Laboratory of Antibody Design

1. Members

Title	Name
Project Leader	Satoshi Nagata
Senior Researcher	Yuji Masuta
Project Researcher	Tomoko Ise
Collaborative Research Scientist	Hao Ding, Masaki Inoue, Yifan Li, Yuta Inai, Koichiro Suzuki
Visiting Researcher	Hiroki Akiba, Takuya Iwasaki
Technical Assistant	Kayoko Kato, Reiko Sato
Administrative Assistant	Megumi Mori
Trainee	Yuta Tsuji

2. Research Overview

Antibodies are highly flexible and diverse molecules capable of binding to various surfaces of the three-dimensional structure of target molecules. Because differences in binding site and binding orientation (binding mode) can either enhance or inhibit the function of a target molecule, antibodies have the potential to be applied to a wide range of diseases. However, because both antigens and antibodies undergo dynamic conformational changes, accurately predicting the relationship between binding mode and biological function—and designing antibodies that achieve both efficacy and safety—in clinical settings remains a major challenge.

The Antibody Design Project focuses on analyzing and designing the binding mode itself—where and how an antibody binds to its target—with the aim of creating next-generation antibody therapeutics that maximize therapeutic efficacy in patients. By integrating our proprietary Epitope Normalized Antibody Panel technology with AI-based structural modeling, we seek to shift antibody discovery from empirical screening to rational design. Our research primarily targets difficult-to-treat diseases such as cancer, immune disorders, and infectious diseases, while also expanding into areas where new therapeutic strategies are needed.

In addition, the project places strong emphasis on collaboration among academia, industry, and government, and actively pursues intellectual property strategies to ensure that research outcomes are translated effectively into real-world medical applications.

3. Research Background

Antibodies are a group of proteins known as immunoglobulins (Ig), produced in living organisms to recognize and eliminate non-self substances. Immunoglobulins are not a single molecule but a highly diverse group of proteins with different antigen-binding sites.

Unlike other drug modalities, because antibodies can recognize diverse three-dimensional structures of target molecules through multiple binding modes, and can therefore bind to many regions on the surface of a target protein. Among these, antibodies that selectively recognize specific structural features in vivo and exhibit sufficient affinity and specificity become functionally useful antibodies. Even when targeting the same molecule, differences in epitope location, binding angle, contact residues, and binding mode can result in markedly different biological functions.

Our research aims to harness the nearly limitless diversity inherent in antibodies for the development of next-generation antibody therapeutics. Each antibody generates different functional outcomes—such as agonistic or antagonistic activity or neutralization—depending on where and how it interacts with the target antigen. Antigen–antibody interactions are mediated by various intermolecular forces, including hydrogen bonds, hydrophobic interactions, and electrostatic attractions. Consequently, fundamental properties required for pharmaceuticals—such as specificity, affinity, and physicochemical stability—vary among antibodies.

Importantly, antibody specificity is determined not only by binding to the intended target but also by the balance with potential non-specific interactions with numerous molecules present in the biological environment. To identify therapeutic antibodies from the vast diversity of antibodies capable of exerting pharmacological effects in humans, our laboratory has established the following research themes.

4. Research Areas

In our project, we treat the binding mode, formed by the epitope (antigen binding site) and paratope (antibody binding site), as the fundamental design unit, integrating functional optimization with physicochemical property optimization.

Our laboratory particularly focuses on membrane proteins involved in refractory diseases, including GPCRs, TNFSF/TNFRSF family molecules, and immune checkpoint molecules, as major therapeutic targets. We have reported achievements such as the development of functional antibodies targeting TNFR family members and immune checkpoint molecules including PD-1, as well as the design of biparatopic antibodies.

(1) Generation and Functional Analysis of Antibodies Against Difficult Drug Targets

Multi-pass membrane proteins such as GPCRs are promising drug targets that regulate many physiological and pathological processes. However, antibody-based therapeutics targeting these receptors remain insufficiently explored due to challenges such as receptor conformational dynamics and limited extracellular epitopes.

Genome sequencing has revealed that a large number of GPCR proteins exist in the genome, many of which are orphan receptors whose ligands remain unknown. These factors have hindered both functional analysis and therapeutic antibody development.

To address this challenge, we are developing antibody generation and evaluation systems that consider membrane-associated higher-order structures and molecular complexes, thereby accelerating functional analysis and therapeutic development of these potential drug targets using antibodies.

(2) Antibody Engineering for Functional Enhancement and Clinical Translation

In addition to GPCRs, we focus on high-impact therapeutic targets such as molecules expressed on regulatory T cells (Treg) and B-cell-derived tumors, immune checkpoint molecules, and TNFSF/TNFRSF family members.

Through antibody engineering approaches—including ADCC-optimized antibodies, antibody-drug conjugates (ADC), bispecific antibodies, and biparatopic antibodies—we aim to design novel binding modes and mechanisms of action that are difficult to achieve with natural antibodies, thereby maximizing therapeutic efficacy and facilitating early clinical translation.

(3) AI-Driven Structural Modeling and Computational Design Principles

We apply AI-based structural modeling and computational analyses to predict antibody binding modes, physicochemical properties, and off-target binding profiles. These approaches enable the establishment of rational design principles for antibody engineering.

(4) Systematic Epitope Classification Using Immune Responses as a Drug Discovery Resource

We regard antibody responses induced in immunized animals as a valuable resource for drug discovery and aim to systematize epitope classification. Specifically, we integrate two types of similarity:　(1) similarity between the human antigen used for immunization and orthologs in other species; (2) similarity between the antigen and the host animal’s own ortholog (regions where immune responses are suppressed due to immune tolerance)

By considering these two factors, we classify regions where immune responses are induced or avoided, enabling the use of antibody repertoire formation to guide next-generation antibody discovery based on binding modes.

5. Our Unique Approach

Traditionally, antibody discovery has relied on empirical screening in which large numbers of antibodies are generated and evaluated for function. In contrast, our laboratory aims to shift toward a strategy in which functional maps of antigen surfaces are constructed to guide rational antibody design.

As a core technology, we have developed a proprietary platform called the Epitope Homogenized Antibody Panel, which systematically generates antibodies recognizing diverse epitopes across an antigen surface. This panel enables experimental visualization of antibody-accessible regions on the antigen and allows systematic identification of epitopes associated with specific functions, such as receptor activation, inhibition, or internalization.

This approach facilitates the transition from empirical antibody screening to rational antibody design based on binding modes.

●How many epitopes should be expected on a target molecule? — Epitope Normalized Antibody Panels, 　Experimental Medicine, 2018 doi.10.18958/5653-00001-0001553-00e

　Satoshi Nagata, Tomoko Ise, Haruhiko Kamada,

　Related material (PDF):documents/jikkenigaku.pdf PDFファイル（3942KB）

　※Reprinted with permission from the author (no modification or excerpting allowed).

7.Recent Publications

Urano E, Okamura T, Higuchi M, Furukawa SM, Ueda K, Nagata S, Kamada H, Yasutomi Y. Pathological characteristics of SARS-CoV-2 variants and immune responses induced in a COVID-19 macaque model. Commun Biol. 2026. doi:10.1038/s42003-026-09684-x
Akiba H, Ise T, Satoh R, Abe Y, Tsumoto K, Ohno H, Kamada H, Nagata S. Generation of antagonistic biparatopic anti-CD30 antibody from an agonistic antibody by precise epitope determination and utilization of structural characteristics of CD30 molecule. Antib Ther. 2025 Jan 14;8(1):56-67. doi:10.1093/abt/tbaf002.
Tsugawa Y, Furukawa K, Ise T, Takayama M, Ota T, Kuroda T, Shano S, Hashimoto T, Konishi H, Ishihara T, Sato M, Kamada H, Fukao K, Shishido T, Yoshikawa M, Takahashi T, Nagata S. Discovery of anti-SARS-CoV-2 S2 protein antibody CV804 with broad-spectrum reactivity with various beta coronaviruses and analysis of its pharmacological properties in vitro and in vivo. PLoS One. 2024 Dec 2;19(12):e0300297. doi:10.1371/journal.pone.0300297.
Asano R, Nakakido M, Pérez JF, Ise T, Caaveiro JMM, Nagata S, Tsumoto K. Crystal structures of human CD40 in complex with monoclonal antibodies dacetuzumab and bleselumab. Biochem Biophys Res Commun. 2024 Apr 18;714:149969. doi:10.1016/j.bbrc.2024.149969
Akiba H, Fujita J, Ise T, Nishiyama K, Miyata T, Kato T, Namba K, Ohno H, Kamada H, Nagata S, Tsumoto K. Development of a 1:1-binding biparatopic anti-TNFR2 antagonist by reducing signaling activity through epitope selection. Commun Biol. 2023;6:987. doi:10.1038/s42003-023-05326-8
Suzuki K, Tajima M, Tokumaru Y, Oshiro Y, Nagata S, Kamada H, Kihara M, Nakano K, Honjo T, Ohta A. Anti-PD-1 antibodies recognizing the membrane proximal region are PD-1 agonists that can downregulate inflammatory diseases. Sci Immunol. 2023 Jan 13;8(79):eadd4947. doi:10.1126/sciimmunol.add4947
Yamaguchi T, Hoshizaki M, Minato T, Nirasawa S, Asaka MN, Niiyama M, Imai M, Uda A, Chan JF, Takahashi S, An J, Saku A, Nukiwa R, Utsumi D, Yasuhara A, Poon VKM, Chan CSC, Fujino Y, Motoyama S, Nagata S, Penninger JM, Kamada H, Yuen KY, Kamitani W, Maeda K, Kawaoka Y, Yasutomi Y, Imai Y, Kuba K. ACE2-like carboxypeptidase B38-CAP protects from SARS-CoV-2-induced lung injury. Nat Commun. 2021;12(1):6791. doi:10.1038/s41467-021-27097-8
Urano E, Okamura T, Ono C, Ueno S, Nagata S, Kamada H, Higuchi M, Furukawa M, Kamitani W, Matsuura Y, Kawaoka Y, Yasutomi Y. COVID-19 cynomolgus macaque model reflecting human COVID-19 pathological conditions. Proc Natl Acad Sci U S A. 2021;118(43):e2104847118. doi:10.1073/pnas.2104847118
Asaka MN, Utsumi D, Kamada H, Nagata S, Nakachi Y, Yamaguchi T, Kawaoka Y, Kuba K, Yasutomi Y. Highly susceptible SARS-CoV-2 model in CAG promoter-driven hACE2-transgenic mice. JCI Insight. 2021;6(19):e152529. doi:10.1172/jci.insight.152529
Akiba H, Ise T, Nagata S, Kamada H, Ohno H, Tsumoto K. Production of IgG1-based bispecific antibody without extra cysteine residue via intein-mediated protein trans-splicing. Sci Rep. 2021;11(1):19411. doi:10.1038/s41598-021-98855-3
Akiba H, Satoh R, Nagata S, Tsumoto K. Effect of allotypic variation of human IgG1 on the thermal stability of disulfide-linked knobs-into-holes mutants of the Fc for stable bispecific antibody design. Antibody Therapeutics. 2019;2(3):65-69. doi:10.1093/abt/tbz008
Ambegaonkar AA, Nagata S, Pierce SK, Sohn H. The differentiation in vitro of human tonsil B cells with the phenotypic and functional characteristics of T-bet+ atypical memory B cells in malaria. Front Immunol. 2019;10:852. doi:10.3389/fimmu.2019.00852
Shancer Z, Liu XF, Nagata S, Zhou Q, Bera TK, Pastan I. Anti-BCMA immunotoxins produce durable complete remissions in two mouse myeloma models. Proc Natl Acad Sci U S A. 2019;116(10):4592-4598. doi:10.1073/pnas.1821733116