Biology subjects

Errington, W. J.

Publications and source records attributed to Errington, W. J..

2 recordsLinked to original sources

bioRxiv2022

Antibody-lectin chimeras for glyco-immune checkpoint blockade

Despite the curative potential of checkpoint blockade immunotherapy, most patients remain unresponsive to existing treatments. Glyco-immune checkpoints - interactions of cell-surface glycans with lectin, or glycan-binding, immunoreceptors - have emerged as prominent mechanisms of immune evasion and therapeutic resistance in cancer. Here, we describe antibody-lectin chimeras (AbLecs), a modular platform for glyco-immune checkpoint blockade. AbLecs are bispecific antibody-like molecules comprising a cell-targeting antibody domain and a lectin "decoy receptor" domain that directly binds glycans and blocks their ability to engage inhibitory lectin receptors. AbLecs potentiate anticancer immune responses including phagocytosis and cytotoxicity, outperforming most existing therapies and combinations tested. By targeting a distinct axis of immunological regulation, AbLecs synergize with blockade of established immune checkpoints. AbLecs can be readily designed to target numerous tumor and immune cell subsets as well as glyco-immune checkpoints, and therefore represent a new modality for cancer immunotherapy.

biochemistry↗

bioRxiv2021

MVsim: a toolset for quantifying and designing multivalent interactions

Arising through multiple binding elements, multivalency can specify the avidity, duration, cooperativity, and selectivity of biomolecular interactions, but quantitative prediction and design of these properties has remained challenging. Here we present MVsim, an application suite built around a configurational network model of multivalency to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena through a simple graphical user interface. To demonstrate the utility and versatility of MVsim, we first show that both monospecific and multispecific multivalent ligand-receptor interactions, with their noncanonical binding kinetics, can be accurately simulated. We then quantitatively predict the ultrasensitivity and performance of multivalent-encoded protein logic gates, evaluate the inherent programmability of multispecificity for selective receptor targeting, and extract rate constants of conformational switching for the SARS-CoV-2 spike protein and model its binding to ACE2 as well as multivalent inhibitors of this interaction. MVsim is freely available at https://sarkarlab.github.io/MVsim/.

systems biology↗