Biology subjects

Bauer, M. S.

Publications and source records attributed to Bauer, M. S..

12 recordsLinked to original sources

bioRxiv2026

Design of readers for pathological PTM proteoforms in Alzheimer's disease

Alzheimer's disease (AD) is characterized by heterogeneous Tau phosphorylation and aberrant amyloid-beta (Abeta) processing, yet molecular tools that distinguish closely related molecular states of tau and Abeta with predefined specificity remain difficult to develop. Here, we designed de novo protein readers targeting three disease-associated phospho-Tau regions and N-terminal pyroglutamate-modified Abeta (N3pG-Abeta). Screening 192 designs per target identified 51 modification-selective hits among 768 candidates (6.6%). Representative readers exhibited nanomolar to subnanomolar affinities for modified peptides, discriminated authentic modifications from unmodified or substitution-based controls, and preferentially recognized modified full-length targets. We further programmed local modification specificity by interface redesign, generating pT231 readers conditional on the phosphorylation state of neighboring S235 and S237. A 2.0-angstrom crystal structure of an N3pG-Abeta reader closely matched the computational design model (interface C-alpha RMSD = 0.52 angstrom), and redesign of pT231 readers tuned apparent binding affinities from greater than 1 uM to below 1 nM. In a human 3D neuronal culture with both pathological Abeta and tau, selective readers targeting N3pG-Abeta, Tau pT231, and Tau pT217 recognized disease-associated signals, exhibiting colocalization with related antibodies and much higher signal in the AD line than the control. Tau pT231 readers further quantitatively distinguish AD patients and control human brain lysates in dot-blot assays. Together, these results establish genetically encoded readers with programmable specificity for defined Tau and Abeta modification states, enabling molecular-state-resolved detection in human disease models and biological samples, and lay a foundation for controlled pathological molecular perturbation.

bioengineering↗

bioRxiv2026

Reliable and Efficient Agentic Protein Design with Toolset Harnessing

Computational protein design workflows require the orchestration of multiple tools, data formats, and analysis steps that are often fragmented. Here, we introduce Chaperone, a lightweight and customizable framework that enables seamless integration of RFdiffusion3 (RFD3) with downstream sequence design, structure prediction, and evaluation tools, including ProteinMPNN, AlphaFold3 (AF3), and more than 50 other protein design tools. By combining a programmable agent-friendly interface with parallelized execution on high-performance computing systems, Chaperone as a harness enables rapid iteration and scalable exploration of complex protein design workflows. Across an evaluation of nine biomolecular design tasks, we find using Chaperone reduces total token usage relative to baseline agents by 86% and GPU costs by 64%, while increasing the overall computational design pass rate. We demonstrate Chaperones utility for large-scale design-space exploration through a two-week end-to-end small-molecule binder design campaign, yielding low nanomolar binders to cortisol zero shot. We further demonstrate its versatility across distinct design challenges, including the design of a symmetric 12-subunit self-assembly nanoparticle and a linker that mediates interactions between C2- and D3-symmetric protein complexes to form crystalline assemblies. Together, these results demonstrate how agent harnesses built around standardized tool interfaces can substantially improve the efficiency and success of complex, long-horizon agentic design workflows in biology. We make Chaperone freely available to the community on GitHub: https://github.com/RosettaCommons/chaperone.

biochemistry↗

bioRxiv2026

De novo design of selective kinase modulators

Protein kinases are critical regulators of cellular signaling, but precise modulation of their activity remains challenging due to their high structural conservation. Here, we present de novo designed genetically encoded miniproteins capable of activating or inhibiting focal adhesion kinase (FAK) by directly targeting the kinase domain itself. Among 96 binders designed to stabilize distinct conformational states of FAK, 33 modulated kinase activity. Biochemical characterization of the four most potent modulators revealed that two designs inhibit FAK with low-nanomolar IC50 values while the remaining two potentiated FAK activity by more than two-fold. When expressed in cells, the modulators preserved the same inhibitory and activating effects observed in vitro, establishing that designed conformational binders can directly tune FAK signaling in living cells. Taking advantage of the high similarity between kinases, we redesigned the FAK inhibitors to inhibit Src kinase. Our approach establishes a versatile platform for selective and genetically encoded kinase control as a way to rewire cell signaling and as a starting point for the discovery of novel modulatory sites of kinases.

biochemistry↗

bioRxiv2026

Engineering the mechanosensitivity of single DNA molecules via high-throughput microfluidic force spectroscopy

Single-molecule force spectroscopy (SMFS) is a powerful tool to measure how biomolecules respond to mechanical force, but limited sequence throughput constrains its potential. Here, we present a single-molecule, multiplexed, microfluidic force spectroscopy (SM3FS) assay that uses parallelized microfluidics to measure up to 80 sequence variants per experiment. Using SM3FS, we stretched, overstretched, or unzipped 241 different DNA structures and generated 131,847 single-molecule traces from a quarter-million observations. High sequence throughput allowed us to identify DNA structures that are kinetically stable yet mechanically fragile (Frupture < 3 pN at 0.5 pN s-1), revealing how mechanosensitivity can arise as an intrinsic property of multivalent systems. By enabling systematic sequence-function mapping under force, SM3FS opens a path to high-throughput nonequilibrium studies of biomolecules.

biophysics↗

bioRxiv2025

Computational design of cysteine proteases

Despite advances in de novo enzyme design, success has been largely limited to low energy barrier model reactions. Amide bonds such as those linking amino acids along the peptide backbone are stable for hundreds of years in neutral aqueous solution because of the high energy barrier to hydrolysis. Here we describe the de novo design of enzymes which utilize an activated cysteine nucleophile to hydrolyze the polypeptide backbone in a sequence-dependent manner, with a success rate of 13/69=19% and rate enhancements over the background reaction (kcat/kuncat) of up to 3 x 10^7. The designed proteases have folds very different from proteases in nature (TM score < 0.50), and six crystal structures are very close to the design models (Ca RMSDs < 1.2 A), highlighting the capacity for generalization and the accuracy of the design methodology. Experimental and computational analyses suggest that the remaining gap in activity to the most active native cysteine proteases arises from imperfections in active site preorganization and substrate positioning. The designed proteases efficiently cleave their targets in mammalian cells, opening the door to a wide range of synthetic biology applications.

biochemistry↗

bioRxiv2025

De novo design of phospho-tyrosine peptide binders

Phosphorylation on tyrosine is a key step in many signaling pathways. Despite recent progress in de novo design of protein binders, there are no current methods for designing binders that recognize phosphorylated proteins and peptides; this is a challenging problem as phosphate groups are highly charged, and phosphorylation often occurs within unstructured regions. Here we introduce RoseTTAFold Diffusion 2 for Molecular Interfaces (RFD2-MI), a deep generative framework for the design of binders for protein, ligand, and covalently modified protein targets. We demonstrate the power and versatility of this method by designing binders for four critical phosphotyrosine sites on three clinically relevant targets: Cluster of Differentiation 3 (CD3{varepsilon}), Epidermal Growth Factor Receptor (EGFR), Insulin Receptor (INSR) and Signal Transducer and Activator of Transcription 5 (STAT5). Experimental characterization shows that the designs bind their phosphotyrosine containing targets with affinities comparable to native binding sites and have negligible binding to non-phosphorylated targets or phosphopeptides with different sequences. X-ray crystal structures of generated binders to CD3{varepsilon} and EGFR are very close to the design models, demonstrating the accuracy of the design approach. A designed binder to an EGFR intracellular region phosphorylated upon EGF activation co-localizes with the receptor following EGF stimulation in single-particle tracking (SPT) experiments, demonstrating pY specific recognition in living cells. RFD2-MI provides a generalizable all-atom diffusion framework for probing and modulating phosphorylation-dependent signaling, and more generally, for developing research tools and targeted therapeutics against post-translationally modified proteins.

bioengineering↗

bioRxiv2025

Accelerating Biomolecular Modeling with AtomWorks andRF3

Deep learning methods trained on protein structure databases have revolutionized biomolecular structure prediction, but developing and training new models remains a considerable challenge. To facilitate the development of new models, we present AtomWorks: a broadly applicable data framework for developing state-of-the-art biomolecular foundation models spanning diverse tasks, including structure prediction, generative protein design, and fixed backbone sequence design. We use AtomWorks to train RosettaFold-3 (RF3), a structure prediction network capable of predicting arbitrary biomolecular complexes with an improved treatment of chirality that narrows the performance gap between closed-source AlphaFold3 (AF3) and existing open-source implementations. We expect that AtomWorks will accelerate the next generation of open-source biomolecular machine learning models and that RF3 will be broadly useful as a structure prediction tool. To this end, we release the AtomWorks framework (https://github.com/RosettaCommons/atomworks), together with curated training data, code and model weights for RF3 (https://github.com/RosettaCommons/modelforge) under a permissive BSD license.

biochemistry↗

bioRxiv2023

Restructuring of olfactory representations in the fly brain around odor relationships in natural sources

A core challenge of olfactory neuroscience is to understand how neural representations of odor are generated and progressively transformed across different layers of the olfactory circuit into formats that support perception and behavior. The encoding of odor by odorant receptors in the input layer of the olfactory system reflects, at least in part, the chemical relationships between odor compounds. Neural representations of odor in higher order associative olfactory areas, generated by random feedforward networks, are expected to largely preserve these input odor relationships1-3. We evaluated these ideas by examining how odors are represented at different stages of processing in the olfactory circuit of the vinegar fly D. melanogaster. We found that representations of odor in the mushroom body (MB), a third-order associative olfactory area in the fly brain, are indeed structured and invariant across flies. However, the structure of MB representational space diverged significantly from what is expected in a randomly connected network. In addition, odor relationships encoded in the MB were better correlated with a metric of the similarity of their distribution across natural sources compared to their similarity with respect to chemical features, and the converse was true for odor relationships encoded in primary olfactory receptor neurons (ORNs). Comparison of odor coding at primary, secondary, and tertiary layers of the circuit revealed that odors were significantly regrouped with respect to their representational similarity across successive stages of olfactory processing, with the largest changes occurring in the MB. The non-linear reorganization of odor relationships in the MB indicates that unappreciated structure exists in the fly olfactory circuit, and this structure may facilitate the generalization of odors with respect to their co-occurence in natural sources.

neuroscience↗

bioRxiv2023

Effects of Variants of Concern Mutations on the Force-Stability of the SARS-CoV-2:ACE2 Interface and Virus Transmissibility

Viruses mutate under a variety of selection pressures, allowing them to continuously adapt to their hosts. Mutations in SARS-CoV-2 have shown effective evasion of population immunity and increased affinity to host factors, in particular to the cellular receptor ACE2. However, in the dynamic environment of the respiratory tract forces act on the binding partners, which raises the question whether not only affinity, but also force-stability of the SARS-CoV-2:ACE2 bond, might be a selection factor for mutations. Here, we use magnetic tweezers (MT) to study the effect of amino acid substitutions in variants of concern (VOCs) on RBD:ACE2 bond kinetics with and without external load. We find higher affinity for all VOCs compared to wt, in good agreement with previous affinity measurements in bulk. In contrast, Alpha is the only VOC that shows significantly higher force stability compared to wt. Investigating the RBD:ACE2 interactions with molecular dynamics simulations, we are able to rationalize the mechanistic molecular origins of this increase in force-stability. Our study emphasizes the diversity of contributions to the assertiveness of variants and establishes force-stability as one of several factors for fitness. Understanding fitness-advantages opens the possibility for prediction of likely mutations allowing rapid adjustment of therapeutics, vaccination, and intervention measures.

biophysics↗

bioRxiv2021

A Tethered Ligand Assay to Probe SARS-CoV-2:ACE2 Interactions

SARS-CoV-2 infections are initiated by attachment of the receptor-binding domain (RBD) on the viral Spike protein to angiotensin-converting enzyme-2 (ACE2) on human host cells. This critical first step occurs in dynamic environments, where external forces act on the binding partners and multivalent interactions play critical roles, creating an urgent need for assays that can quantitate SARS-CoV-2 interactions with ACE2 under mechanical load and in defined geometries. Here, we introduce a tethered ligand assay that comprises the RBD and the ACE2 ectodomain joined by a flexible peptide linker. Using magnetic tweezers and atomic force spectroscopy as highly complementary single-molecule force spectroscopy techniques, we investigate the RBD:ACE2 interaction over the whole physiologically relevant force range. We combine the experimental results with steered molecular dynamics simulations and observe and assign fully consistent unbinding and unfolding events across the three techniques, enabling us to establish ACE2 unfolding as a molecular fingerprint. Measuring at forces of 2-5 pN, we quantify the force dependence and kinetics of the RBD:ACE2 bond in equilibrium. We show that the SARS-CoV-2 RBD:ACE2 interaction has higher mechanical stability, larger binding free energy, and a lower dissociation rate in comparison to SARS-CoV-1, which helps to rationalize the different infection patterns of the two viruses. By studying how free ACE2 outcompetes tethered ACE2, we show that our assay is sensitive to prevention of bond formation by external binders. We expect our results to provide a novel way to investigate the roles of mutations and blocking agents for targeted pharmaceutical intervention.

biophysics↗

bioRxiv2020

A Tethered Ligand Assay to Probe the SARS-CoV-2 ACE2 Interaction under Constant Force

The current COVID-19 pandemic has a devastating global impact and is caused by the SARS-CoV-2 virus. SARS-CoV-2 attaches to human host cells through interaction of its receptor binding domain (RBD) located on the viral Spike (S) glycoprotein with angiotensin converting enzyme-2 (ACE2) on the surface of host cells. RBD binding to ACE2 is a critical first step in SARS-CoV-2 infection. Viral attachment occurs in dynamic environments where forces act on the binding partners and multivalent interactions play central roles, creating an urgent need for assays that can quantitate SARS-CoV-2 interactions with ACE2 under mechanical load and in defined geometries. Here, we introduce a tethered ligand assay that comprises the RBD and the ACE2 ectodomain joined by a flexible peptide linker. Using specific molecular handles, we tether the fusion proteins between a functionalized flow cell surface and magnetic beads in magnetic tweezers. We observe repeated interactions of RBD and ACE2 under constant loads and can fully quantify the force dependence and kinetics of the binding interaction. Our results suggest that the SARS-CoV-2 ACE2 interaction has higher mechanical stability, a larger free energy of binding, and a lower off-rate than that of SARS-CoV-1, the causative agents of the 2002-2004 SARS outbreak. In the absence of force, the SARS-CoV-2 RBD rapidly (within [≤]1 ms) engages the ACE2 receptor if held in close proximity and remains bound to ACE2 for 400-800 s, much longer than what has been reported for other viruses engaging their cellular receptors. We anticipate that our assay will be a powerful tool investigate the roles of mutations in the RBD that might alter the infectivity of the virus and to test the modes of action of neutralizing antibodies and other agents designed to block RBD binding to ACE2 that are currently developed as potential COVID-19 therapeutics.

biophysics↗

bioRxiv2018

Monomeric streptavidin: a versatile regenerative handle for force spectroscopy

Most avidin-based handles in force spectroscopy are tetravalent biotin binders. Tetravalency presents two issues: multiple pulling geometries as well as multiple targets bound simultaneously. Additionally, such tetravalent handles require elaborate purification protocols in order to reassemble. A stoichiometric, monomeric variant of streptavidin (mcSA2) had been engineered previously. It is readily expressed and purified, and it binds biotin with a nanomolar KD. For atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS), we fused the monomeric streptavidin with a small protein domain as an experimental fingerprint and to improve solubility. A ybbR-tag was additionally included for covalent site-specific tethering. Rupture forces of the mcSA2:biotin complex were found to be in a comparable range above 150 pN at force loading rates of 1E4 pN/s as for previously published, tetravalent streptavidin:biotin systems. Additionally, when tethering mcSA2 from its C-terminus, rupture forces were found to be slightly higher than when tethered N-terminally. Due to its monomeric nature, mcSA2 could also be chemically denatured and subsequently refolded - and thus regenerated during an experiment, in case the handle gets misfolded or clogged. We show that mcSA2 features a straightforward expression and purification with flexible tags, high stability, regeneration possibilities and an unambiguous pulling geometry. Combined, these properties establish mcSA2 as a reliable handle for single-molecule force spectroscopy.

biophysics↗