Hydrolytic haloalkane dehalogenase enzymes catalyze an SN2 nucleophilic substitution to erase halogen substituents in organohalogen compounds. The acid-base-nucleophile triad secures irreversible SN2 displacement of the halogen for the hydroxyl derived from the water. Catalysis relies on the protonatable imidazole ring of the histidine base, and its substitution with an asparagine traps the enzyme in a covalently bound intermediate state, a principle exploited in the widely used HaloTag technology. By contrast, the histidine-to-phenylalanine substitution triggers reversibility of the SN2 reaction, but the molecular trick by which it reprograms the catalytic pathway remains unknown. Here, we show that the phenylalanine at the site of the histidine base spatially disturbs the adjacent residues, leading to the remodeling of surrounding active-site loops. Consequently, rerouting the access tunnels imparts distinctive kinetic behavior featuring a reversible SN2 chemical step that facilitates transhalogenation reactions. This information is crucial for engineering next-generation biocatalysts for sustainable chemistry.

Cardiovascular diseases, including ischemic stroke, necessitate improved thrombolytic agents. A microbe-encoded plasminogen activator staphylokinase (SAK) is a promising alternative to the widely used tissue plasminogen activator (tPA) due to its high fibrin specificity and low production cost. To overcome potential immunogenicity hampering its use in clinical settings, the low-immunogenic variants SAK SY155 and SAK THR174 were previously engineered. However, the molecular basis underlying their reduced immunogenicity is not understood and requires detailed elucidation. Here, we determine molecular structures and compare flexibility between low-immunogenic and immunogenic SAK variants, using a combination of experimental and computational structural techniques. Our analyses show that all variants share the canonical SAK fold and retain similar plasminogen activation kinetics, despite the number of introduced substitutions. Crucially, the low-immunogenic variants exhibit distinct flexibility profiles, with SAK THR174 showing substantially increased flexibility in the H1 helix and B3 region. SAK SY155 exhibits an increased flexibility in the H1-B3 loop and propensity to homodimerize. These flexibility changes are found in the known immunogenic epitopes. Our multi-scale flexibility analysis provides the molecular explanation for the reduced immunogenicity, altered thermostability, and retained fibrinolytic function of the engineered variants. This information is critical for the design of next-generation thrombolytics. ### Competing Interest Statement The authors have declared no competing interest. Czech Science Foundation, https://ror.org/01pv73b02, GX25-17329X, 25-18233M

Salidroside (SAL) is the active ingredient of the traditional adaptogenic herb Rhodiola rosea. Cytochromes P450 (P450), crucial enzymes in drug metabolism, are central to understanding drug–herb interactions. This study investigates the impact of SAL on the metabolic activity of selected P450 in both rat and human systems. Wistar rats were administered intragastrically with SAL 5, 15, or 45 mg/kg/day for seven days. The metabolic activity of CYP1A2, CYP2C6, CYP2D, and CYP3A was measured in rat liver microsomes (RLMs). Amounts and gene expressions of CYP1A2 and CYP2C6 were assessed in RLMs using Western blot and two-step qRT-PCR. rPXR, hPXR, and CAR3 gene reporter assays were conducted. The in vitro inhibitory studies of SAL in both drug-naïve rat and human liver microsomes were performed. Interactions between SAL and human P450 were also studied by in silico methods. SAL at the dose of 5 mg/kg/day slightly increased the specific activity of the P450 studied. However, SAL did not change either the P450 protein levels or the expression of the corresponding genes in rat liver. It also did not cause direct inhibition of rat and human P450 in liver microsomes in vitro. Molecular docking with human P450 confirmed these findings. Moreover, SAL inhibited the agonist-mediated induction of both rat and human PXR. Based on our findings, SAL is unlikely to pose a significant risk of P450-mediated drug-herb interactions and rather preserves the constitutional CYP3A metabolic activity via interaction with PXR. Not applicable.

Scientific progress has historically depended on collaboration. For the first time, some collaborators may be non-human. Multi-agent artificial intelligence (AI) systems operate as teams of specialised digital scientists addressing shared challenges. Instead of relying on a single model, these systems integrate multiple AI agents, each assigned distinct roles, perspectives, or reasoning strategies. Agents generate proposals, critique one another’s suggestions, and iteratively refine solutions through both collaboration and competition. Advancement arises from the interaction of diverse viewpoints and the exchange of ideas, rather than from a single insight.

Abstract Molecular dynamics simulations provide atomistic views of protein motions, but conventional analyses often struggle with extracting subtle mechanistic insights from complex trajectories. Here, we present an integrated framework, ProtXAI, combining molecular dynamics and explainable artificial intelligence (XAI), to identify residue-level determinants of conformational change across diverse protein systems. By leveraging inter-residue distance dynamics, deep learning, and sequential relevance propagation, the approach captures both local fluctuations and long-range communication pathways within protein structures. We applied this framework to three mechanistically distinct systems: apolipoprotein E4 (ApoE4), staphylokinase (SAK) variants, and an ancestral luciferase. Across these applications, our XAI-based approach recovered experimentally supported dynamic hotspots: ligand-responsive hinges in ApoE4, mutation-dependent flexibility shifts in SAK, and evolutionary redistribution of motions in the luciferase. ProtXAI also revealed additional long-range couplings not accessible to classical analysis. Together, these findings demonstrate that combining molecular dynamics with XAI provides a general and scalable strategy for dissecting protein dynamics and uncovering structural determinants of function, stability, and evolutionary changes without prior bias. This approach thus advances the current methodological repertoire for analysing proteins and their intrinsic properties. Highlights Molecular dynamics simulations are increasingly accessible, yet scalable tools for comparative analysis remain limited. We demonstrate that machine learning coupled with explainable AI can automatically extract structural determinants of protein dynamics from trajectories. ProtXAI identifies key dynamic regions across diverse scenarios, including comparison of protein variants, understanding ligand modulation, and single-trajectory analysis. ProtXAI enables scalable, unbiased interpretation of long trajectories, providing an alternative to manual, time-intensive analysis.

Bioanalytical methods targeting adverse cellular outcomes are increasingly used in environmental toxicology, including receptor-mediated toxicity pathways relevant to high-throughput monitoring of drinking water, wastewater, and other environmental samples. However, despite their increasing regulatory acceptance, the representativeness of human tissue-derived bioassays for assessing toxicity toward aquatic species remains uncertain. Given these circumstances, this data article presents molecular docking and sequence-alignment datasets generated to compare human and zebrafish receptor/sensor variants associated with the oxidative stress response (Keap1/Nrf2) and xenobiotic metabolism (AhR/ARNT) pathways. The dataset includes docking data for hKeap1, zfKeap1a, and zfKeap1b, as well as hAhR, zfAhR1a, zfAhR1b, and zfAhR2 receptor/sensor variants, with selected reference ligands and environmental pollutants.Receptor/sensor protein structures derived from AlphaFold predictions, X-ray crystallography, or cryo-electron microscopy were retrieved, prepared, and refined for molecular docking. Ligand structures included the reference agonists tetrachlorodibenzodioxin and tert-butylhydroquinone, as well as the environmental pollutants climbazole, daidzein, thiabendazole, and metazachlor. Docking was performed using AutoDock Vina, generating the best-energy poses for each ligand-protein pair within defined docking grids. AlphaFold-predicted structures were evaluated by parallel docking into available partial X-ray crystal structures of the corresponding variants. For Keap1 variants, blind and site-directed docking approaches were applied, including grids covering reactive cysteine-associated binding regions, and potential effects of Keap1 dimerisation were considered. For AhR variants, docking focused on the PAS-B ligand-binding domain. Protein sequence alignment was conducted using the ClustalW algorithm to compare human and zebrafish receptor/sensor variants and support cross-species comparison of docking outputs.The dataset comprises prepared protein and ligand files, representative docking poses, binding-affinity outputs, and sequence-alignment data. These files provide reusable input and output material for comparative toxicology, cross-species extrapolation, receptor-ligand interaction assessment, and benchmarking of molecular docking workflows. The data may inform scientists and regulators interested in molecular initiating events, toxicity-pathway conservation, and interspecies differences in receptor-mediated responses. This data article complements a related research article (please add link after parallel review process) by providing supporting docking data, receptor/sensor variant sequence-alignments, and quality-assurance procedures for the molecular docking workflow.

Staphylokinase (SAK) is a highly fibrin-specific plasminogen activator with significant potential as a safe and affordable thrombolytic. Yet, its clinical translation can be limited by potential immunogenicity. To accelerate the development of improved thrombolytics, a critical step is identifying the most suitable molecular template. Therefore, we performed a comparative analysis of biochemical and immunological properties of three engineered low-immunogenic variants (SAK SY155, SAK THR174, and SAK STAR FRIDA) and two wild-types (SAK STAR and SAK 42D), using a newly established panel of assays. All variants retained potent thrombolytic activity, with SAK SY155 displaying the highest catalytic efficiency and fibrin-clot permeability. However, this advantage did not fully translate into improved clot reduction under flow conditions. Comprehensive immunological profiling, including monocyte activation, T lymphocyte proliferation, dendritic cell maturation, and mouse immunization models, revealed no strong immunogenic response in any tested variant. Overall, low-immunogenic SAK SY155 and its background wild-type SAK STAR emerged as the most promising templates for rational engineering of next-generation thrombolytics. ### Competing Interest Statement The authors have declared no competing interest. European Union’s Horizon 2020, 857560 Horizon Europe Framework programme, 101136607 the Czech Grant Agency the Czech Health Research Council, NW24-08-00064 the Ministry of Education, Youth and Sports of the Czech Republic, 90254, LM2023055, LM2023069

Abstract The identification of aggregation-prone regions in proteins and their suppression through mutations is a powerful strategy to enhance protein solubility and yield, significantly expanding their potential applications. Here, we developed and experimentally validated a deep neural network-based predictor, AggreProt, that generates a residue-level aggregation profile for protein sequences. The model outperformed or matched current state-of-the-art algorithms, as validated on two independent datasets comprising hexapeptides and full-length proteins with annotated aggregation-prone regions. Importantly, we validated the model experimentally using a set of 34 hexapeptides identified in the model protein haloalkane dehalogenase LinB, along with seven proteins from the AmyPro database. Experimental results agreed with our predictions in 79% of cases and revealed inaccuracies in some database annotations. Finally, the algorithm’s utility was demonstrated by identifying aggregation-prone regions in the LinB enzyme and designing mutations to suppress aggregation in its exposed regions. The resulting variants exhibited reduced aggregation propensity, improved solubility, and up to a 100% increase in yield compared to the wild type. AggreProt is freely available to the scientific community via a user-friendly web server: https://loschmidt.chemi.muni.cz/aggreprot .

Evolution-guided protein design remains one of the most effective strategies for engineering proteins with enhanced stability, activity, or specificity. To make these approaches more accessible, we previously developed FireProtASR-a fully automated pipeline for ancestral sequence reconstruction (ASR). Here, we present FireProtASR 2.0, a significantly enhanced version that extends the design space beyond ancestral inference by integrating a successor sequence predictor (SSP) and a generative model based on variational autoencoders (VAEs). These new modules enable both 'prospective' and 'retrospective' evolutionary design strategies. The SSP module predicts likely future mutations based on site-wise evolutionary trends, and the method was previously validated through in silico benchmarks, demonstrating improvements in thermostability and activity. The VAE module captures global evolutionary constraints in a low-dimensional latent space, from which novel functional ancestral-like variants can be sampled. The VAE-based design strategy was previously validated experimentally on the haloalkane dehalogenase family, yielding variants with enhanced thermostability while maintaining catalytic activity. Both these modules are newly available in FireProtASR in a fully automated pipeline, guiding the users via an interactive graphical user interface. With expanded functionality, modernized user interface, and a more robust backend, FireProtASR 2.0 provides a comprehensive, accessible, and fully automated platform for evolutionary-based protein engineering (https://loschmidt.chemi.muni.cz/fireprotasr/).

Enhancing enzymes to improve desired properties remains an expensive and time-consuming process. Scanning databases of known protein sequences to find enzymes with similar catalytic activity and enhanced properties is an efficient and valuable approach. The EnzymeMiner web server has proven integral as an automated, user-friendly tool that identifies enzymes with the desired catalytic activity from provided sequences and essential residues. Here, we introduce EnzymeMiner 2.0 that builds upon its predecessor, retaining its original functionality, while introducing several key improvements: (i) significantly expanded searched protein space; (ii) annotation of discovered sequences with predictions of the melting temperature, optimal pH, catalytic activity and efficiency, and aggregation propensity with state-of-the-art computational tools; and (iii) smart automatic sequence prioritization and filtering based on user-defined goals or a set of predefined scenarios. With all these enhancements, EnzymeMiner 2.0 aims to remain among the leading solutions for efficient discovery of novel enzymes. The server is freely accessible at https://loschmidt.chemi.muni.cz/enzymeminer/.

Apolipoprotein E4 (ApoE4) is a major genetic risk factor in many neurodegenerative diseases, yet effective therapeutic strategies targeting its associated pathologies remain unresolved. The aggregation of ApoE4, a key pathological feature, is modulated by tramiprosate and its metabolite 3-sulfopropanoic acid. In this study, we provide mechanistic insights into how taurine, a close chemical analogue of tramiprosate, interacts with ApoE4 and may similarly modulate its aggregation behavior. Using an integrated approach, which included molecular dynamics simulations, static light scattering, mass spectrometry, and cerebral organoid models, we investigated the effects of taurine on ApoE4 aggregation. Our results indicate that taurine effectively prevents ApoE4 aggregation and exerts a partial disaggregating effect on pre-formed aggregates. Notably, taurine modulates molecular and cellular features associated with the ApoE4 isoform, shifting them toward patterns observed in the more benign ApoE3 isoform. These observations are consistent with effects similar to those reported for tramiprosate and 3-sulfopropanoic acid and suggest that taurine influences ApoE4-related molecular mechanisms, particularly in the context of the high-risk ApoE4/E4 genotype.

Abstract The nonradiative transport of electronic excitation from one chromophore to another, known as resonance energy transfer, lies at the root of photochemical processes in biology. 1,2 Unlike photosynthesis, bioluminescence converts chemical energy into light through an enzymatic oxygenation of an energy-rich luciferin. 3–5 In glowing cnidarians, the energy is relocated from an excited oxyluciferin to a fluorescent protein, shifting the colour and enhancing the quantum yield of a photogenic reaction. 6,7 How protein-chromophore complexes assemble during this interplay in real space, and what this association entails for function, are unknown. Here, we report co-crystal structures of a 120-kilodalton energy-transfer complex from the luminescent soft coral Renilla reniformis . We find a heterotetrameric 2:2 assembly composed of two coelenteramide-loaded luciferases (RrLuc) docked at opposite sides of a head-to-tail dimer of green fluorescent protein (RrGFP). The edge-to-edge distance between donor and acceptor chromophores is below 3 nm, favouring the Förster-type radiationless energy transfer. Furthermore, RrGFP serves not only as a colour-switchable antenna and luminescence amplifier but also tunes the efficiency of luciferase catalysis by controlling its inherent dynamics. Our results provide detailed spatial information about intermolecular dipole-dipole coupling in Renilla bioluminescence, including the arrangement of donor-acceptor pairs that secure excited-state energy transfer with exquisite precision.

Thermostable proteins are crucial in numerous biomedical and biotechnological applications. However, naturally occurring proteins have evolved to function in mild conditions, and laboratory experiments aiming at improving protein stability have proven laborious and expensive. Computational methods overcome this issue by providing a cheap and scalable alternative. Despite significant progress, their reliability is still hindered by the availability of high-quality data. FireProtDB 2.0 (http://loschmidt.chemi.muni.cz/fireprotdb) is a large-scale database aggregating stability data from multiple sources. The second version builds upon its predecessor, retaining its original functionality while introducing a new approach to data storage and maintenance. The new scheme enables the introduction of both absolute and relative data types connected with measurements of wild-types, mutants, protein domains, and de novo designed proteins. Furthermore, while the original database was limited to single-point mutations, more complex data such as insertions, deletions, and multiple-point mutations are now available. As a result, the inclusion of large-scale mutagenesis has increased the size of the database from 16 000 to almost 5 500 000 experiments. Moreover, the updated abstract scheme is fully expandable with any new measurements and annotations without the need for any restructuring. Finally, the tracking of history together with fixed identifiers is in accordance with the FAIR principles.

Holistic protection goals in environmental hazard and risk assessment, complex pollutant mixtures, and limitations in targeted chemical analysis highlight the need for robust, mechanistically informative bioanalytics to support water quality monitoring. Given the scarcity of high-throughput, non-mammalian in vitro effect-based methods, this study evaluates the suitability of mammalian models as surrogates for aquatic species by investigating interspecies differences in the activation of oxidative stress (Nrf2/Keap1/ARE) and xenobiotic metabolism (AhR/ARNT/XRE) pathways quantified with cellular reporter gene assays. Wastewater treatment plant influent and effluent samples, alongside reference compounds, were analysed in human, mouse, and zebrafish reporter assays. Bioanalytics were complemented by in silico-mediated effect-directed analysis, iceberg-, molecular docking-, and chemical bioavailability-modelling. For Nrf2/Keap1/ARE, high concordance in reporter activity across species was observed in response to environmental samples, whereas the reference compound tert-butylhydroquinone elicited species-/assay-specific differences due to varying ligand affinities for the Keap1 redox sensor. In contrast, metazachlor exposure resulted in conserved activation patterns across species. For AhR/ARNT/XRE, interspecies variability in bioactivity was observed across environmental samples and the reference compound 2,3,7,8-tetrachlorodibenzodioxin, yielding divergent bioequivalent concentration estimates. In silico-mediated effect-directed analysis identified climbazole, daidzein, and thiabendazole as principal aryl hydrocarbon receptor activators, which also displayed species-/assay-specific activity under isolated exposure. Molecular docking confirmed species-dependent receptor-ligand affinities, while bioavailability modelling excluded differential cellular uptake, supporting receptor-mediated mechanisms as key drivers. Collectively, mammalian reporter assays can approximate oxidative stress responses in aquatic species, but limitations remain for xenobiotic metabolism, highlighting the need for species-representative assays and caution when contextually interpreting data from mammalian systems.

The α/β-hydrolase (ABH) superfamily is a widespread and functionally versatile protein fold recognized for its ability to adapt to diverse molecular functions across all three domains of life. One such spectacular example of evolutionary adaptation at the ABH fold is an acquisition of oxygenolytic luciferase reaction that occurred within the hydrolytic haloalkane dehalogenase family. The molecular details of this evolution remain puzzling. In this work, we determine crystal structures and explore dynamical behaviour of a bifunctional ancestral ABH-fold enzyme, highlighting molecular features associated with the transition from hydrolytic to oxygenolytic catalysis at this fold. Structures showed a canonical αβα-sandwich shielded with a helical cap domain. The catalytic pocket is voluminous enough to accommodate a bulky substrate. Molecular dynamics simulations demonstrated that coelenterazine entry does not present a major energetic barrier and identified a preferred binding orientation important for oxygenolytic catalysis. Comparisons between ancestral and extant enzymes highlighted specific amino acids and sequence motifs characteristic for oxygenolytic luciferases. Collectively, our results provide an expanded view of the evolutionary transition in which ABH-fold enzymes, originally using water to cleave chemical bonds, adapted to utilize dioxygen for bioluminescence.

Retinoic acid (RA), a vitamin A metabolite, plays a crucial and evolutionarily conserved role in vertebrate development. Chemical disruption of retinoid signaling can severely affect organisms; yet, despite its teratogenicity and pathway interactions, this disruption remains understudied. Increasing research aims to address these gaps by developing comprehensive frameworks like Adverse Outcome Pathways (AOPs). This study refines a previously proposed AOP network on retinoid-induced teratogenicity by: (1) empirically confirming overactivation of the Retinoic Acid Receptor (RAR)/Retinoid X Receptor (RXR) heterodimer as the molecular initiating event (MIE), through morphological rescue of 5 dpf zebrafish co-exposed to all-trans Retinoic Acid (ATRA), a RAR ligand, and either BMS493 (RAR inverse agonist) or UVI3003 (RXR antagonist); (2) Identifying the window of sensitivity for MIE through time-stage co-exposure (4-24, 4-48, 4-72, and 4-120 hpf); (3) integrating key molecular and cellular events from existing knowledge. The study also brings new knowledge on how RXR signaling disruption contributes to RA and Thyroid Hormone (TH) signaling disruption using in vitro reporter assays and in vivo morphological endpoints. Results show that BMS493 and, unexpectedly, diclazuril (pesticide identified as a thyroid hormone receptor antagonist in vitro) inhibit Retinoic Acid Response Element (RARE) activity in vitro. UVI3003-ATRA co-exposure induced additive effect on RARE activity. UVI3003-TH co-exposure inhibited Thyroid Hormone Response Element activity. In zebrafish, co-exposure of ATRA with BMS493 or diclazuril rescued ATRA-induced malformations, i.e., craniofacial and tail malformations, and microphthalmia - confirming RAR/RXR overactivation as MIE. It also rescued posterior swim bladder inflation and retinal layer defects -revealing novel role for RAR/RXR in these phenotypes. Additionally, UVI3003-ATRA co-exposure increased zebrafish embryos mortality, and UVI3003 alone increased fluorescence expressed in thyrocytes of thyroglobulin-mCherry zebrafish. Altogether, these findings reveal RXR's involvement in endocrine crosstalk and highlight the critical role of retinoid signaling in developmental toxicity and the need for its inclusion in hazard assessment.

Modern computational tools can predict the mutational effects on protein stability, sometimes at the expense of activity or solubility. Here, we investigate two homologous computationally stabilized haloalkane dehalogenases: (i) the soluble thermostable DhaA115 (Tmapp = 74 °C) and (ii) the poorly soluble and aggregating thermostable LinB116 (Tmapp = 65 °C), together with their respective wild-type variants. The intriguing difference in the solubility of these highly homologous proteins has remained unexplained for three decades. We combined experimental and in-silico techniques and examined the effects of stabilization on solubility and aggregation propensity. A detailed analysis of the unfolding mechanisms in the context of aggregation explained the negative consequences of stabilization observed in LinB116. With the aid of molecular dynamics simulations, we identified regions exposed during the unfolding of LinB116 that were later found to exhibit aggregation propensity. Our analysis identified cryptic aggregation-prone regions and increased surface hydrophobicity as key factors contributing to the reduced solubility of LinB116. This study reveals novel molecular mechanisms of unfolding for hyperstabilized dehalogenases and highlights the importance of contextual information in protein engineering to avoid the negative effects of stabilizing mutations on protein solubility.

Engineering protein dynamics is a challenging and unsolved problem in protein design. Loop transplantation or loop grafting has been previously employed to transfer dynamic properties between proteins. We recently released a LoopGrafter Web server to execute the loop grafting task, employing eight computational tools and one database. The LoopGrafter method relies on the prediction of the local dynamic behavior of the elements to be transplanted and has successfully reconstructed previously engineered sequences. However, it was unclear whether catalytically competitive previously uncharacterized designs could be obtained by this method. Here, we address this question, showing how LoopGrafter generates viable loop-grafted chimeras of luciferases, how these chimeras encompass the activity of interest and unique kinetic properties, and how all this process is done fully automatically and agnostic of any previous knowledge. All constructed designs proved to be catalytically active, and the most active one improved the activity of the template enzyme by 4 orders of magnitude. The computational details and parameter optimization of the sequence pairing step of the LoopGrafter workflow are revealed. The optimized and experimentally validated loop grafting workflow available as a fully automated Web server represents a powerful approach for engineering catalytically efficient enzymes by modification of protein dynamics.

Tailoring natural enzymes to synthetic needs is often associated with high costs and long timelines, hindering the broader adoption of biocatalysis in the chemical and pharmaceutical industries. To address this, we developed the RISE (rapid in vitro semi-rational engineering) workflow that makes enzyme engineering accessible to chemistry laboratories. RISE integrates four key concepts: computational design of focused variant libraries, rapid generation of linear mutant DNA libraries via PCR, cell-free protein synthesis from linear template DNA, and iterative cycles of mutagenesis, expression, and testing to accumulate beneficial mutations. In a proof-of-concept study, we engineered a ketimine reductase from Rattus norvegicus (RnKIRED), achieving stereoselectivity inversion in one reductive amination reaction and a 400-fold activity improvement in another. These engineered variants enabled the gram-scale synthesis of key intermediates for ACE2 inhibitor drugs. RISE bridges the gap between inefficient wild-type enzymes and expensive directed evolution, promoting biocatalysis implementation in early chemical development.