Antibodies in Screening

-S-S -S-S -S-S -S-S S- S ANTIBODIES IN SCREENING Antibodies have transcended their biological roles to become effective therapeutic agents. In this infographic, we will outline key screening strategies used in the development and production of therapeutic antibodies, including high throughput screening and artificial intelligence (AI). WHAT ARE ANTIBODIES? Antibodies are large, Y-shaped glycoproteins produced by B cells of the immune system. They target and neutralize “foreign” molecules, like those found on bacteria and viruses by binding to a target antigen at a region called an epitope. ANTIBODY STRUCTURE Antigen binding site Antibodies consist of four polypeptides: Two light chains -S-S Two heavy chains -S-S- The variable region S S differs across antibodies S S The base of the Y shape, the and gives the antibody its Fc region, determines the specificity for binding to a response that is triggered by target antigen. S S the antibody–antigen binding. S S The first therapeutic WHAT ARE THERAPEUTIC ANTIBODIES? antibody to be Therapeutic antibodies represent one of the licensed was muromonab- fastest-growing classes of new drugs. CD3, a mouse hybridoma In 2023, the FDA approved 12 therapeutic monoclonal antibody. The drug antibody drugs: 8 IgG molecules, 3 bivalent received approval from the US bispecifics and 1 trivalent bispecific Food and Drug Administration They can be designed to target a wide variety (FDA) in 1986 for use in of molecules with high affinity, allowing them preventing transplant to precisely target the molecular mechanisms rejection. that underpin disease. EXAMPLES INCLUDE: Monoclonal antibodies (mAbs) mAbs are produced by a single immune cell clone to produce a homogenous antibody population. Antibody fragments They bind tightly to almost any antigen Their relatively small but can be expensive to produce. size helps them to reach difficult targets and penetrate tissues. Using microbial expression systems, they may also be simpler to produce than full-size antibodies. Drug mAb Linker Bispecific antibodies Antibody-drug conjugates These are engineered (ADCs) from two antibodies ADCs consist of a mAb in order to target two Anti-target 1 Anti-target 2 attached to a drug via a epitopes at once. chemical linker. For example, targeting Used in cancer treatment, both T cells and tumor ADCs guide drug delivery cells to bring them close to the target tissue. together and eliminate tumor cells. Most therapeutic antibodies are approved for oncology. Other therapy areas include: Immune-related disorders Infectious diseases Cardiovascular diseases 46.06% - Oncology 27.27% - Immunology 10.30% - Infectious Disease 4.24% - Hematological Disorders 4.24% - Neurological Disorders 2.42% - Genetic Diseases 2.42% - Ophthalmology 1.82% - Metabolic Disorders 1.21% - Musculoskeletal Disorders Primary indications for approved antibody therapeutics and those in late-stage clinical studies. Based on data as of July 1, 2022. DEVELOPMENT OF THERAPEUTIC ANTIBODIES What do we look for when developing therapeutic antibodies? Efficacy Its ability to, once bound, successfully elicit a biological response and modulate the chosen mechanism. Specificity and affinity Must be highly specific to the target antigen and bind with a strong affinity to maximize its therapeutic potential. Safety Present a low risk of adverse effects, such as triggering immune responses or reactivity with non-target tissues. Developability This depends on the antibody’s stability, solubility and large scale manufacturability. ANTIBODY DEVELOPMENT FALLS INTO SEVERAL STAGES: 1 2 Target identification and validation Hit generation and lead identificatio • Gather data to support target • Specificity, affinity and functionality selection testing in vitro and in vivo • Experimentally identify and validate • Evaluate leads with desirable selected target properties 3 4 Lead engineering and optimization Candidate selection • Generate hits with display and hybridoma approaches • Data analysis • Select leads with desirable • Candidate should have strong biochemical properties therapeutic potential and optimized activity and developability • Demonstrate efficacy in vivo • Epitope mapping HIGH-THROUGHPUT SCREENING APPROACHES Antibody screening takes place during lead identification, and screening large libraries of lead candidates can be time-consuming and labor-intensive. However, high-throughput approaches can enable 1000s of candidates to be tested quickly. EXAMPLES OF HIGH-THROUGHPUT APPROACHES INCLUDE: Antibody-bearing bacteriophages Phage display • Identifies high-affinity interactions between antibodies and antigens by displaying proteins on the surface of bacteriophages. • Genetic sequence encoding antibodies are Phages Display Selection Cycle integrated into the DNA of bacteriophages. Amplificatio Selective binding Millions of antibody-bearing bacteriophages can be screened against immobilized antigens. • Relatively fast and can be used to identify binders in large-scale libraries. Specific phages Unbound phages Hybridoma • Antibody-producing B cells are fused with immortal Inject Antigen myeloma cells to give rise to hybridoma cell lines, which perpetually produce identical monoclonal Myeloma cells antibodies • Assays such as ELISAs can be used to screen B cells hybridomas to identify monoclonal antibodies with high antigen affinity • Resulting antibodies are highly specific, but Hybridoma cells can take a long time to produce and require Monoclonal Antibody humanization. Artificial intelligence and machine learning approaches • AI has the potential to improve upon other slow, expensive and laborious antibody screening methods – it is already reshaping the landscape of small molecule drug discovery. Antigen • Large language models (LLMs) trained on protein sequences – called Epitope protein language models – can be applied to antibody generation. Paratope • AI stands to be particularly useful for screening approaches such as: • Epitope/paratope mapping – Predicting the areas of the antibody (the paratope) and antigen (the epitope) involved in binding. • Affinity optimization – Affinity prediction using sequences and 3D structures could increase screening throughput and guide rational design. • Off-target prediction Antibody – Computational methods can predict binding to unrelated proteins, possibly helping to reduce clinical trial failures. • De novo antibody design – AI may enable novel antibodies to be designed from scratch (de novo), instead of improving existing antibody sequences. The landscape of antibody development continues to evolve, with more effective and targeted antibody therapies on the horizon. Screening aided by advances in high-throughput approaches and AI stands to accelerate the development of new and innovative treatments for a myriad of conditions. Sponsored by S-S -S-S- -S-S- -S-S- -S-S-