Biology subjects

McCoy, K. M.

Publications and source records attributed to McCoy, K. M..

4 recordsLinked to original sources

bioRxiv2024

Combining computational modeling and experimental library screening to affinity-mature VEEV-neutralizing antibody F5

Engineered monoclonal antibodies (mAbs) have proven to be highly effective therapeutics in recent viral outbreaks due to their specificity and ability to provide immediate protection, regardless of immune status. However, despite technical advancements in the field, an ability to rapidly adapt or increase antibody affinity and by extension, therapeutic efficacy, has yet to be fully realized. We endeavored to stand-up such a pipeline using molecular modeling combined with experimental library screening to increase the affinity of a given antibody, F5, to recombinant E1E2 antigen from Venezuelan Equine Encephalitis Virus (VEEV) subtype IAB (TC-83). F5 is a monoclonal antibody with potent neutralizing activity against VEEV that was isolated from human bone marrow donors. F5 is known to bind to spikes on the surface of VEEV made up of a trimer of heterodimers of the glycoproteins E1 and E2. In this work we modeled the interaction of F5 with the E1E2 trimer of VEEV (TC-83) and generated predictions for mutations to improve binding using a Rosetta-based approach and dTERMen, an informatics approach. Modeling the structure of the complex was complicated by the fact that a high-resolution structure of F5 is not available and the H3 loop of F5 exceeds the length for which current modeling approaches can determine a unique structure. To overcome these challenges nine F5 structures with varying H3 loop conformations were generated using RosettaAntibody, PIGS (Prediction of ImmunoGlobulin Structure), and SWISS-Model and these base antibody structures were evaluated in docking trials to recombinant VEEV E1E2 based on relative binding affinity for several subtypes. The structure that gave the best agreement with the experimental trend in relative binding affinity was used for mutation analysis. A subset of the predicted mutations from both methods were incorporated into a phage display library of scFvs (single-chain variable fragments) and screened for binding affinity to the recombinant E1E2 antigen. Results from this screen were used to identify favorable mutations which were then incorporated into twelve human-IgG1 variants. All twelve variants showed increased binding relative to the parental F5 human-IgG1. The best case showed > 60x increased binding to recombinant E1E2 relative to the parental antibody, notably showing a drastic improvement of the Kd or "off rate" compared to the parental F5 IgG. These results demonstrate the ability of our methods to rapidly increase affinity and could be leveraged for increasing Ab binding breadth to additional viral variants.

microbiology↗

bioRxiv2024

A Comparison of Antibody-Antigen Complex Sequence-to-Structure Prediction Methods and their Systematic Biases

The ability to accurately predict antibody-antigen complex structures from their sequences could greatly advance our understanding of the immune system and would aid in the development of novel antibody therapeutics. There have been considerable recent advancements in predicting protein-protein interactions (PPIs) fueled by progress in machine learning (ML). To understand the current state of the field, we compare six representative methods for predicting antibody-antigen complexes from sequence, including two deep learning approaches trained to predict PPIs in general (AlphaFold-Multimer, RoseTTAFold), two composite methods that initially predict antibody and antigen structures separately and dock them (using antibody-mode ClusPro), local refinement in Rosetta (SnugDock) of globally docked poses from ClusPro, and a pipeline combining homology modeling with rigid-body docking informed by ML-based epitope and paratope prediction (AbAdapt). We find that AlphaFold-Multimer outperformed other methods, although the absolute performance leaves considerable room for improvement. AlphaFold-Multimer models of lower-quality display significant structural biases at the level of tertiary motifs (TERMs) towards having fewer structural matches in non-antibody containing structures from the Protein Data Bank (PDB). Specifically, better models exhibit more common PDB-like TERMs at the antibody-antigen interface than worse ones. Importantly, the clear relationship between performance and the commonness of interfacial TERMs suggests that scarcity of interfacial geometry data in the structural database may currently limit application of machine learning to the prediction of antibody-antigen interactions.

bioinformatics↗

bioRxiv2022

GTP-bound E. coli FtsZ filaments are composed of Tense monomers: A DNP NMR study using interface detection.

FtsZ filaments are the major structural component of the bacterial Z-ring and are drivers of bacterial division. While crystal structures for FtsZ from some gram positive bacteria in the presence of GTP-analog like compounds suggest the possibility of a high energy "Tense" conformation, to date it remains an important question to elucidate whether this Tense form is the dominant form in filaments. Using dynamic nuclear polarization (DNP) solid-state NMR and differential isotopic labelling, we directly detect residues located at the inter-monomer interface of GTP-bound WT Escherichia coli FtsZ filaments. We combine chemical shift prediction, homology modelling, and heteronuclear dipolar recoupling techniques to characterize the E. coli FtsZ filament interface and demonstrate that the monomers in active filaments assume a Tense conformation.

microbiology↗

bioRxiv2019

Stability of Nitroxide Biradical TOTAPOL in Biological Samples

We characterize chemical reduction of a nitroxide biradical, TOTAPOL, used in dynamic nuclear polarization (DNP) experiments, specifically probing the stability in whole-cell pellets and lysates, and present a few strategies to stabilize the biradicals for DNP studies. DNP solid-state NMR experiments use paramagnetic species such as nitroxide biradicals to dramatically increase NMR signals. Although there is considerable excitement about using nitroxide-based DNP for detecting the NMR spectra of proteins in whole cells, nitroxide radicals are reduced in minutes in bacterial cell pellets, which we confirm and quantify here. We show that addition of the covalent cysteine blocker N-ethylmaleimide to whole cells significantly slows the rate of reduction, suggesting that cysteine thiol radicals are important to in vivo radical reduction. The use of cell lysates rather than whole cells also slows TOTAPOL reduction, which suggests a possible role for the periplasm and oxidative phosphorylation metabolites in radical degradation. Reduced TOTAPOL in lysates can also be efficiently reoxidized with potassium ferricyanide. These results point to a practical and robust set of strategies for DNP of cellular preparations.

biophysics↗