Biology subjects

Höcker, B.

Publications and source records attributed to Höcker, B..

14 recordsLinked to original sources

bioRxiv2026

The novel viper FETUA-3 protein evolved a unique mode of inhibiting snake venom metalloproteinases

Molecular innovation and coevolution play major roles in the evolution of biological diversity, yet we have relatively few instances in which we understand the biological and molecular bases of coevolution. Rattlesnakes and other vipers have evolved resistance to their own novel venom metalloproteinase (MP) toxins through the invention and coevolution of serum-borne inhibitors (FETUAs) derived from the ancestral, non-inhibitory, serum glycoprotein Fetuin-A. However, how FETUAs acquired their function and their mechanism of action are unknown. Here, we use a combination of structure prediction, site-directed mutagenesis, functional analyses, and molecular dynamics to elucidate how the rattlesnake FETUA-3 protein evolved to inhibit three classes of venom MP toxins. We show that FETUA-3 uses a combination of structural motifs to bind multiple MPs with high-affinity and acts as a potent noncompetitive inhibitor by inserting its N-terminus into MP active sites and directly disrupting substrate cleavage. We also find strong selective constraints on key N-terminal residues that maintain FETUA-3 specificity for multiple MP targets. These results reveal that FETUA-3 evolved a unique mechanism of action distinct from other vertebrate metalloproteinase inhibitors and how a small number of FETUA proteins controls the activities of a large family of venom toxins.

evolutionary biology↗

bioRxiv2026

Predicting single mutation effects on binding affinity at protein-protein interfaces based on MMPBSA calculations

Accurate prediction of mutation-induced changes in protein-protein affinity remains a central challenge in computational biophysics and protein engineering. Here we present a physics-based scoring method for predicting the effects of single amino acid substitutions on protein-protein and protein-peptide binding affinity. The method is based on MMPBSA energy calculations and implemented in a user-friendly, publicly available workflow (https://github.com/Hoecker-Lab/mmpbsa_scoring). To derive the scoring function, MMPBSA energy terms were fitted using a large and diverse dataset of experimentally measured binding affinity changes upon point mutation. The terms were then evaluated on independent systems. Specifically, we assessed the ability to predict mutational effects at the interface of SARS-CoV-2 spike protein with its cellular receptor, as well as computationally predicted Armadillo-repeat protein-peptide complexes. The approach performs well across diverse targets and shows promising predictive performance on both experimentally determined and computationally predicted structures. It matches or exceeds the accuracy of established physics-based protein design software and state-of-the-art deep learning-based scoring functions when applied to data outside their training domain. The method provides a computationally efficient and interpretable framework for prioritizing interface mutations in protein engineering and binding affinity optimization.

bioinformatics↗

bioRxiv2026

An engineered biosensor for the fast and accurate detection of terephthalate

Accelerating the development of enzymatic degradation of polyesters such as poly(ethylene terephthalate) (PET) and poly(butylene terephthalate) (PBT) requires a rapid and parallelizable detection method. We developed a protein-based biosensor for the fast and accurate quantification of the PET and PBT degradation product, terephthalate (TPA), which we named TPAsense. Engineering TPAsense required overcoming low thermal stability and aggregation of the initial construct by introducing stabilizing mutations without disrupting the binding affinity to TPA. The sensor performance was validated by screening for the PBT degrading activity of a Leaf-branch Compost Cutinase (LCC) mutant library and comparing with liquid chromatography data. TPAsense detects nanomolar concentrations of TPA enabling shorter incubation times for screening workflows. In addition, a comparative analysis of PETase and PBTase kinetics was performed with TPAsense. Finally, we demonstrated the detection of PET microplastic in samples from a wastewater treatment plant by combining the biosensor and a PETase. TPAsense offers a platform to accelerate PETase and PBTase development for plastic waste recycling and detection of microplastic in the environment.

biochemistry↗

bioRxiv2025

Optimizing stability in dynamic small-molecule binding proteins

The function of dynamic proteins is determined by the stability of distinct conformational states and the energy barriers that separate these states. For most dynamic proteins, the molecular details of the energy barriers are not known, implying a fundamental limit to the ability of protein design methods to engineer beneficial mutations without disrupting activity. We hypothesized that designing mutations that are compatible with structurally distinct equilibrium conformations may enable reliable stability design. We focus on periplasmic binding proteins (PBPs), a superfamily of dynamic proteins that change conformation from open to closed states in response to binding their small-molecule ligands. We find that the evolutionary constrained space of allowed mutations computed for one conformation is incompatible with the other. Therefore, putative conformational hinge points and interface residues were additionally constraint, and incompatible mutations were filtered out. Starting from four different PBPs, we designed a total of 16 stabilized variants with 7-28 mutations each. Our results show that design based on a single conformation with evolutionary constraints is not sufficient to maintain wild type-like binding affinity. Conversely, using a subset of mutations compatible with both conformations and structural constraints reliably enhances thermal stability while mitigating trade-offs in ligand binding. Our work demonstrates a straightforward method for the one-shot stabilization of dynamic proteins, which is critically required to generate robust starting points for thermostable and responsive biosensors.

biochemistry↗

bioRxiv2025

Tumbleweed: an artificial motor protein that walks along a DNA track

Summary ParagraphMolecular motors are fundamental to life1-6 because of their ability to convert chemical energy into mechanical work, an ability that is conferred by the chemical and structural complexity of their constituent proteins. Scientists have long sought to create artificial protein motors that may reveal insights into how biological motors function. While artificial molecular motors based on small molecules7 and DNA8,9 have been developed, creating an artificial motor protein has remained an elusive goal in synthetic biology10. Here we demonstrate the realization of an artificial protein motor called Tumbleweed (TW) that walks directionally along a DNA track under external control. TW consists of three legs, each with a ligand-gated DNA-binding domain that enables selective interaction with specific sites along a DNA track11. Using single-molecule fluorescence assays and a programmable microfluidic device, we show that TW steps directionally along a designed DNA track in response to a defined sequence of ligand inputs. We built our TW molecular walker using a modular approach, combining existing proteins with known properties to achieve emergent motor function, similar to how Nature evolves new proteins. Our design strategy thus offers a a platform for engineering advanced and dynamic protein functionality. Our demonstration of TW walking represents a step toward developing fully autonomous protein motors and opens new avenues for uncovering and leveraging the principles by which biological motors transduce chemical energy into motion.

biophysics↗

bioRxiv2025

A third type of PETase from the marine Halopseudomonas lineage

The enzymatic degradation of polyethylene terephthalate (PET) offers a sustainable solution for PET recycling. Over the past two decades, more than 100 PETases have been characterized, primarily exhibiting similar sequences and structures. Here, we report new PET-degrading /{beta} hydrolases, including HaloPETase1 from the marine Halopseudomonas lineage, thereby extending the narrow sequence space by novel features at the active site. The crystal structure of HaloPETase1 was determined to a resolution of 1.16 [A], revealing a unique active site architecture and a lack of the canonical {pi}-stacking clamp found in PETases so far. Further, variations in active site composition and loop structures were observed. Additionally, we found five more enzymes from the same lineage, two of which have a high similarity to type IIa bacterial PETases, while the other three resemble HaloPETase1. All these enzymes exhibited high salt tolerance ranging from 2.5 to 5 M NaCl leading to higher total product releases upon PET degradation at 40 or 50 {degrees}C. Based on these findings, we propose an extension of the existing PETase classification system to include type III PETases.

biochemistry↗

bioRxiv2024

De novo design of triosephosphate isomerases using generative language models

The design of proteins with tailored functions is of immense interest to biotechnology, medicine, and the chemical industry. While protein design is rapidly evolving with the use of AI techniques, the design of complex enzymes remains a challenge. Here, we present the use of two large language models (LLMs), ZymCTRL and ProtGPT2, for the generation of de novo enzymes that catalyze the triosephosphate isomerase (TIM) reaction. Natural TIM enzymes are obligatory oligomers that catalyze a multi-step isomerization reaction near the diffusion limit. This makes TIM an ideal target to assess the generative ability of protein language models. Newly generated sequences were filtered to obtain a set of twelve candidates from each approach for experimental validation. Multiple constructs from both language models exhibit the intended function in vivo through their ability to complement a TIM-deficient E. coli strain. In-depth characterization of the best-behaving artificial enzyme reveals behavior and catalytic efficiency close to its natural counterparts. These findings support the use of conditional and fine-tuned unconditional LLMs for the generation of complex enzymes.

biochemistry↗

bioRxiv2024

A fluorescent biosensor for the visualization of agmatine

Agmatine is known to regulate various neurotransmitter systems, yet the underlying molecular mechanisms remain elusive. To visualize agmatine dynamics in cellular networks and thereby unravel its physiological functions, we developed a genetically encoded fluorescent agmatine biosensor (AGMsen) based on the periplasmic putrescine binding protein PotF. We first analyzed the agmatine binding properties of the PotF receptor module based on its crystal structure and introduced mutations into the binding pocket to favor agmatine binding over other biogenic amines. Validation of AGMsen functionality across different cell types, including primary neuronal cultures, demonstrates its ability of real-time agmatine visualization. Thus, the sensor can serve as a valuable tool to advance our understanding of agmatine distribution and dynamics, and shed light on their effect on neuronal functions in vivo.

biochemistry↗

bioRxiv2023

Hydrophobic Clusters Direct Folding of a Synthetic Chimeric Protein

Extant proteins frequently share sub-domain sized fragments, suggesting that among other mechanisms, proteins evolved new structure and functions via recombination of existing fragments. While the role of protein fragments as evolutionary units is well-established, their biophysical features necessary for generating a well-folded and stable protein are not clearly understood. In order to probe how fragments determine foldability and stability of recombined proteins, we investigated the stability, folding and dynamics of a synthetic chimera created by fusion of fragments of the chemotactic response regulator protein CheY that belongs to the flavodoxin-like fold and imidazole glycerol phosphate synthase from histidine biosynthesis (HisF) which harbors the TIM-barrel fold. The chimera unfolds via an equilibrium intermediate. Mutation of a glycine residue present at the interface of the CheY and HisF fragments to a valine abrogates the equilibrium intermediate while mutation to isoleucine dramatically increases the native state kinetic stability without any significant change in the folding rate. Parts of the fragment interface in the chimera are found to be conformationally dynamic while hydrophobic mutations globally increase its conformational rigidity. We hypothesize that the hydrophobic mutation improves sidechain packing in a large cluster of isoleucine, leucine and valine (ILV) residues that spans the fragment interface. We also extrapolate that inheritance of large ILV clusters from parent proteins could be a key determinant of successful fragment recombination.

biophysics↗

bioRxiv2023

Retracing the evolution of a modern periplasmic binding protein

Investigating the evolution of structural features in modern multidomain proteins helps to understand their immense diversity and functional versatility. The class of periplasmic binding proteins (PBPs) offers an opportunity to interrogate one of the main processes driving diversification: the duplication and fusion of protein sequences to generate new architectures. The symmetry of their two-lobed topology, their mechanism of binding, and the organization of their operon structure led to the hypothesis that PBPs arose through a duplication and fusion event of a single common ancestor. To investigate this claim, we set out to reverse the evolutionary process and recreate the structural equivalent of a single-lobed progenitor using ribose-binding protein (RBP) as our model. We found that this modern PBP can be deconstructed into its lobes, producing two proteins that represent possible progenitor halves. The isolated halves of RBP are well folded and monomeric proteins, albeit with a lower thermostability, and do not retain the original binding function. However, the two entities readily form a heterodimer in vitro and in-cell. The X-ray structure of the heterodimer closely resembles the parental protein. Moreover, the binding function is fully regained upon formation of the heterodimer with a ligand affinity similar to that observed in the modern RBP. This highlights how a duplication event could have given rise to a stable and functional PBP-like fold and provides insights into how more complex functional structures can evolve from simpler molecular components.

biochemistry↗

bioRxiv2022

A deep unsupervised language model for protein design

Protein design aims to build new proteins from scratch thereby holding the potential to tackle many environmental and biomedical problems. Recent progress in the field of natural language processing (NLP) has enabled the implementation of ever-growing language models capable of understanding and generating text with human-like capabilities. Given the many similarities between human languages and protein sequences, the use of NLP models offers itself for predictive tasks in protein research. Motivated by the evident success of generative Transformer-based language models such as the GPT-x series, we developed ProtGPT2, a language model trained on protein space that generates de novo protein sequences that follow the principles of natural ones. In particular, the generated proteins display amino acid propensities which resemble natural proteins. Disorder and secondary structure prediction indicate that 88% of ProtGPT2-generated proteins are globular, in line with natural sequences. Sensitive sequence searches in protein databases show that ProtGPT2 sequences are distantly related to natural ones, and similarity networks further demonstrate that ProtGPT2 is sampling unexplored regions of protein space. AlphaFold prediction of ProtGPT2-sequences yielded well-folded non-idealized structures with embodiments as well as large loops and revealed new topologies not captured in current structure databases. ProtGPT2 has learned to speak the protein language. It has the potential to generate de novo proteins in a high throughput fashion in a matter of seconds. The model is easy-to-use and freely available.

bioinformatics↗

bioRxiv2022

ATLIGATOR: Editing protein interactions with an atlas-based approach

MotivationRecognition of specific molecules by proteins is a fundamental cellular mechanism and relevant for many applications. Being able to modify binding is a key interest and can be achieved by repurposing established interaction motifs. We were specifically interested in a methodology for the design of peptide binding modules. By leveraging interaction data from known protein structures, we plan to accelerate the design of novel protein or peptide binders. ResultsWe developed ATLIGATOR - a computational method to support the analysis and design of a proteins interaction with a single side chain. Our program enables the building of interaction atlases based on structures from the PDB. From these atlases pocket definitions are extracted that can be searched for frequent interactions. These searches can reveal similarities in unrelated proteins as we show here for one example. Such frequent interactions can then be grafted onto a new protein scaffold as a starting point of the design process. The ATLIGATOR tool is made accessible through a python API as well as a CLI with python scripts. Availability and ImplementationSource code can be downloaded at github (https://www.github.com/Hoecker-Lab/atligator), installed from PyPI ("atligator") and is implemented in Python 3.

bioinformatics↗

bioRxiv2020

Extension of a de novo TIM barrel with a rationally designed secondary structure element

The ability to construct novel enzymes is a major aim in de novo protein design. A popular enzyme fold for design attempts is the TIM barrel. This fold is a common topology for enzymes and can harbor many diverse reactions. The recently published de novo design of a four-fold symmetric TIM barrel provides a well understood minimal scaffold for potential enzyme designs. Here we explore opportunities to extend and diversify this scaffold by adding a short de novo helix on top of the barrel. Due to the size of the protein we developed a design pipeline based on computational ab initio folding that solves a less complex sub-problem focused around the helix and its vicinity and adapt it to the entire protein. We provide biochemical characterization and a high-resolution X-ray structure for one variant and compare it to our design model. The successful extension of this robust TIM-barrel scaffold opens opportunities to diversify it towards more pocket like arrangements and as such can be considered a building block for future design of binding or catalytic sites.

biochemistry↗

bioRxiv2020

Epistasis on the stability landscape of de novo TIM barrels explored by a modular design approach

The ability to design stable proteins with custom-made functions is a major goal in biochemistry with practical relevance for our environment and society. High conformational stability lowers protein sensitivity to mutations and changes in the environment; thus, understanding and manipulating protein stability will expand the applications of de novo proteins. Since the ({beta}/)8-barrel or TIM-barrel fold is one of the most common functional scaffolds, in this work we designed a collection of stable de novo TIM barrels (DeNovoTIMs), using a computational fixed-backbone and modular approach based on improved hydrophobic packing of sTIM11, the first validated de novo TIM barrel. DeNovoTIMs navigate a region of the stability landscape previously uncharted by natural TIM barrels, with variations spanning 60 degrees in melting temperature and 22 kcal per mol in conformational stability throughout the designs. Significant non-additive or epistatic effects were observed when stabilizing mutations from different regions of the barrel were combined. The molecular basis of epistasis in DeNovoTIMs appears to be related to the extension of the hydrophobic cores. This study is an important step towards the fine-tuned modulation of protein stability by design. Significance StatementDe novo protein design expands our knowledge about protein structure and stability. The TIM barrel is a highly relevant fold used in nature to host a rich variety of catalytic functions. Here, we follow a modular approach to design and characterize a collection of de novo TIM barrels and subjected them to a thorough folding analysis. Non-additive effects modulate the increase in stability when different regions of the barrel are mutated, showing a wide variety of thermodynamic properties that allow them to navigate an unexplored region of the stability landscape found in natural TIM barrels. The design of stable proteins increases the applicability of de novo proteins and provides crucial information on the molecular determinants that modulate structure and stability. One Sentence SummaryA family of designed TIM barrels with diverse thermodynamic properties shows epistatic effects on its stability landscape.

biochemistry↗