Biology subjects

Sarkar, C. A.

Publications and source records attributed to Sarkar, C. A..

3 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↗

bioRxiv2021

Model-guided engineering of DNA sequences with predictable site-specific recombination rates

Site-specific recombination (SSR) is an important tool in genome editing and gene circuit design. However, its applications are limited by the inability to simply and predictably tune SSR reaction rates across orders of magnitude. Facile rate manipulation can in principle be achieved by modifying the nucleotide sequence of the DNA substrate of the recombinase, but the design principles for rationally doing so have not been elucidated. To enable predictable tuning of SSR reaction kinetics via DNA sequence, we developed an integrated experimental and computational method to parse individual nucleotide contributions to the overall reaction rate, which we used to analyze and engineer the DNA attachment sequence attP for the inversion reaction mediated by the serine recombinase Bxb1. A quantitative PCR method was developed to measure the Bxb1 reaction rate in vitro. Then, attP sequence libraries were designed, selected, and sequenced to inform a machine-learning model, which revealed that the Bxb1 reaction rate can be accurately represented assuming independent contributions of nucleotides at key positions. Next, we used the model to predict the performance of DNA site variants in reaction rate assays both in vitro and in Escherichia coli, with flipping rates ranging from 0.01- to 10-fold that of the wild-type attP sequence. Finally, we demonstrate that attP variants with predictable DNA recombination rates can be used in concert to achieve kinetic control in gene circuit design by coordinating the coexpression of two proteins in both their relative proportion and their total amount. Our high-throughput, data-driven method for rationally tuning SSR reaction rates through DNA sequence modification enhances our understanding of recombinase function and expands the synthetic biology toolbox. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

synthetic biology↗