of Structural Biology in an Increasingly Fast-Paced Drug Discovery Environment
- Addressing the perceived mismatch between rapid AI-driven discovery cycles and slower experimental structural biology workflows
- Ensuring structural biology remains a critical decision-making tool rather than a downstream support function
- Integrating structural biology, computational chemistry, and AI/ML teams to drive confident discovery decisions
- Lessons from building cross-functional structural biology capabilities within a modern pharma organization
4:00 pm Roundtable Discussion: Building Trust & Designing Structural Data Collaboration for Industry-Scale Programs
Despite rapid advances in co-folding models, foundation architectures, and AI-driven structure prediction, one constraint continues to limit progress: access to sufficiently diverse, high-quality structural datasets. Individual organizations rarely hold enough breadth to train highly predictive models across modalities and target classes, yet historical consortium efforts have struggled due to confidentiality concerns, governance complexity, and unclear value exchange.
This interactive discussion will allow open discussion with industry peers to identify opportunities for
collaboration by discussing:
Data Contribution:
- The minimum viable data contributions (structural diversity, ligand space, experimental annotation) that would be required to improve predictive models
- How value should be quantified and fairly exchanged?
- Whether collaborations should be modality-specific?
Competitive Boundaries:
- What technical, legal and operational safeguards would be required?
- What would need to change from previous consortium models to make future participation viable and more attractive?
4:30 pm Scaling Structural AI Through Data Collaboration Without Comprising Confidentiality
- Addressing the data bottleneck in limiting predictive model performance
- Explaining federating learning frameworks and how they enable companies to retain full data and IP control, while contributing to shared model improvements
- Providing an update on dataset diversity, scale and benchmarking strategies; coupled with future plans for the initiative