Biology subjects

Winkler, D.

Publications and source records attributed to Winkler, D..

18 recordsLinked to original sources

bioRxiv2026

Learning from human and chemical languages to predict biological function

Understanding how molecular structure encodes biological function remains a grand challenge in drug discovery. Here, we present PubCheF-1, a deep learning model that predicts literature-derived biological function directly from chemical structure. PubCheF-1 was trained on a dataset linking molecules to labels derived from the scientific articles in which they appear, a strategy that connects disparate compounds through the language used to describe their functionalities. When tasked with identifying inhibitors of {beta}-lactamases, including enzymes considered largely refractory to inhibition, PubCheF-1 predicted structurally distinct compounds that collectively have activity against all {beta}-lactamase classes. Furthermore, hit compounds directly bind the enzyme active site, restore antibiotic efficacy in multidrug-resistant high-priority pathogens, and demonstrate potent activity in animal infection models. Together, these findings establish that machine learning-based prediction of biological function derived from the language of scientific literature allows the identification of bioactive molecules at high hit rates, thereby accelerating therapeutic discovery.

bioinformatics↗

bioRxiv2026

Discovery of CDK4-selective molecular glue degraders by high-throughput proteomics

Molecular glue degraders (MGDs) are proximity-inducing molecules that promote the destruction of disease-causing proteins by stabilizing novel interfaces between E3 ubiquitin ligases and target proteins. The rational design of MGDs remains exceptionally challenging, historically relying on serendipitous discoveries. Here, we deployed a high-throughput, mass spectrometry (MS)-based screen evaluating thousands of cereblon (CRBN)-directed compounds to expedite the identification of novel neosubstrates. This workflow led to the discovery of NE26394, a first-in-class MGD that selectively eliminates cyclin-dependent kinase 4 (CDK4), a critical oncogenic driver of cell cycle progression. Mechanistically, NE26394-induced CDK4 recognition by CRBN depends on the co-recruitment of endogenous INK4 family proteins. In CDK4-dependent cancer models, NE26394 effectively mimics the anti-proliferative RB-E2F pathway perturbations induced by clinical CDK4 inhibitors, rendering it an attractive candidate for further preclinical development.

biochemistry↗

bioRxiv2026

Integrated proteomic screening reveals design principles of CRBN molecular glue degraders

Cereblon (CRBN)-based molecular glue degraders (MGDs) induce the degradation of diverse disease-relevant proteins, underscoring their broad therapeutic potential. Here we systematically expand the CRBN neosubstrate landscape using a target-agnostic discovery approach. By integrating deep proteomic and ubiquitinomic profiling of a 960-compound library, we identify compound-induced ubiquitination and depletion of over 230 endogenous proteins. Among these, 124 represent previously unreported CRBN neosubstrates, with over half lacking a predicted G-loop degron. We provide this dataset via an interactive resource, NeosubstratesDB. Complementary cellular and biochemical assays mechanistically define the interaction domain of IRAK1 and establish G-loop-dependent degradation for BCL6. Interpretable machine learning (iML) integrating proteomic profiles with chemical structures highlights key molecular fingerprints driving neosubstrate selectivity for targets such as CSNK1A1, ZFP91 and WEE1. Together, these findings significantly expand the repertoire of CRBN neosubstrates and provide a framework for rational design of next-generation MGDs.

biochemistry↗

bioRxiv2026

Developing Potent and Selective TBK1 Molecular Glue Degraders for Cancer Immunotherapy

Immune checkpoint blockade (ICB) has transformed cancer therapy across multiple tumour types, yet primary and acquired resistance remain major barriers to durable benefit. TANK-binding kinase 1 (TBK1) has emerged as an attractive target to enhance anti-tumour immunity, acting as a serine/threonine kinase that restrains immunogenic cell death and downstream immune activation. Here we report the discovery of a first-in-class TBK1 molecular glue degrader (MGD), CCT412020, identified through high-throughput proteomics screening of a next-generation molecular glue library. CCT412020 induces rapid, potent and selective TBK1 degradation across a panel of breast cancer cell lines. A cryo-EM structure of CCT412020 in complex with CRBN/{Delta}BPB-DDB1 and TBK1-homodimer reveals an unexpected binding mode that bypasses the canonical G-loop and instead engages an unconventional site at the TBK1 homodimer interface. Functionally, TBK1 loss via CCT412020 sensitises tumour cells to TNF- and interferon-driven responses and reduced viability across a broad range of cancer cell lines. Together, these findings establish CCT412020 as a mechanistically distinct TBK1 degrader and provide a framework for developing TBK1-targeted degraders as immunomodulatory anti-cancer agents to overcome ICB resistance.

cancer biology↗

bioRxiv2025

Ambient temperature, clutch size, and daylight are the main drivers of incubation behavior in two neotropical swallows breeding 8,000 km apart

The central dilemma in incubation behaviour is how to allocate time between warming up the clutch and self-preservation activities outside the nest. It is assumed that incubating birds follow a classical framework in which the environmental temperature, the main variable influencing incubation behaviour, and bout duration show a non-linear relationship. In this context, incubating birds would maximize bout duration for most of the temperature range in which they breed. To determine whether this theoretical framework applies to species breeding at different latitudes under extremely different environmental conditions, we collected incubation data from two distant but breeding populations of Tachycineta swallows. T. leucopyga (Chillean swallow) breeds in Ushuaia, Argentina, and T. meyeni (mangrove swallow) breeds in Hill Bank, Belize. These populations do not overlap in terms of ambient temperature; they are exposed to different daylight conditions and the latitudinal differences influence life-history traits such as clutch size. Tachycineta swallows showed similar incubation consistency over 24 hours ([~]75% of nest attendance) but followed different behavioral strategies to achieve this consistency. Daylight duration limited incubation activity in mangrove swallows, but longer nocturnal incubation compensated for shorter days. Larger clutches only took their toll on the Chilean swallows, by shortening their incubation bouts and lengthening their foraging bouts, which affected the length of their daily activity. Overall, both swallow species showed incubation patterns adapted to the local conditions. They responded differently to increasing temperatures, but both species reduced their incubation effort whenever possible. Our results contrast with previous work where maximizing incubation effort was the rule. In our populations, females reduced their incubation effort as soon as weather conditions improved (i.e., increasing temperatures), changing the paradigm of incubation behaviour. Lay summary- In species where only the male or female incubates, they need to find a balance between the time they spend incubating in the nest and the time they spend foraging out of the nest. - The ambient temperature is the most important factor influencing the duration of both behaviours, and birds are thought to respond similarly to the same range of temperatures. - We studied the incubation behaviour of two species of swallows breeding in Belize and Argentina, respectively. - Both species incubated for a similar length of time in 24 hours, but each followed a different strategy depending on clutch size and daylight duration. - Their incubation behaviour was also related to ambient temperature, but differed between populations, suggesting adaptations to local conditions. - We cannot expect different species to show similar responses to ambient temperature under different conditions.

animal behavior and cognition↗

bioRxiv2025

Role of Chloroplast Lipid-Remodelling Protein 23 During Cold Acclimation in Arabidopsis thaliana

Cold acclimation is a crucial physiological process that enables plants to adapt to low temperatures. A key aspect of this adaptation is lipid remodeling, which preserves membrane fluidity and integrity under cold stress. Proteins of the chloroplast envelope membranes are increasingly recognized for their role in acclimation to changing environmental conditions. While lipid synthesis occurs at the inner envelope membrane, little is known about specific proteins involved in lipid remodeling during cold acclimation. In this study, we investigate the role of Chloroplast Lipid Remodeling Protein 23 (CLRP23) as a component of the inner chloroplast envelope membrane. Subcellular fractionation combined with protease protection assays provided evidence for its orientation toward the intermembrane space. To explore its function, we analyzed the physiological performance and lipid composition in CLRP23-deficient mutant plants. Under cold stress, we observed significant impairments in photosynthesis and exaggerations in galactolipid response, suggesting CLRP23 is involved in lipid remodeling. Lipid overlay assays, supported by in silico docking analyses, demonstrate that CLRP23 can directly interact with chloroplast lipids, including galactolipids. Complementary transcriptomic and proteomic analyses reveal broader effects on cold-responsive pathways, supporting the view that CLRP23 contributes to the integration of membrane and metabolic responses during acclimation. These findings expand our understanding of protein-mediated processes during cold acclimation.

plant biology↗

bioRxiv2024

Identification of Molecular Compounds Targeting Bacterial Propionate Metabolism with Topological Machine Learning

This study demonstrates the effective integration of comparative protein sequence analysis with novel topological machine learning methods to tackle a key issue in computational biology: identifying potential inhibitor compounds for methylcitrate dehydratase--an enzyme essential to the methylcitrate pathway in bacteria and fungi. While many ML models have proven effective on benchmark datasets, we applied these techniques specifically to discover compounds for this target protein. This pathway, crucial for metabolizing propionic acid, is essential in pathogenic bacteria for utilizing host-derived lipids and amino acids, making it a promising antimicrobial target. Inefficient removal of propionate can lead to toxic accumulation, threatening microbial survival. In our research, we utilize the latest methods in topological machine learning, multiparameter persistence, to transform the molecular structure of potential compounds into topological vectors for ligand-based drug discovery. By applying our tailored topological model, we prioritized 15 compounds with promising characteristics for inhibiting the active site of methylcitrate dehydratase. Computational molecular docking simulations reveal that these identified compounds interact with key amino acid residues critical to the enzymes function. Our findings underscore the power of integrating topology-based modeling with comparative sequencestructure-function analysis and ligand docking. Considering compounds geometric fit, energy, and interaction profiles enhances predictions and guides the design of optimized new compounds. This refined approach offers a solid foundation for lead optimization, representing the most promising molecular scaffolds for modification, advancing compound discovery, and providing valuable insights into binding interactions for further experimental validation and potential drug development. Our code is available at https://github.com/AstritTola/Molecular-Compounds-Targeting

microbiology↗

bioRxiv2023

Robust and scalable single-molecule protein sequencing with fluorosequencing

The need to accurately survey proteins and their modifications with ever higher sensitivities, particularly in clinical settings with limited samples, is spurring development of new single molecule proteomics technologies. Fluorosequencing is one such highly parallelized single molecule peptide sequencing platform, based on determining the sequence positions of select amino acid types within peptides to enable their identification and quantification from a reference database. Here, we describe substantial improvements to fluorosequencing, including identifying fluorophores compatible with the sequencing chemistry, mitigating dye-dye interactions through the use of extended polyproline linkers, and developing an end-to-end workflow for sample preparation and sequencing. We demonstrate by fluorosequencing peptides in mixtures and identifying a target neoantigen from a database of decoy MHC peptides, highlighting the potential of the technology for high sensitivity clinical applications.

molecular biology↗

bioRxiv2023

Directed evolution of piperazic acid incorporation by a nonribosomal peptide synthetase

Engineering of biosynthetic enzymes is increasingly employed to synthesize structural analogues of antibiotics. Of special interest are non-ribosomal peptide synthetases (NRPSs) responsible for production of important antimicrobial peptides. Here, directed evolution of an adenylation domain of a Pro-specific NRPS module completely switched substrate specificity to the non-standard amino acid piperazic acid (Piz) bearing a labile N-N bond. This success was achieved by LC-MS/MS based screening of small, rationally designed mutant libraries and can presumably be replicated with a larger number of substrates and NRPS modules. The evolved NRPS produces a Piz-derived gramicidin S analog. Thus, we give new impetus to the too-early dismissed idea that widely accessible low-throughput methods can switch the specificity of NRPSs in a biosynthetically useful fashion.

synthetic biology↗

bioRxiv2023

Signalling pathway crosstalk stimulated by L-proline drives differentiation of mouse embryonic stem cells to primitive-ectoderm-like cells

The amino acid L-proline exhibits novel growth factor-like properties during development - from improving blastocyst development to driving neurogenesis in vitro. Addition of 400 M L-proline to self-renewal medium drives mouse embryonic stem cells (ESCs) to a transcriptionally distinct pluripotent cell population - early primitive ectoderm-like (EPL) cells - which lies between the naive and primed states. EPL cells retain expression of pluripotency genes, upregulate primitive ectoderm markers, undergo a morphological change and have increased cell number. These changes are facilitated by a complex signalling network hinging on the Mapk, Fgfr, Pi3k and mTor pathways. We use a factorial experimental design coupled with linear modelling and Bayesian regularised neural networks to understand which signalling pathways are involved in the transition between ESCs and EPL cells, and how they underpin changes in morphology, cell number, apoptosis, proliferation and gene expression. This approach allows for consideration of where pathways work antagonistically or synergistically. Modelling showed that most properties were affected by more than one inhibitor, and each inhibitor blocked specific aspects of differentiation. These mechanisms underpin both progression of stem cells across the in vitro pluripotency continuum and serve as a model for pre-, peri- and post-implantation embryogenesis. Summary StatementL-proline acts as growth factor to modulate phosphorylation of the Mapk, Pi3k, Fgf and mTor signalling pathways to drive embryonic stem cells to primitive ectoderm-like cells.

developmental biology↗

bioRxiv2021

Acidophilic Micrarchaeon Seems to Maintain a Slightly Alkaline Cytosolic pH

Despite several discoveries in recent years, the physiology of acidophilic Micrarchaeota remains largely enigmatic. "Candidatus Micrarchaeum harzensis A_DKE", for example, highly expresses numerous genes encoding hypothetical proteins and their function is difficult to elucidate due to a lacking genetic system. Still, not even the intracellular pH value of A_DKE is known, and heterologous production attempts are generally missing so far. Hence, A_DKEs isocitrate dehydrogenase (MhIDH) was recombinantly produced in Escherichia coli and purified for bio-chemical characterisation. MhIDH appeared to be specific for NADP+, yet promiscuous regarding divalent cations as cofactors. Kinetic studies showed KM-values of 53.03{+/-}5.63 {micro}M and 1.94{+/-}0.12 mM and kcat-values of 38.48{+/-}1.62 s-1 and 43.99{+/-}1.46 s-1 for DL-isocitrate and NADP+, respectively. MhIDHs exceptionally low affinity for NADP+, potentially limiting its reaction rate, can be likely attributed to the presence of a proline residue in the NADP+ binding-pocket, which might cause a decrease in hydrogen bonding of the cofactor and a distortion of local secondary structure. Furthermore, a pH optimum of 7.89 implies, that A_DKE applies potent mechanisms of proton homoeostasis, to maintain a slightly alkaline cytosolic milieu in a highly acidic environment.

biochemistry↗

bioRxiv2021

Micrarchaeota are covered by a proteinaceous S-Layer

In previous publications, it was hypothesized that Micrarchaeota cells are covered by two individual membrane systems. This study proofs that at least the recently cultivated "Candidatus Micrarchaeum harzensis A_DKE" possesses an S-layer covering its cytoplasmic membrane. The potential S-layer protein was found to be among the proteins with the highest abundance in A_DKE and in silico characterization of its primary structure indicated homologies to other known S-layer proteins. Homologs of this protein were found in other Micrarchaeota genomes, which raises the question, whether the ability to form an S-layer is a common trait within this phylum. The S-layer protein seems to be glycosylated and the Micrarchaeum expresses genes for N-glycosylation under cultivation conditions, despite not being able to synthesize carbohydrates. Electron micrographs of freeze-etched samples of a previously described co-culture, containing Micrarchaeum A_DKE and a Thermoplasmatales member as its host organism, verified the hypothesis of an S-layer on the surface of A_DKE. Both organisms are clearly distinguishable by cell size, shape and surface structure.

microbiology↗

bioRxiv2021

Escitalopram Administration, Neuroplastic Effects and Relearning: A Diffusion Tensor Imaging Study in Healthy Individuals

BackgroundNeuroplastic processes are influenced by selective serotonergic reuptake inhibitors, while learning in conjunction with the administration of serotonergic agents alters white matter microstructure in humans. The goal of this double-blind, placebo-controlled imaging study was to investigate the influence of escitalopram on white matter plasticity during (re)learning. MethodsSeventy-one healthy individuals (age = 25.6{+/-}5.0, 43 females) underwent 3 diffusion magnetic resonance imaging sessions: at baseline, after 3-weeks of associative learning (emotional/non-emotional content) and after relearning shuffled associations for an additional 3 weeks. During the relearning phase, subjects received daily escitalopram 10 mg or placebo orally. Statistical analysis was performed with statistical parametric mapping (SPM) and using sandwich estimator. ResultsA three-way and two-way rmANOVA was conducted to analyze the effects of escitalopram on AD, FA, MD and RD during the learning and relearning period. We found no significant three-way or two-way interactions for each DTI metrics (pFDR > 0.05), thus neither after 3 nor after 6 weeks we found significant changes in white matter microstructure. ConclusionWe examined neither an effect of escitalopram nor learning (or relearning) interventions on different DTI metrics. The duration and intensity of study interventions (i.e. administration of escitalopram and learning as the relearning task) might have been chosen insufficiently to induce detectable alterations. Previous studies examining the effects of SSRIs on white matter tracts in humans are underrepresented, but do mainly yield towards non-significant findings. The results implicate that escitalopram does not impact white matter microstructures in healthy subjects.

neuroscience↗

bioRxiv2020

Evolutionary design of optimal surface topographies for biomaterials

Natural evolution tackles optimization by producing many genetic variants and exposing these variants to selective pressure, resulting in the survival of the fittest. We use high throughput screening of large libraries of materials with differing surface topographies to probe the interactions of implantable device coatings with cells and tissues. However, the vast size of possible parameter design space precludes a brute force approach to screening all topographical possibilities. Here, we took inspiration from Nature to optimize materials surface topographies using evolutionary algorithms. We show that successive cycles of material design, production, fitness assessment, selection, and mutation results in optimization of biomaterials designs. Starting from a small selection of topographically designed surfaces that upregulate expression of an osteogenic marker, we used genetic crossover and random mutagenesis to generate new generations of topographies.

bioinformatics↗

bioRxiv2019

Detection of interictal epileptiform discharges:A comparison of on-scalp MEG and conventional MEGmeasurements

Magnetoencephalography (MEG) is an important part of epilepsy evaluations because of its unsurpassed ability to detect interictal epileptiform discharges (IEDs). This ability may be improved by next-generation MEG sensors, where sensors are placed directly on the scalp instead of in a fixed-size helmet, as in todays conventional MEG systems. In order to investigate the usefulness of on-scalp MEG measurements we performed the first-ever measurements of on-scalp MEG on an epilepsy patient. The measurement was conducted as a benchmarking study, with special focus on IED detection. An on-scalp high-temperature SQUID system was utilized alongside a conventional low-temperature "in-helmet" SQUID system. EEG was co-registered during both recordings. Visual inspection of IEDs in the raw on-scalp MEG data was unfeasible why a novel machine learning-based IED-detection algorithm was developed to guide IED detection in the on-scalp MEG data. A total of 24 IEDs were identified visually from the conventional in-helmet MEG session (of these, 16 were also seen in the EEG data; eight were detected only by MEG). The on-scalp MEG data contained a total of 47 probable IEDs of which 16 IEDs were co-registered by the EEG, and 31 IEDs were on-scalp MEG-unique IEDs found by the IED detection algorithm. We present a successful benchmarking study where on-scalp MEG are compared to conventional in-helmet MEG in a temporal lobe epilepsy patient. Our results demonstrate that on-scalp MEG measurements are feasible on epilepsy patients, and indicate that on-scalp MEG might capture IEDs not seen by other non-invasive modalities.

neuroscience↗

bioRxiv2019

On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG

Magnetoencephalography (MEG) has a unique capacity to resolve the spatio-temporal development of brain activity from non-invasive measurements. Conventional MEG, however, relies on sensors that sample from a distance (20-40 mm) to the head due to thermal insulation requirements (the MEG sensors function at 4 K in a helmet). A gain in signal strength and spatial resolution may be achieved if sensors are moved closer to the head. Here, we report a study comparing measurements from a seven-channel on-scalp SQUID MEG system to those from a conventional (in-helmet) SQUID MEG system.\n\nWe compared spatio-temporal resolution between on-scalp and conventional MEG by comparing the discrimination accuracy for neural activity patterns resulting from stimulating five different phalanges of the right hand. Because of proximity and sensor density differences between on-scalp and conventional MEG, we hypothesized that on-scalp MEG would allow for a more high-resolved assessment of these activity patterns, and therefore also a better classification performance in discriminating between neural activations from the different phalanges.\n\nWe observed that on-scalp MEG provided better classification performance during an early post-stimulus period (15-30 ms). This corresponded to electroencephalographic (EEG) response components N16 and P23, and was an unexpected observation as these components are usually not observed in conventional MEG. They indicate that on-scalp MEG opens up for a richer registration of the cortical signal, allowing for sensitivity to what are potentially sources in the thalamo-cortical radiation and to quasi-radial sources.\n\nWe had originally expected that on-scalp MEG would provide better classification accuracy based on activity in proximity to the P60m component compared to conventional MEG. This component indeed allowed for the best classification performance for both MEG systems (60-75%, chance 50%). However, we did not find that on-scalp MEG allowed for better classification than conventional MEG at this latency. We believe this may be due to the limited sensor coverage in the recording, in combination with our strategy for positioning the on-scalp MEG sensors. We discuss how sensor density and coverage as well as between-phalange source field dissimilarities may influence our hypothesis testing, which we believe to be useful for future benchmarking measurements.

neuroscience↗

bioRxiv2019

Sensor localization using magnetic dipole-like coils: A method for highly accurate co-registration in on-scalp MEG

Source modelling in magnetoencephalography (MEG) requires precise co-registration of the sensor array and the anatomical structure of the measured individuals head. In conventional MEG, positions and orientations of the sensors relative to each other are fixed and known beforehand, requiring only localization of the head relative to the sensor array. Since the sensors in on-scalp MEG are positioned on the scalp, locations of the individual sensors depend on the subjects head shape and size. The positions and orientations of on-scalp sensors must therefore be measured at every recording. This can be achieved by inverting conventional head localization, localizing the sensors relative to the head - rather than the other way around.\n\nIn this study we present a practical method for localizing sensors using magnetic dipole-like coils attached to the subjects head. We implement and evaluate the method in a set of on-scalp MEG recordings using a 7-channel on-scalp MEG system based on high critical temperature superconducting quantum interference devices (high-Tc SQUIDs). The method provides accurate estimates of individual sensor positions and orientations with short averaging time ([≤] 2 mm and < 3 degrees, respectively, with 1-second averaging), enabling continuous sensor localization. Calibrating and jointly localizing the sensor array can further improve the localization accuracy (< 1 mm and < 2.5 degrees, respectively, with 1-second coil recordings).\n\nWe demonstrate source localization of on-scalp recorded somatosensory evoked activity based on co-registration with our method. Equivalent current dipole fits of the evoked responses corresponded well (within 5.3 mm) with those based on a commercial, whole-head MEG system.

neuroscience↗

bioRxiv2019

A 7-channel high-Tc SQUID-based on-scalp MEG system

Due to their higher operating temperature, high-Tc superconducting quantum interference devices (SQUIDs) require less thermal insulation than the low-Tc sensors that are utilized in commercial magnetoen-cephalography (MEG) systems. As a result, they can be placed closer to the head, where neuromagnetic fields are higher and more focal, potentially leading to higher spatial resolution. The first such on-scalp MEG measurements using high-Tc SQUIDs have shown the potential of the technology. In order to be useful for neuroscience and clinical applications, however, multi-channel systems are required. Herein, we present a 7-channel on-scalp MEG system based on high-Tc SQUIDs. The YBCO SQUID magnetometers are arranged in a dense, head-aligned hexagonal array inside a single, liquid nitrogen-cooled cryostat. The spacing between the magnetometers and the head is adjustable down to 1 mm. The sensors are side-mounted on the cryostat that is mounted on an articulated armature for recordings on arbitrary head locations of a seated subject. We demonstrate white noise levels of 50-130 fT/Hz1/2 at 10 Hz, sensor-to-sensor crosstalk values of <0.6%, and single-fill operation times of 16 hours. We validate the system with MEG recordings of visual alpha modulation and auditory evoked fields. The system is thus useful for densely and sensitively sampling neuromagnetic fields over any[~] 10 cm2 patch of the scalp surface over the course of a day.

neuroscience↗