Difficult-to-Express Proteins
Mastering the Expression, Purification, and Production of Challenging Proteins
5/10/2027 - May 11, 2027 ALL TIMES EDT
As protein therapeutics become increasingly complex and AI-generated designs expand the boundaries of what can be engineered, producing them at the required speed, quality, and quantity remains a fundamental challenge. Cambridge Healthtech Institute’s 22nd Annual Difficult-to-Express Proteins conference will explore the latest strategies for overcoming expression barriers that impede research, discovery, and development. Topics will include alternative hosts and cell-free systems, membrane proteins and GPCRs, multispecific antibodies and other complex formats, and the expression challenges associated with minibinders and de novo proteins. A new session on conjugation precursors will examine redox control and site-specific conjugation for antibody-drug and antibody-oligonucleotide conjugates.
Preliminary Agenda

PLENARY KEYNOTE SESSION

Is AI-Driven Antibody Discovery a Data-Driven Sport?

Photo of Charlotte M. Deane, PhD, Professor, Structural Bioinformatics, Statistics, University of Oxford; Executive Chair, Engineering and Physical Sciences Research Council (EPSRC) , Prof Structural Bioinformatics , Statistics , Oxford University
Charlotte M. Deane, PhD, Professor, Structural Bioinformatics, Statistics, University of Oxford; Executive Chair, Engineering and Physical Sciences Research Council (EPSRC) , Prof Structural Bioinformatics , Statistics , Oxford University

YOUNG SCIENTIST KEYNOTE

Generative Design of Evolution-Resilient Antiviral Biologics

Photo of Pranam Chatterjee, PhD, Assistant Professor, Bioengineering and Computer Science, University of Pennsylvania , Assistant Professor , Bioengineering and Computer Science , University of Pennsylvania
Pranam Chatterjee, PhD, Assistant Professor, Bioengineering and Computer Science, University of Pennsylvania , Assistant Professor , Bioengineering and Computer Science , University of Pennsylvania

Viral evolution can erode the activity of antiviral therapeutics. We integrate evolutionary forecasting with generative molecular design to develop peptides and proteins that remain effective against plausible future variants. Tree-valued Schrödinger bridge matching (TreeSBM) predicts branching evolutionary trajectories and their uncertainty. PROPHET, our multi-objective discrete flow model, then uses these forecasts to generate and optimize biologics for target engagement, therapeutic properties, and robustness across predicted futures. I will present unpublished pseudoviral infection data demonstrating functional envelope variants predicted by TreeSBM and PROPHET-designed peptides that block infection by later variants of concern and interest, using only earlier viral sequences for design.

MULTISPECIFIC AND COMPLEX FORMAT EXPRESSION: ASSEMBLY, PAIRING & QUALITY

Protein Production Platforms for Increasingly Complex Biologics and Multispecifics

Photo of Chelsy Chesterman, PhD, Associate Director, AstraZeneca , Associate Director , AstraZeneca
Chelsy Chesterman, PhD, Associate Director, AstraZeneca , Associate Director , AstraZeneca

Protein Expression Challenges Associated with Multispecifics

Photo of Jane (Yongjing) Guo, PhD, Senior Principal Scientist & Lab Head, Large Molecules Research, Sanofi , Sr Principal Scientist & Lab Head , Large Molecules Research , Sanofi
Jane (Yongjing) Guo, PhD, Senior Principal Scientist & Lab Head, Large Molecules Research, Sanofi , Sr Principal Scientist & Lab Head , Large Molecules Research , Sanofi

Engineering Soluble TCR Bispecifics for Expression and Stability

Photo of Peter E. Molloy, Senior Fellow, Science & Technology, Protein Engineering, Immunocore LLC , Senior Fellow , Science & Technology, Protein Engineering , Immunocore LLC
Peter E. Molloy, Senior Fellow, Science & Technology, Protein Engineering, Immunocore LLC , Senior Fellow , Science & Technology, Protein Engineering , Immunocore LLC

Turning soluble TCRs into viable therapeutics means engineering heterodimers/multimers that express well and remain stable. This talk covers strategies to achieve this across TCR bispecific formats, tracing how these approaches have evolved. It highlights the interplay between affinity enhancement, format choices, expressibility, product quality, and yield, drawing on real lessons learned while taking complex TCR-based molecules from discovery through to developability.

Modified Protein Folding Trajectories Enable Co-expression of Highly Pure Bispecific Antibody Mixtures

Qian Zhao, Sr Scientist, Biologics Discovery, Johnson & Johnson Innovative Medicine , Senior Scientist , Biologics Discovery , Johnson & Johnson Innovative Medicine

MEMBRANE PROTEINS AND GPCRs: FROM SOLUBILIZATION TO SCALE

Protein Expression and G Protein-Based Functional Characterization of Orphan GPCRs

Nam Nguyen, PhD, Senior Principal Scientist, Therapeutic Proteins, Regeneron Pharmaceuticals Inc. , Sr. Principal Scientist , Therapeutic Proteins , Regeneron Pharmaceuticals Inc

Orphan GPCRs present unique challenges for protein expression and functional characterization due to limited tools and poorly understood biology. Using GPR75 as a model, we applied G protein-based approaches to enable functional characterization of this challenging receptor. This presentation will highlight strategies for expressing and evaluating functional GPCR systems and demonstrate how protein expression and G protein coupling can support characterization of therapeutically relevant orphan receptors.

Producing Multipass Membrane Proteins in Virus-like Particles for Antibody Discovery

Photo of Allan Mills, PhD, Research Scientist, Antigen Production, Institute for Protein Innovation , Research Scientist , Antigen Production , Institute for Protein Innovation
Allan Mills, PhD, Research Scientist, Antigen Production, Institute for Protein Innovation , Research Scientist , Antigen Production , Institute for Protein Innovation

Virus-like particles (VLPs) provide a lipid membrane environment for challenging targets, including GPCRs and tetraspanins. We present strategies to increase expression of these multipass membrane protein targets and enhance their incorporation into VLPs for antigen display, along with methods for subsequent particle purification. We also discuss adaptations of VLP-based antigen display for antibody discovery workflows. We identify optimized conditions that improve results for downstream antibody discovery and validation.

Designing de novo WRAPs for Detergent-Free Expression of Membrane Proteins

Photo of Pooja D. Bandawane, PhD Student, Baker Lab, University of Washington , PhD Student , Baker Lab , University of Washington
Pooja D. Bandawane, PhD Student, Baker Lab, University of Washington , PhD Student , Baker Lab , University of Washington

Membrane proteins are among the hardest targets to express and study, and conventional extraction requires detergents, which are laborious to optimize and often destabilize the protein. We use deep learning-based computational protein design to create WRAPs, de novo proteins that wrap around a membrane protein's hydrophobic surface. Fused to the target, WRAPs enable expression in E. coli without detergents or changes to the native sequence. WRAPed proteins are thermostable and retain enzymatic and ligand-binding function, and a WRAPed porin yielded a 2.95 Ã… cryo-EM structure; we are currently exploring potential applications in drug discovery and vaccine design.

Engineering Soluble Representations of Challenging Targets for Antibody Discovery

Photo of Alexander Taguchi, PhD, Director of Machine Learning, iBio Inc. , Director , Machine Learning & Antibody Discovery , iBio Inc
Alexander Taguchi, PhD, Director of Machine Learning, iBio Inc. , Director , Machine Learning & Antibody Discovery , iBio Inc

With the rapid advancement of AI-driven drug discovery, the production of quality antigens for screening and selection has emerged as a critical bottleneck. By engineering antigens for enhanced expression, solubility, and stability, we unlock previously intractable targets for antibody discovery. We highlight applications to GPCRs and structurally complex proteins, demonstrating how generative AI coupled with high-throughput experimental validation can expand the landscape of therapeutically accessible targets.

MINIBINDERS AND DE NOVO THERAPIES: CLOSING THE AI DESIGN-TO-EXPRESSION GAP

Producing and Profiling de novo-Designed Antibodies

Photo of Allison Sheen, PhD, Senior Scientist, Nabla Bio Inc. , Senior Scientist , Nabla Bio Inc
Allison Sheen, PhD, Senior Scientist, Nabla Bio Inc. , Senior Scientist , Nabla Bio Inc

Production and Purification of an 11 Valent Multispecific Immune Cell Engager

Photo of Arturo Vera-Rodriguez, PhD, Head, Bioprocess Development, AI Proteins , Head , Bioprocess Dev , AI Proteins
Arturo Vera-Rodriguez, PhD, Head, Bioprocess Development, AI Proteins , Head , Bioprocess Dev , AI Proteins

EXPRESSION TO CONJUGATION: ENGINEERING ADC-READY PRECURSORS

From Expression to Conjugation: Genetically Encoded Tetrazines for Programmable Therapeutic Proteins

Photo of Ryan Mehl, PhD, Professor, Director, GCE4All, Biochemistry & Biophysics, Oregon State University , Professor , Biochemistry & Biophysics , Oregon State University
Ryan Mehl, PhD, Professor, Director, GCE4All, Biochemistry & Biophysics, Oregon State University , Professor , Biochemistry & Biophysics , Oregon State University

Precision bioconjugation starts with engineering proteins that carry reliable, site-specific reactive handles. We will introduce UniTet, an evolved genetic code expansion platform that enables efficient tetrazine incorporation at low substrate concentrations across bacterial and mammalian expression systems, supporting antibody fragments, full-length antibodies, and functional ADC production. A complementary antibody–IL-2 study uses rapid tetrazine ligation to assemble conjugates with varied attachment sites and linker lengths, revealing topology-dependent changes in regulatory T cell expansion, systemic exposure, and inflammatory cytokine responses in vivo. Together, these advances connect efficient production of conjugation-ready proteins with programmable therapeutic function.

Engineering Noncanonical Amino Acids into ADC-Ready Precursors for Site-Specific Conjugation

Photo of Abhishek Chatterjee, PhD, Professor, Chemistry, Boston College , Professor , Chemistry , Boston College
Abhishek Chatterjee, PhD, Professor, Chemistry, Boston College , Professor , Chemistry , Boston College

For more details on the conference, please contact:
Daniel Barry
Senior Conference Director
Cambridge Healthtech Institute
Phone: +44 7837 651 303
Email: dbarry@healthtech.com

For sponsorship information, please contact:

Companies A-K
Jason Gerardi
Sr. Manager, Business Development
Cambridge Healthtech Institute
Phone: +1 781-972-5452
Email: jgerardi@healthtech.com

Companies L-Z
Ashley Parsons
Manager, Business Development
Cambridge Healthtech Institute
Phone: +1 781-972-1340
Email: ashleyparsons@healthtech.com


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