CAR and Antibodies Structure-Activity Relationships and molecular architecture

Division Of Basic Sciences - Nci

Investigators

Linked publications & trials

Abstract

An important focus of this project is to support CARs (Chimeric Antigen Receptors) and antibodies' precise bottom-up engineering by acquiring the detailed knowledge of the interplay between their constitutive molecular elements (Antibody binding moiety, Hinge, Transmembrane, and stimulatory domains) and the characterization of their functional role. State-of-the-art CARs design strategies rely on the buildup of chimeras from these modular domains used as components. This is done through a combinatorial process using an expensive trial and error approach to select the most promising candidates. My research has focused in the last few years on the study of self-association determinants of molecular systems, especially proteins, as revealed by their structural symmetries at several levels of molecular organization: molecular assemblies, protein chains, protein domains, and protein supersecondary structures (protodomains) [Youkharibache 2019,2021]. While symmetry is high and apparent in large molecular assemblies, it is difficult to detect at the level of protein domains or receptor-ligand interactions. For example, while antibodies' heavy and light chain symmetries are well known, the individual Immunoglobulin domains consist themselves of intrinsically pseudo-symmetric protodomains [Youkharibache 2021], a property largely ignored that can open new routes to antibody engineering, especially nanobodies. At the same time, many of the cell surface protein receptors, from T-Cell to their target cells (TCRs, CD4, CD8, CD28, CTLA4, PD1, PDL1, etc.) are composed of Ig domains interacting through oligomeric pseudo-symmetric arrangements. We have developed methods for their structural analysis to inform and possibly design new Ig-based immunoreceptors. We use experimental and computational tools to explore these questions. Our modeling tools' application helped us characterize anti-CD19 and anti-BCMA CARs using variable CD8 and CD28 hinge components based on flexibility analysis [Brudno et al. 2020], suggesting that CAR toxicity can be related to its flexibility. Our exploration of CAR extracellular domains by X-ray crystallography techniques resulted in the first report on the formation of a spontaneous rearrangement of a CAR scFv mediated by quasi-symmetry, resulting in an unexpected VL-VL arrangement [PDBid: 7JO8 Cheung et al. 2020]. The use of NMR confirmed bioinformatics and structure prediction analyses on the intrinsic disorder character of the CD8 HIinge (Chen et al., 2022). These early promising results supported developing a pipeline for the rapid modeling of CARs at different scales of complexity and the exploration of their properties through computational techniques. These techniques are based on the application of a combination of data science methods, mining of big-data repositories, new approaches to in-silico structure analysis, and machine learning tools [Wang et al. 2020, Wang et al. 2022; Youkharibache et al. 2019, Youkharibache et al. 2020, Youkharibache et al. 2021]. The Immunoglobulin domain swapping observed [Cheung et al. 2020] gave support to our growing interest in exploring symmetry-related rearrangements as a data/knowledge organizing criteria and its application to antibody design, both stand-alone and as CAR antigen binding moieties. We expect to expand our experimental characterization of these domains by performing stability measurements to complement the available data. We plan to shift our experimental exploration of CARs by emphasizing ultrastructure analysis and CAR fragment analysis. Ultrastructure analysis (how CARs are organized in the membrane) by thin-section TEM studies may lead to Cryo-ET studies in favorable cases. The use of diffraction techniques to analyze CAR fragments may expedite the uncovering of some of the missing structures. The two approaches are complementary and will provide critical missing information to improve our understanding of these complex systems.