Biology subjects

Weitzner, B. D.

Publications and source records attributed to Weitzner, B. D..

5 recordsLinked to original sources

bioRxiv2026

A Dynamically Regulated Designed IL-2 for Tumor-localized Signaling

Cytokines mediate cell-cell communication to coordinate immune responses and hold clinical promise as immunotherapies. While natural cytokines are exquisitely regulated by immune cells, engineered cytokines have not yet matched this sophisticated regulation, limiting clinical efficacy and safety. IL-2 is an important cytokine involved in antitumor response, but its production is disrupted in the immune-suppressive tumor microenvironment. Here we designed a regulated IL-2 module, OUTSMART designed IL-2 (dIL-2), that functions robustly in solid tumors and reduces systemic activity that could trigger toxicity: we computationally redesigned IL-2 to have a novel topology that increases stability, preserves native IL-2R{beta}{gamma} interfaces, ablates IL-2R binding, and delivers IL-2 signaling to CD8+ immune-effector cells. This designed cytokine is genetically regulated by a T cell activation-responsive promoter, allowing dynamic production from chimeric antigen receptor (CAR) T cells. Like wild type IL-2, OUTSMART dIL-2 drives T cell proliferation and enhances effector function. Unlike wild type IL-2, it preferentially stimulates CD8+ T cells and Natural Killer (NK) cells, avoids T regulatory cells, and stimulates CAR-T proliferation while preserving stemness, achieving durable tumor elimination in two solid tumor animal models. These design principles can be applied to create other dynamically-regulated cytokine systems that address mechanisms of complex disease.

synthetic biology↗

bioRxiv2026

A Rationally Designed Transgene Drives CAR T Functional Persistence and Durable Regression of Solid Tumors

The eradication of solid tumors by chimeric antigen receptor (CAR) T cells requires dynamic therapies capable of outlasting an immune suppressive tumor microenvironment (TME). However, biological barriers--including rapid exhaustion, poor expansion, and loss of stem-like memory--quickly neutralize these therapies. Because single-technology interventions often introduce unacceptable tradeoffs between efficacy and safety, durable remission demands a paradigm where multiple engineered solutions work in concert. To holistically address these mechanisms, we rationally designed a single-vector transgene that intrinsically drives CAR T functional persistence. The platform integrates four synergistic technologies: a high-avidity mesothelin (MSLN)-targeting CAR optimized to resist shed decoy antigens, a T-cell activation-responsive promoter (OUTLAST OP1) resisting exhaustion, a CD8-targeted designed IL-2 cytokine (OUTSMART dIL-2) driving intratumoral CAR-T expansion, and an EGFRopt safety switch. In lung and ovarian cancer models, this rational integration was required to drive antigen-dependent T cell expansion and eradicate established tumors at extremely low CAR T doses. Furthermore, engineered cells established a self-renewing pool of stem-like memory T cells capable of rejecting tumor rechallenge months later. Ultimately, this work demonstrates that intrinsic T cell dysfunction and extrinsic tumor-derived barriers can be simultaneously overcome by integrating synergistic technologies.

synthetic biology↗

bioRxiv2026

Protein design to broadly reprogram engineered T cell function

The efficacy of engineered T cell therapies in solid tumors remains limited by T cell dysfunction, driven by complex processes that cannot be easily manipulated via genetic knockouts or overexpression of individual genes. Protein design can create new biological functions that can rewire these consequential cell fate decisions. Here, we introduce OUTLAST Regulators, designed proteins that reprogram critical T cell signaling pathways to enhance functional persistence. These proteins are capable of regulating diverse groups of proteins such as the NR4A family of pro-exhaustion transcription factors, E3 ligases Cbl-b and c-Cbl, and SOCS family proteins. Our designs markedly improve CAR-T and TCR-T performance in vitro and in vivo in stringent solid tumor preclinical models. OUTLAST Regulators are implemented as compact genetic modules compatible with standard viral vectors and cell therapy manufacturing processes, creating a powerful platform for programming new functions into enhanced cell and gene therapies.

synthetic biology↗

bioRxiv2019

Designing Peptides on a Quantum Computer

Although a wide variety of quantum computers are currently being developed, actual computational results have been largely restricted to contrived, artificial tasks. Finding ways to apply quantum computers to useful, real-world computational tasks remains an active research area. Here we describe our mapping of the protein design problem to the D-Wave quantum annealer. We present a system whereby Rosetta, a state-of-the-art protein design software suite, interfaces with the D-Wave quantum processing unit to find amino acid side chain identities and conformations to stabilize a fixed protein backbone. Our approach, which we call the QPacker, uses a large side-chain rotamer library and the full Rosetta energy function, and in no way reduces the design task to a simpler format. We demonstrate that quantum annealer-based design can be applied to complex real-world design tasks, producing designed molecules comparable to those produced by widely adopted classical design approaches. We also show through large-scale classical folding simulations that the results produced on the quantum annealer can inform wet-lab experiments. For design tasks that scale exponentially on classical computers, the QPacker achieves nearly constant runtime performance over the range of problem sizes that could be tested. We anticipate better than classical performance scaling as quantum computers mature.

bioengineering↗

bioRxiv2017

Rosetta Antibody Design (RAbD): A General Framework for Computational Antibody Design

A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J. Mol. Biol., 406:228-256, 2011). It then performs sequence design according to amino acid sequence profiles of each cluster, and samples CDR backbones using a flexible-backbone design protocol incorporating cluster-based CDR constraints. Starting from an existing experimental or computationally modeled antigen-antibody structure, RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody-antigen complexes, using two design strategies - optimizing total Rosetta energy and optimizing interface energy alone. We utilized two novel metrics for measuring success in computational protein design. The design risk ratio (DRR) is equal to the frequency of recovery of native CDR lengths and clusters divided by the frequency of sampling of those features during the Monte Carlo design procedure. Ratios greater than 1.0 indicate that the design process is picking out the native more frequently than expected from their sampled rate. We achieved DRRs for the non-H3 CDRs of between 2.4 and 4.0. The antigen risk ratio (ARR) is the ratio of frequencies of the native amino acid types, CDR lengths, and clusters in the output decoys for simulations performed in the presence and absence of the antigen. For CDRs, we achieved cluster ARRs as high as 2.5 for L1 and 1.5 for H2. For sequence design simulations without CDR grafting, the overall recovery for the native amino acid types for residues that contact the antigen in the native structures was 72% in simulations performed in the presence of the antigen and 48% in simulations performed without the antigen, for an ARR of 1.5. For the non-contacting residues, the ARR was 1.08. This shows that the sequence profiles are able to maintain the amino acid types of these conserved, buried sites, while recovery of the exposed, contacting residues requires the presence of the antigen-antibody interface. We tested RAbD experimentally on both a lambda and kappa antibody-antigen complex, successfully improving their affinities 10 to 50 fold by replacing individual CDRs of the native antibody with new CDR lengths and clusters.\n\nAuthor SummaryAntibodies are proteins produced by the immune system to attack infections and cancer and are also used as drugs to treat cancer and autoimmune diseases. The mechanism that has evolved to produce them is able to make 10s of millions of different antibodies, each with a different surface used to bind the foreign or mutated molecule. We have developed a method to design antibodies computationally, based on the 1000s of experimentally determined three-dimensional structures of antibodies available. The method works by treating pieces of these structures as a collection of parts that can be combined in new ways to make better antibodies. Our method has been implemented in the protein modeling program Rosetta, and is called RosettaAntibodyDesign (RAbD). We tested RAbD both computationally and experimentally. The experimental test shows that we can improve existing antibodies by 10 to 50 fold, paving the way for design of entirely new antibodies in the future.

bioengineering↗