Biology subjects

Birnbaum, F.

Publications and source records attributed to Birnbaum, F..

7 recordsLinked to original sources

bioRxiv2026

pH-sensitive binder design with Proton-PottsMPNN

Physiological compartments span a wide pH range, from blood plasma near pH 7.4 through the mildly acidic tumor microenvironment to the acidified endosome and lysosome, and binders whose affinity responds to these differences underpin recycling antibodies, catalytic extracellular degraders and tumor-conditional therapeutics. Such binders are still obtained mainly by combinatorial histidine scanning and display selection, which is laborious and yields few transferable design rules. Recent computational approaches have enabled the design of pH-sensitive binders that engage at physiological pH and release under acidic conditions, by introducing histidines at key positions so that protonation generates electrostatic repulsion, evaluated through physics-based calculations. However, because the design model has no explicit representation of protonation state, it cannot shape the residues around a titratable site to favor one state over the other, leaving pH sensitivity to be screened for rather than specified. Here we present Proton-PottsMPNN, a sequence-design model that explicitly represents the protonated and deprotonated states of histidine, aspartate and glutamate as distinct sequence tokens. Because protonation state is specified rather than inferred, the model redesigns the microenvironment around a titratable residue so that the chosen protonation state is energetically favored over its alternative. Using Proton-PottsMPNN we designed a library of 8,407 de novo PD-L1 candidate binders in which sequence-structure compatibility and protonation state preference were designed jointly under a single energy function, with no structure-prediction filtering applied. The full library was synthesized and displayed on yeast, then screened against PD-L1 across a series of pH values by fluorescence- and magnetic-activated cell sorting, recovering 237 and 288 unique pH-dependent designs respectively. Transition pH values spanned 4.0 to 5.8, and switches were centered on protonated aspartate and glutamate as well as histidine. Recovered designs showed a stronger model preference for their designed protonation state than designs from the same backbone that were not recovered, and this preference was strongest in the designs that required the most acidic conditions to bind. Proton-PottsMPNN therefore designs binders that engage PD-L1 under acidic conditions fully de novo, directly from a specified protonation state.

biophysics↗

bioRxiv2026

Seed-Guided De Novo Design Expands the Structural Diversity of Antitoxin Protein Binders

De novo design of protein binders targeting extended, multi-site interaction surfaces remains difficult for current generative methods, which often produce limited structural diversity and predominantly helical topologies. Here, we advance diffusion-based binder design by guiding protein backbone generation through "seeds," which are PDB-derived fragments selected for geometric complementarity to the target surface. To test this approach, we computationally generated seed-guided binders of the bacterial toxin RelE. RelB, the native antitoxin of RelE, engages two distinct interfaces with high surface complementarity, making it an appropriate test case. Seed-guided RFdiffusion produced backbones with substantially higher structural diversity and more target contacts than RFdiffusion alone. Experimental screening of 1,402 designs in a high-throughput bacterial survival assay identified multiple functional binders, including variants with nanomolar to low-micromolar affinity and one design with RelE neutralization comparable to RelBpep. Computational structure prediction and mutational analyses support that the designed interfaces rely on seed-derived contacts and adopt binding modes distinct from RelB. Molecular dynamics simulations and hydrogen-deuterium exchange experiments further suggest that one high-affinity design undergoes a conformational change upon binding. Notably, successful designs exhibited reduced cross-reactivity to RelE orthologs compared with RelBpep, suggesting that the extensive interfaces generated through seed-guided design can enable enhanced selectivity. These results establish motif scaffolding of surface-complementing seeds as an effective strategy for overcoming current limitations of de novo generative models, enabling the design of proteins that can engage challenging interface sites.

bioengineering↗

bioRxiv2026

Multiomic screening platform uncovers the impact of histone mutations on chromatin and cell fate

Somatic missense mutations in histone genes, often referred to as oncohistones, have been identified in diverse types of human cancers. The functional and mechanistic impact of most oncohistones remains unknown. To address this gap, we developed CHANCLA, a modular platform for high-throughput functional screening of oncohistones using multiomic phenotypic readouts. We used CHANCLA to systematically measure the impact of 303 human oncohistones on cellular proliferation, differentiation, histone-specific post-translational modifications, and chromatin accessibility. Integrative multiomic analyses revealed discrete oncohistone molecular classes that promote proliferation, block lineage-specific differentiation, and physically remodel the chromatin landscape by altering specific histone modifications and reducing nucleosome stability. Structural mapping and computational modeling studies uncovered that functionally convergent mutations are clustered at key nucleosome interfaces, particularly H2B-H4, and that chromatin accessibility-promoting mutations are linked to mono-nucleosome destabilization. Leveraging this multiomic resource, we discovered that the H3.3-Q5H mutant histone is a bona fide human oncohistone that accelerates lung adenocarcinoma growth in vivo. Mechanistically, we found that H3.3-Q5H expression leads to suppression of promoter-associated H3K4me3 and expansion of repressive H3K27me3 domains, resulting in increased KRAS signaling and gene expression programs associated with epithelial-to-mesenchymal transition. Together, this work provides a multiomic functional atlas of cancer-associated histone mutations, identifies structural and mechanistic principles governing chromatin reprogramming by oncohistones, and establishes CHANCLA as a modular platform for systematic discovery of mechanisms and vulnerabilities associated with these genetic lesions.

cancer biology↗

bioRxiv2026

Beyond native sequence recovery: Improved modeling of thesequence-energy landscape of protein structures

Computational protein design using machine learning models has advanced rapidly since the introduction of AlphaFold2. There is now a suite of tools that enable in silico design of proteins with desired structures and properties. Most design workflows require fitting a designed backbone with a sequence that stabilizes it, and many machine learning sequence design models have been proposed. These models are trained to recover the native sequence paired with a known structure, a task known as native sequence recovery (NSR). Here, we demonstrate the limitations of optimizing a sequence design model only for NSR. We show that NSR is often misaligned with more important metrics of model performance: the compatibility of the generated sequence with the desired fold and the ability of the model to predict the energetic effects of mutations. We introduce PottsMPNN, which is trained to generate a Potts energy function consisting of single-residue and residue-pair terms from a protein backbone, and we demonstrate that learning a Potts model reduces NSR but improves sequence generation and energy prediction. To further show that NSR is not the optimal metric, we trained PottsMPNN with noised backbone structures and multiple sequence alignments. In tests on held-out data, NSR decreased, but the quality of the designed sequences and energy predictions improved. By demonstrating the limitations of optimizing for NSR and the effectiveness of alternative strategies for avoiding over-optimizing for NSR, our work provides a new direction for the sequence design field.

biophysics↗

bioRxiv2024

STAT5B leukemic mutations, altering SH2 tyrosine 665, have opposing impacts on immune gene programs

STAT5B is a vital transcription factor for lymphocytes. Here, function of two STAT5B mutations from human T cell leukemias: one substituting tyrosine 665 with phenylalanine (STAT5BY665F), the other with histidine (STAT5BY665H) was interrogated. In silico modeling predicted divergent energetic effects on homodimerization with a range of pathogenicity. In primary T cells in vitro STAT5BY665F showed gain-of-function while STAT5BY665H demonstrated loss-of-function. Introducing the mutation into the mouse genome illustrated that the gain-of-function Stat5bY665F mutation resulted in accumulation of CD8+ effector and memory and CD4+ regulatory T-cells, altering CD8+/CD4+ ratios. In contrast, STAT5BY665H knock-in mice showed diminished CD8+ effector and memory and CD4+ regulatory T cells. In contrast to wild-type STAT5, the STAT5BY665F variant displayed greater STAT5 phosphorylation, DNA binding and transcriptional activity following cytokine activation while the STAT5BY665H variant resembled a null. The work exemplifies how joining in silico and in vivo studies of single nucleotides deepens our understanding of disease-associated variants, revealing structural determinants of altered function, defining mechanistic roles, and, specifically here, identifying a gain-of function variant that does not directly induce hematopoietic malignancy.

genetics↗

bioRxiv2022

TRF2 rescues pathogenic phenotypes in Duchenne muscular dystrophy cardiomyocytes derived from human iPSCs

Duchenne muscular dystrophy (DMD) is a severe muscle wasting disease caused by the lack of dystrophin. Heart failure, driven by cardiomyocyte death, fibrosis, and the development of dilated cardiomyopathy, is the leading cause of death in DMD patients. Current treatments decrease the mechanical load on the heart, but do not address the root cause of dilated cardiomyopathy: cardiomyocyte death. Previously, we showed that telomere shortening is a hallmark of cardiomyocytes in DMD patient cardiac tissues and in a mouse model of DMD we generated that manifests dilated cardiomyopathy. We also found that this telomere shortening is recapitulated in DMD cardiomyocytes differentiated from patient-derived induced pluripotent stem cells (iPSCs). Here we further characterize that DMD cardiomyocytes exhibit reduced cell size, nuclear size, and sarcomere density compared to healthy isogenic controls. The telomere-binding protein, TRF2, is a core component of the shelterin complex, which protects chromosome ends and is expressed at lower levels in DMD cardiomyocytes compared to controls. We investigated whether preservation of telomere length could be achieved with upregulation of TRF2. We found that TRF2 upregulation in DMD cardiomyocytes increased telomere lengths, cell size, nuclear size, sarcomere density, and cell survival. These data suggest TRF2 gene therapy has the potential to delay the onset of dilated cardiomyopathy.

cell biology↗

bioRxiv2021

Insights into single hiPSC-derived cardiomyocyte phenotypes and maturation using ConTraX, an efficient pipeline for tracking contractile dynamics

Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) are powerful in-vitro models to study the mechanisms underlying cardiomyopathies and cardiotoxicity. To understand how cellular mechanisms affect the heart, it is crucial to quantify the contractile function in single hiPSC-CMs over time, however, such measurements remain demanding and low-throughput, and are too seldom considered. We developed an open-access, versatile, streamlined, and highly automated pipeline to address these challenges and enable quantitative tracking of the contractile dynamics of single hiPSC- CMs over time: ConTraX. Three interlocking software modules enable: (i) parameter-based localization and selection of single hiPSC-CMs; (ii) automated video acquisition of >200 cells/hour; and (iii) streamlined measurements of the contractile parameters via traction force microscopy. Using ConTraX, we analyzed >2,753 hiPSC-CMs over time under orthogonal experimental conditions in terms of culture media and substrate stiffnesses. Using undirected high-dimensional clustering, we dissected the complex diversity of contractile phenotypes in hiPSC-CM populations and revealed converging maturation patterns. Our modular ConTraX pipeline empowers biologists with a potent quantitative analytic tool applicable to the development of cardiac therapies.

bioengineering↗