Conference Day One - Wednesday June 4, 2025
7:00 am Check in & Morning Refreshments
8:20 am Program Director’s Opening Remarks
8:20 am Chair’s Opening Remarks
Maximizing the Structural Biology Toolbox for Structural Generation to Accelerate Tailored Drug Design
8:30 am Structure-Guided Drug Design of MTA-Cooperative PRMT5 Inhibitors
Synopsis
- Highlight rationale for targeting MTA-bound PRMT5 in MTAP-deleted cancers
- Describe efforts informed by structure to convert SAM-cooperative PRMT5 inhibitors to MTA-cooperative PRMT5 inhibitors
- Highlight role of structural biology during efforts to advance a different chemical series from a modestly potent HTS hit to the clinical-stage MTA-cooperative PRMT5 inhibitors TNG908 and TNG462
9:00 am Pushing the Boundaries in Protein, Particle & Cell Imaging to Power Discovery & Development with Electron Microscopy
9:30 am Structure-Guided Drug Design of MTA-Cooperative PRMT5 Inhibitors
Synopsis
- Highlight rationale for targeting MTA-bound PRMT5 in MTAP-deleted cancers
- Describe efforts informed by structure to convert SAM-cooperative PRMT5 inhibitors to MTA-cooperative PRMT5 inhibitors
- Highlight role of structural biology during efforts to advance a different chemical series from a modestly potent HTS hit to the clinical-stage MTA-cooperative PRMT5 inhibitors TNG908 and TNG462
10:00 am Speed Networking
Synopsis
This informal session provides the perfect opportunity to connect with your industry colleagues, from structural biologists to medicinal and computational chemists, protein engineers, and drug discovery experts. Instigate useful introductions to build upon for the rest of the conference forming valuable connections.
10:45 am Morning Break
Cultivating Data Acquisition & Management of Structural Insights to Maximize Drug Design
11:00 am Interactive Roundtable: Overcoming Challenges in Structural Data Acquisition & Management
Synopsis
This interactive session gives you the opportunity to be part of the discussion—get ready to share ideas and learn from your peers. Among the key talking points to consider:
- Optimizing Structural Data Management: How can we address the challenges of storing and processing large datasets from Cryo-EM, Cryo-ET, NMR, and X-ray crystallography? What strategies—such as cloud computing, automated data pipelines, or advanced storage solutions—are proving most effective in balancing cost, accessibility, and processing power?
- Standardization & Cross-Collaboration: How do differences in data handling across structural biology techniques impact workflow standardization, and what approaches can harmonize data management for better reproducibility?
- Enhancing Sample Preparation for Higher Resolution: What are the best strategies for reducing sample requirements while achieving higher resolution? How can optimized protein expression, purification protocols, and sample modifications improve data quality across different structural techniques?
- Cost-Effective Innovations: With the growing demand for high-quality structural insights, what emerging technologies and methodologies are helping reduce the cost of data acquisition while maintaining accuracy and efficiency?
Join this discussion to share your experiences, hear real-world strategies from your peers, and walk away with actionable insights to enhance your structural data collection and management workflows.
11:30 am Towards Automated, High-Throughput Cryo-EM Data Analysis
Synopsis
- Novel algorithms for improving particle localization and map isotropy
- Novel tools & features of the CryoCloud platform
- Case-studies on high-throughput structure determination by cryo-EM
12:00 pm Lunch Break
Utilizing Structural Insights Bridging Medicinal Chemistry & Computational Chemistry for Improved Drug Design
1:00 pm Leveraging Structural Insights for Protein Engineering & Drug Stability Optimization
Synopsis
- Examining how structural biology techniques, including crystallography and HDX, reveal conformational flexibility and drive protein engineering decisions
- Bridging structural insights with computational modelling to stabilize biologics and improve their pharmacokinetics in circulation
- Applying protein engineering strategies to mimic small-molecule-induced stabilization, enhancing therapeutic potential beyond traditional medicinal chemistry approaches
1:30 pm Structure without Compromise: Empirical Epitope Mapping for High- Throughput Hit-to-Lead and Optimization
Synopsis
- The best antibodies are those that exhibit specificity to disease or targets, that limit liabilities for production and therapeutic delivery, and that demonstrate the best function – but these are difficult to predict when relying on the typical antibody characterization approaches
- By leveraging high-throughput, high-resolution structure determination and combining it with more conventional bioanalytical and functional assessments, we systematically selected for the antibodies exhibiting the most desirable attributes against several mechanistic targets
- We demonstrate how structural insights can be gleaned from very difficult targets, including on membrane-stabilized GPCRs, and how dynamics in addition to binding sites are critical to function and prediction
2:00 pm Panel Discussion: Bridging Medicinal & Computational Chemistry with Structural Insights for Smarter Drug Design
Synopsis
- Overcoming challenges in integrating structural and computational approaches to advance from target identification to lead development
- Real-world success stories and lessons learned from projects were collaboration between disciplines significantly improved drug candidates
- Strategies for future-proofing drug discovery pipelines by embedding structural insights into medicinal and computational chemistry workflows
2:30 pm Afternoon Break & Poster Session
Leveraging AI & Machine Learning in Structure-Based Drug Development from Predicting Protein Folding to Optimizing Experimental Workflows
3:30 pm ML Augmented Active Learning for Structure-Based Biologics Engineering
Synopsis
- Discuss how AI models are increasingly being used to predict the stability of proteins, addressing common drug development challenges like aggregation and misfolding
- Explore the integration of AI-driven generative models in solving protein stability issues and facilitating the design of more robust and soluble therapeutic proteins
- Integrating AI predictions into the broader drug design pipeline to accelerate lead optimization
4:00 pm Discovery of Nonretinoid Antagonists of Retinol-Binding Protein 4 for the Treatment of Atrophic Age-Related Macular Degeneration and Stargardt Disease
Synopsis
- Antagonists of retinol-binding protein 4 (RBP4) impede ocular uptake of serum all-trans retinol and have been shown to reduce cytotoxic bisretinoid formation in the retinal pigment epithelium (RPE), which is associated with the pathogenesis of both atrophic age-related macular degeneration (AMD) and Stargardt disease
- Computer-assisted drug design based around several RBP4 protein crystal structures was used to help design and computationally evaluate novel nonretinoid RBP4 antagonists
- Potent RBP4 antagonists were identified with favorable drug-like characteristics that reduced circulating plasma RBP4 levels, demonstrating in vivo target engagement and potential as oral treatments for atrophic AMD and Stargardt disease
4:30 pm Expanding AI-Driven Structural Predictions Beyond Proteins with Insights on Modeling Complex Molecular Interactions
Synopsis
- Exploring how OpenFold3 is expanding beyond proteins to predict interactions with RNA, DNA, small molecules, and ionizable lipids
- Insights from retraining AlphaFold2 and OpenFold to uncover how deep learning models generalize and refine structural predictions
- Discussing the importance of experimental studies in validating AI-generated structural predictions and improving model accuracy
5:00 pm Panel & Audience Discussion: Beyond the AI Hype – Overcoming the Barriers to Fully Maximizing AI in Drug Design
Synopsis
This panel brings together experts to discuss the real challenges in adopting AI in drug design, moving beyond the hype to practical solutions for overcoming barriers related to data quality, integration, and model reliability.
- What are the current limitations and challenges in leveraging AI within the context of drug design and structural biology?
- How can the scientific community ensure that AI models are properly validated, integrated with experimental data, and implemented in real-world workflows?
- What advancements are needed in AI, data management, and experimental techniques to unlock its full potential for drug development?
5:30 pm Chairs Closing Remarks
Networking & Poster Session Continued
Synopsis
The Poster Session is a unique opportunity to present your latest research and engage with leading experts in the field. This is your chance to showcase your work to an audience of industry pioneers and decision-makers. Gain valuable feedback, spark collaborations, and elevate your visibility within the SBDD community. Submit your poster and be part of the conversation shaping the future of structure-based drug design!