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Takulapalli, B.

Publications and source records attributed to Takulapalli, B..

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An approach for single-amino-acid resolution epitope mapping by kinetic affinity screening of antibody drugs against biosensor on-chip library of deep mutationally-scanned target variants

Epitope mapping is central to rational antibody drug design, affinity optimization and the anticipation of therapeutic resistance mechanisms. Here, we demonstrate the use of Sensor Integrated Proteome on Chip (SPOC) technology for single amino acid resolution epitope mapping. By generating high throughput (HTP) binding kinetics data, we identify important residues within the target epitope whose mutations alter drug-target interactions. The SPOC platform integrates simultaneous HTP cell-free production of folded proteins in nanowells from immobilized plasmid DNAs or linear expression cassettes and capture onto biosensor chips for subsequent label-free binding kinetic analysis using surface plasmon resonance (SPR). The model system comprised the extracellular domain (ECD) of CD20, a membrane-spanning 4-domain family protein, screened against its FDA-approved therapeutic monoclonal antibodies (thAbs) - rituximab and ocrelizumab. Using our proprietary POC protein nanofactory system, a partial deep mutationally scanned (DMS) CD20 ECD mutant library of 79 variants was produced on SPOC biosensor chips via rational single amino acid substitutions of the epitope and surrounding residues with alanine, aspartic acid, lysine, and serine, collectively representing four broad classes of amino acid side chain chemistries: nonpolar, acidic, basic, and polar neutral. The SPOC protein biosensor chip was then screened with both thAbs using SPOC SPR to generate kinetic affinity data, evaluate mutations that led to affinity loss or gain, and ultimately identify critical epitope residues that interface with the antibodies. Most mutations within the rituximab and ocrelizumab epitopes - EPANPSEK and YNCEPANPSEKNSPST, respectively - resulted in complete loss of binding or >25% increase in apparent KD. Notably, N171, P172, and S173 mutations, irrespective of side chain substitution, resulted in complete loss of rituximab binding while at least three diverse side chain substitutions at E168, P169, N171, P172, S173, E174, K175, and T180, led to complete loss of binding for ocrelizumab. These outcomes identify the listed residues as the most critical contact points for their respective antibodies. Interestingly, we also found that functional side-chain substitutions at some residues flanking the epitope increased affinity. This indicates that these non-epitope residues contribute to antibody contact, and that polarity at these sites is a tractable lever for affinity modulation by targeting the corresponding contact residues on the antibody CDRs. The proposed SPOC approach of screening drug candidates against on-chip library of mutationally-scanned therapeutic targets is relevant in the early phase of drug development to resolve epitopes at the residue-level to support more informed down-selection of candidates. It facilitates cost-effective improvement of thAbs, enhancing therapeutic efficacy across a wide array of therapeutic targets, including rare variants that might otherwise lead to therapeutic resistance.

immunology↗

An approach to produce thousands of single-chain antibody variants on a SPR biosensor chip for measuring target binding kinetics and for deep characterization of antibody paratopes

Drug discovery continues to face a staggering 90% failure rate, with many setbacks occurring during late-stage clinical trials. To address this challenge, there is an increasing focus on developing and evaluating new technologies to enhance the "design" and "test" phases of antibody-based drugs (e.g., monoclonal antibodies, bispecifics, CAR-T therapies, ADCs) and biologics during early preclinical development, with the goal of identifying lead molecules with a higher likelihood of clinical success. Artificial intelligence (AI) is becoming an indispensable tool in this domain, both for improving molecules identified through traditional approaches and for the de novo design of novel therapeutics. However, critical bottlenecks persist in the "build" and "test" phases of AI-designed antibodies and protein binders, impeding early preclinical evaluation. While AI models can rapidly generate thousands to millions of putative drug designs, technological and cost limitations mean that only a few dozen candidates are typically produced and tested. Drug developers often face a tradeoff between ultra-high-throughput wet lab methods that provide binary yes/no binding data and biophysical methods that offer detailed characterization of a limited number of drug-target pairs. To address these bottlenecks, we previously reported the development of the Sensor-integrated Proteome On Chip (SPOC(R)) platform, which enables the production and capture-purification of 1,000 - 2,400 folded proteins directly onto a surface plasmon resonance (SPR) biosensor chip for measuring kinetic binding rates with picomolar affinity resolution. In this study, we extend the SPOC technology to the expression of single-chain antibodies (sc-antibodies), specifically scFv and VHH, and dual-chain Fab constructs. We demonstrate that these proteins are capture-purified at high levels on SPR biosensors and retain functionality as shown by the binding specificity to their respective target antigens, with affinities comparable to those reported in the literature. SPOC outputs comprehensive kinetic data including quantitative binding (Rmax), on-rate (ka), off-rate (kd), affinity (KD), and half-life (t1/2), for each of thousands of on-chip sc-antibodies. Additionally, we present a case study showcasing single amino acid mutational scan of the complementarity-determining regions (CDRs) of a HER2 VHH (nanobody) paratope. Using 92 unique mutated variants from four different amino acid substitutions, we pinpoint critical residues within the paratope that could further enhance binding affinity. This study serves as a demonstration of a novel high-throughput approach for biophysical screening of hundreds to thousands of single chain antibody sequences in a single assay, generating high affinity resolution kinetic data to support antibody discovery and AI-enabled pipelines.

immunology↗