Quantitative high-throughput methods for antibody fragment optimization and discovery

用于抗体片段优化和发现的定量高通量方法

• 批准号: 10454415
• 负责人: Curtis Layton
• 金额: $ 85.53万
• 依托单位: PROTILLION BIOSCIENCES, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10454415
• 关键词: 2019-nCoV; Address; Affinity; Amino Acid Sequence; Amino Acids; Antibodies; Antibody Repertoire; Automation; Automobile Driving; Binding; Binding Proteins; Biochemical; Biological Assay; Biophysics; COVID-19; Cells; ChIP-seq; Clinical; Color; DNA biosynthesis; DNA sequencing; Data; Data Set; Detection; Development; Disease; Ecosystem; Evaluation; Exhibits; Fluorescence; Generations; Genes; Genetic Transcription; Human; Human Resources; Hybridomas; Image; Immobilization; Immunoglobulin Fragments; In Situ; In Vitro; Individual; Industry; Infrastructure; Intellectual Property; Laboratory Procedures; Lead; Length; Libraries; Ligands; Liquid substance; Malignant Neoplasms; Maps; Measurement; Measures; Methods; Molecular; Monoclonal Antibodies; Mutation; Mutation Analysis; Peptides; Phage Display; Pharmaceutical Preparations; Phase; Process; Property; Protein Array; Protein Binding Domain; Protein Engineering; Protein Microchips; Proteins; Protocols documentation; Randomized; Reagent; Reporting; Runaway; SARS-CoV-2 inhibitor; Specificity; Technology; Therapeutic; Therapeutic antibodies; Time; Transgenic Animals; Translations; Variant; Viral; Work; Yeasts; antigen binding; base; cancer immunotherapy; cellular imaging; clinically relevant; combinatorial; deep learning; deep learning model; design; fighting; hands on research; high throughput analysis; improved; instrument; instrumentation; nanobodies; novel; novel therapeutics; programmed cell death ligand 1; prospective; protein expression; protein function; receptor binding; scaffold; side effect; single cell analysis; success; therapeutic development

Abstract Monoclonal antibodies and antibody fragments are an important class of therapeutics comprising a $150B industry. However, methods for discovering and optimizing antibodies to have desired affinity are generally laborious laboratory procedures that require months of hands-on research performed by highly skilled personnel (e.g. phage display, hybridoma, single cell). Additionally, the selection of leads to move forward in the therapeutic development pipeline often must be made with limited information that does not necessarily correspond to quantitative binding affinity. To address these challenges, Protillion has commercialized Prot- MaP, a platform for measuring quantitative protein binding across large libraries of 105 to 109 variants on automated instrumentation, with a time-to-result of approximately 2 days. We achieve this by generating immobilized proteins directly on Illumina DNA sequencing flow cells through a process of in-situ transcription and translation. This platform allows for direct, quantitative measurements of fluorescent antigen binding to entire protein libraries at unprecedented scale—a scale that is finally a match for the sparseness of protein function in amino acid mutation space. In our Phase I period, we adapted Prot-MaP to display VHHs (nanobodies) capable of binding the SARS-CoV-2 spike (S1) receptor binding domain (RBD) protein. Our multi-step optimization first comprehensively identified “beneficial” mutations, which were then combined into a second combinatorial library. This strategy identified tens of thousands of protein variants with affinity superior to wild type, with the best exhibiting the highest reported binding affinity for a VHH to this target, a 100-fold improvement from the starting point. We also developed a strategy to humanize this nanobody, producing a near-fully-human sequence that maintained high affinity. In Phase II, we will first improve automation and commercial scalability of our instrumentation, and develop deep learning models for library design and selection of therapeutic leads. We will next optimize other SARS-CoV-2 S1 RBD-binding nanobodies, as well as nanobodies capable of binding PD-L1, a target relevant to cancer immunotherapy. We will develop a universally applicable pipeline for identifying high-affinity, humanized, clinically-relevant VHH reagents. We will also extend our display capabilities to larger, scFv domains, and carry out scFv affinity optimization against two separate target ligands, including SARS-CoV-2 S1 RBD. Finally, we will adapt our methods to display up to 109 distinct protein variants on a NovaSeq sequencing chip, a scale sufficient to identify binders de novo from naïve humanized VHH libraries. The activities outlined in this proposal will enable display multiple types of antibody fragments, optimize affinity and humanize their sequences, and clearly define the landscape of functional protein sequences. The capability of de novo discovery of new binders from untargeted libraries will make the Protillion platform a vertically integrated “one stop shop” allowing both identification of “hits” from untargeted libraries, as well as detailed mutational analysis and optimization of these variants.

抽象的 单克隆抗体和抗体片段是包括$ 150B的一类重要类别 霍弗（Howver）。 费力的实验性程序需要数月的动手研究 人员（例如噬菌体显示，杂交瘤，单细胞）。 通常必须使用有限的信息来制作治疗开发管道 与定量结合亲和力相关。 MAP，一个用于测量105至109个变体的大型文库中定量蛋白结合的平台 自动化仪器，大约有2天的时间分子。 固定蛋白直接在Illumina DNA测序流中通过原子转录过程 和翻译。 整个蛋白质文库以未经编写的量表 - 最终与蛋白质的少量匹配的量表 在我们的第一阶段的氨基酸突变空间 （纳米化）能够结合SARS-COV-2尖峰（S1）受体结合域（RBD）蛋白 多步优化首先全面鉴定出“有益”的突变，然后合并为 第二个组合库。 对野生型，具有对VHH与该目标的最佳施加的结合结合结合，为100倍 从起点进行改进。 维持高亲和力的近乎人类的序列。 我们的乐器的商业可扩展性，并为图书馆设计开发深度学习模型 选择治疗铅。 作为能够结合PD-L1的纳米剂，与癌症免疫疗法有关的靶标。 普遍适用于识别高亲和力，人性化的临床vHH试剂 还将我们的显示功能扩展到较大 单独的目标配体，包括SARS-COV-2 S1 RBD。 Novaseq测序芯片上的独特蛋白质变体，这是一个足以识别从头开始的量表 天真的人源化VHH库。 抗体片段，优化亲和力并使其序列人性化，并清楚地定义了 功能性蛋白质序列。 使Protillion平台成为垂直集成的“一站式商店”，允许从“命中”中识别“命中” 未定位的库，以及这些变体的详细杂种分析和优化。