The clinical urgency is difficult to overstate. H. pylori infects a large proportion of the global population and is firmly linked to chronic active gastritis, peptic ulcer disease, gastric mucosal atrophy, intestinal metaplasia, and gastric adenocarcinoma. Prospective cohort evidence has connected infection to subsequent gastric cancer development, and meta-analytic data indicate that eradication therapy can reduce cancer risk in appropriate populations. The Kyoto global consensus went so far as to define H. pylori gastritis as an infectious disease that should be diagnosed and treated wherever detected. Yet the therapeutic arsenal is weakening. The Maastricht VI/Florence Consensus Report urges clinicians to tailor regimens to local resistance patterns and prior antibiotic exposure, while the 2024 American College of Gastroenterology guideline now advises against empirical clarithromycin triple therapy unless susceptibility has been confirmed, recommending 14-day optimized bismuth quadruple therapy as the default empirical option when susceptibility is unknown.

Into this resistant landscape, the study’s authors introduce a deliberately small and transparent computational experiment. They selected three targets representing complementary biological functions: H. pylori urease, the nickel-dependent virulence enzyme that allows the bacterium to survive gastric acid by hydrolyzing urea; DNA gyrase subunit A, essential for DNA topology and replication; and shikimate kinase, part of a biosynthetic pathway present in many microorganisms and plants but absent from humans. Crystallographic structures from the Protein Data Bank served for urease (PDB 1E9Y, with its nickel-containing architecture carefully preserved) and shikimate kinase (PDB 1ZUH), while DNA gyrase A was represented by an AlphaFold model because a suitable experimental structure for blind docking was unavailable. Ligands were docked blindly using CB-Dock2, an automated server combining cavity detection with Vina-type scoring, and the resulting poses were inspected in three dimensions and mapped residue-by-residue in two-dimensional diagrams.

The choice of ligands was grounded in prior experimental data rather than computational convenience. Niclosamide, a salicylanilide anthelmintic long used against tapeworms, had already demonstrated striking anti-H. pylori activity in vitro: it inhibited strain 60190 with a minimum inhibitory concentration of 0.25 micrograms per milliliter, remained active at acidic pH, showed partial synergy with metronidazole and proton pump inhibitors, reduced bacterial adhesion and invasion of gastric epithelial cells by roughly 3 log CFU, and produced no detectable resistance after prolonged exposure in a Galleria mellonella infection model. Berberine, a quaternary ammonium alkaloid from plants such as Berberis species, carries clinical credentials of its own. A randomized phase IV trial found that a 14-day quadruple regimen containing berberine achieved eradication rates of 90.1 percent by intention-to-treat and 91.3 percent per protocol, non-inferior to a bismuth-containing regimen, and a later meta-analysis reported that adding berberine to standard triple therapy improved eradication with a risk ratio of 1.22.

The docking results positioned both candidates favorably. Against urease, niclosamide and berberine tied for the most negative score at –8.5 kcal/mol, outperforming levofloxacin’s –7.9 kcal/mol. Berberine again led against DNA gyrase A at –8.5 kcal/mol, ahead of niclosamide at –7.8 and levofloxacin at –7.5 kcal/mol. Shikimate kinase proved the least favorable target overall, with berberine at –7.3, levofloxacin at –7.0, and niclosamide at –6.9 kcal/mol. Across all three targets, berberine posted the most negative descriptive mean score at –8.10 ± 0.69 kcal/mol, compared with –7.73 ± 0.80 for niclosamide and –7.47 ± 0.45 for levofloxacin. The authors are categorical that these Vina-type outputs are ranking scores only, not binding free energies or affinity constants; a favorable docked score can occur even for a compound that fails to bind in solution.

Perhaps the most technically instructive finding emerged from the two-dimensional interaction maps: identical scores can mask entirely different binding modes. At urease, where niclosamide and berberine shared the same –8.5 kcal/mol value, their predicted stabilization patterns diverged sharply. Berberine’s pose relied mainly on pi-alkyl, pi-sigma, and hydrophobic contacts with residues including LEU A:13, ALA A:16, VAL A:33, PHE B:441, and TYR A:32, while niclosamide’s pose combined conventional hydrogen bonds with hydrophobic, pi-related, and van der Waals contacts involving VAL B:473, TYR B:475, PRO B:472, and MET A:12. At DNA gyrase A, berberine’s aromatic contacts with PHE A:549 and TYR A:525 drove its top ranking, whereas levofloxacin interacted with ASP A:91, ARG A:95, and GLN A:98, including one unfavorable positive-positive contact. The authors caution, however, that the isolated DNA gyrase A model cannot reproduce the DNA–enzyme–drug ternary complex on which fluoroquinolone pharmacodynamics actually depends.

The ADMET profiling added a sobering pharmacokinetic dimension. All three compounds showed zero Lipinski rule-of-five violations and identical bioavailability scores of 0.55, with high predicted gastrointestinal absorption, but their developability profiles differ meaningfully. Niclosamide’s consensus logP of 3.78 and topological polar surface area of 49.33 square angstroms predict membrane permeability, yet its poor aqueous solubility makes formulation-oriented work essential. Berberine’s permanent quaternary cationic structure, which was preserved in the docking preparation, is associated with complex, formulation-dependent exposure that demands experimental confirmation. Neither descriptor set, the study emphasizes, constitutes evidence of therapeutic suitability; they flag questions about exposure, solubility, and formulation that only laboratory measurement can resolve.

The methodological self-awareness sets this study apart from much of the computational drug-repurposing literature. The authors explicitly note that no redocking validation, receiver operating characteristic benchmarking, molecular dynamics simulations, or MM/GBSA or MM/PBSA free-energy analyses were performed, meaning pose accuracy and screening enrichment cannot be claimed. Alternative protonation and tautomeric states of the ligands were not systematically enumerated, a constraint that can influence both poses and scores. Thermodynamically, they explain, a docking score approximates none of the free-state, solvation, desolvation, and entropic contributions required for a true binding free energy, and virtual screening workflows carry substantial false-positive rates. With only three ligands and three targets, no inferential statistics were applied; all summaries are purely descriptive of this specific matrix.

The study also situates itself honestly within prior evidence. The docking results neither reproduce niclosamide’s previously observed antibacterial effects nor identify their mechanism; instead they generate a separate, target-oriented hypothesis that urease, gyrase, and shikimate kinase engagement could be tested experimentally. Similarly, the mixed clinical record of berberine—a more recent randomized trial found no clear superiority for berberine-containing triple therapy, and reported MIC values against H. pylori vary widely by strain and method—means the alkaloid should be viewed as a scaffold for mechanistic and formulation-focused testing rather than a docking-supported monotherapy. The shikimate kinase results, with their small score differences, are downgraded to a lower-priority experimental hypothesis despite the target’s theoretical selectivity advantage.

What remains is a deliberately restricted but actionable set of next steps. The authors propose urease inhibition assays as the first priority, followed by broth microdilution or agar-dilution MIC determination against reference and clinical H. pylori strains, checkerboard combination testing with standard antibiotics, cytotoxicity screening on gastric epithelial cell models, and, if justified by results, molecular dynamics and post-docking free-energy analyses. Within this framework, berberine earns the most consistent score pattern, niclosamide remains the clearest repurposing candidate for urease-focused testing given its prior experimental pedigree, and levofloxacin serves its role as a clinically interpretable yardstick. None of these outputs demonstrates binding, enzyme inhibition, bacterial killing, or therapeutic efficacy—but as an exercise in reducing the experimental search space before costly microbiological testing, the study offers a model of how computational prioritization can be conducted with the caveats firmly attached.

Subject of Research: Computational docking and ADMET profiling of niclosamide and berberine against Helicobacter pylori urease, DNA gyrase A, and shikimate kinase

Article Title: Comparative molecular docking and ADMET profiling of niclosamide and berberine against multiple Helicobacter pylori enzymatic targets

Article References: Danila, C., Faur, L., Mocan, L., & Cavalu, D. S. (2026). Comparative molecular docking and ADMET profiling of niclosamide and berberine against multiple Helicobacter pylori enzymatic targets. Pharmacia, 73, Article e212118. https://doi.org/10.3897/pharmacia.73.e212118

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e212118

Keywords: Helicobacter pylori, molecular docking, niclosamide, berberine, levofloxacin, ADMET, drug repurposing, urease, DNA gyrase, shikimate kinase, antimicrobial resistance, in silico screening

The researchers assembled a stratified panel of 237 complete bacterial genomes, deliberately chosen to span diverse ecological niches and genome-level characteristics such as size, GC content, and coding capacity. Rather than trusting annotation pipelines alone, they combined annotation-guided screening with profile hidden Markov model searches, a sensitive method for detecting remote protein homologs, and then manually reconstructed each candidate urease locus to confirm its architecture. The panel was then classified into three tiers: genomes with at least one complete urease locus, genomes with candidate but incomplete neighborhoods, and genomes with no supported urease system at all.

The headline numbers are striking in themselves. Of the 237 genomes, 149 encoded at least one complete urease locus, 11 carried candidate but incomplete neighborhoods, and 77 had no detectable urease genes whatsoever. Across the panel, the authors recovered 173 urease-associated genomic neighborhoods. The overwhelming majority, 150 loci, followed the canonical ureABC architecture, in which three structural genes encode the alpha, beta, and gamma subunits that assemble into the active enzyme, typically flanked by accessory genes such as ureD, ureE, ureF, and ureG that shepherd nickel ions into the catalytic center.

Against this conserved backdrop, one alternative design stood out. Seven loci, all confined to Helicobacter, displayed a fused configuration in which the structural genes are arranged as an AB fusion rather than as separate reading frames. This arrangement, best known from the gastric pathogen Helicobacter pylori, persisted in the dataset as a small but stable, lineage-restricted architecture, a reminder that even a deeply conserved enzyme system can tolerate structural tinkering within particular evolutionary branches. Sixteen additional loci were classified as partial or split, highlighting how assembly artifacts, pseudogenization, or genuine decay can blur the boundaries of what counts as a functional urease system.

One of the study’s most intriguing findings concerns genomes that carry two complete canonical urease systems at once. Eight genomes in the panel encoded duplicated loci, and in every case both copies mapped to the same top-level assembly sequence record, ruling out contamination from separate plasmids or unplaced contigs. When the authors compared the two copies within each genome, they found that the paired loci differed in gene order and typically shared only about 62 to 63 percent identity across their concatenated ureABC sequences. That level of divergence is far too deep to reflect a recent, exact duplication. Instead, it points to older internal duplication followed by divergence, or to the secondary acquisition of a second, foreign urease module at some earlier point in the lineage’s history.

To probe how urease systems move across evolutionary distances, the authors built a gene tree from concatenated ureABC sequences and compared it with a genome-wide species tree for the same organisms. If a urease gene tree places a locus next to species that are, by the species tree, only distant relatives, that incongruence is a classic signature of horizontal gene transfer. The comparison flagged 12 candidate incongruent loci, all of them complete canonical systems, marking them as the strongest candidates for intergeneric transfer within the dataset.

Manual inspection of the most compelling examples revealed something ecologically coherent rather than random. Several candidate transfer events clustered in nitrifying bacteria and marine cyanobacteria, two groups for which urea hydrolysis has clear adaptive value: nitrifiers gain a supplemental nitrogen and energy substrate, while ocean-dwelling picocyanobacteria such as Prochlorococcus can exploit urea as a reduced nitrogen source in nutrient-poor waters. In enteric bacteria, the incongruent urease neighborhoods were strikingly associated with nickel transport and hydrogenase-related genes, suggesting that these loci arrived as coordinated functional packages, carrying not just the enzyme but the machinery needed to supply its essential nickel cofactor.

The broader significance of the work lies in its reframing of urease as an evolutionary mosaic. The catalytic core, the ureABC trimer and its nickel metallocenter, is architecturally conserved to a remarkable degree, reflecting the stringent biochemical requirements of activating carbon dioxide and ammonia chemistry with a nickel center. But the surrounding genomic context, including transporters, accessory proteins, and regulatory elements, varies substantially between lineages, tailored to the specific ecological pressures each bacterium faces. The study’s locus-level reconstruction, rather than single-gene screening, is what made this layered picture visible, and the authors argue that future comparative work should treat the entire neighborhood, not just ureC, as the unit of analysis.

The findings also carry practical weight. Urease activity underpins a remarkable range of applications and problems: it drives infection-associated kidney stone formation by Proteus mirabilis, enables H. pylori to survive stomach acid, contributes to ammonia toxicity in ruminant digestion, and powers engineered biomineralization technologies that use ureolytic bacteria to cement sand, seal concrete cracks, and remove heavy metals from water. Understanding which organisms carry which urease architectures, how those systems are regulated by nickel availability, and how readily they move between lineages could sharpen predictions about pathogen virulence, soil nitrogen cycling, and the design of biomineralizing microbial consortia.

As genome databases continue to expand, studies of this kind will only grow more informative. The stratified panel approach used here, combining ecological metadata with rigorous locus reconstruction and species-tree comparison, offers a template for interrogating other multi-gene microbial systems whose distribution may likewise be shaped by a mix of vertical inheritance, duplication, and horizontal exchange. For urease, the message is clear: the enzyme’s blueprint is ancient and shared, but its passport has been stamped many times as it traveled between bacterial genera across evolutionary time.

Subject of Research: Comparative phylogenomics of bacterial urease gene systems across diverse bacterial genomes

Article Title: Comparative phylogenomics of bacterial urease systems reveals architectural conservation, lineage-specific specialization, and candidate horizontal transfer

Article References: Sarkar, M. P., & Pal, A. (2026). Comparative phylogenomics of bacterial urease systems reveals architectural conservation, lineage-specific specialization, and candidate horizontal transfer. Molecular Genetics and Genomics, 301(1), Article 179. https://doi.org/10.1007/s00438-026-02507-y

Image Credits: AI Generated

DOI: 10.1007/s00438-026-02507-y

Keywords: urease, bacteria, phylogenomics, horizontal gene transfer, gene duplication, nickel metalloenzyme, Helicobacter pylori, nitrogen cycling, marine cyanobacteria, nitrifiers, genomics, ureABC

Researchers sampled thirty ponds monthly from June to September 2022, dividing them into four categories: agricultural reservoirs, biologically managed habitat ponds, natural ponds with little anthropogenic influence, and engineered urban stormwater ponds of the kind that now number more than 230 in the city of Ottawa alone. These impoundments are designed to capture runoff, trap sediments and shield downstream ecosystems from floods and pollutants, but they can also become nurseries for unwanted cyanobacteria and the cyanotoxins they produce. The team collected water for physical and chemical analysis, identified phytoplankton communities using FlowCam imaging systems, and quantified land use within a one-kilometer buffer around each pond using provincial land cover databases.

The chemical contrast between pond types was striking. Stormwater ponds had the highest specific conductivity, averaging roughly 1,045 microsiemens per centimeter and peaking above 3,000, a signature of road salt application across their largely impervious urban catchments. Agricultural ponds, by contrast, carried the heaviest nutrient loads, with total phosphorus averaging 0.119 milligrams per liter and total Kjeldahl nitrogen 1.876 milligrams per liter, both significantly higher than in any other pond type. Natural ponds remained consistently low in nutrients, salts and metals, buffered by surrounding soils and forest cover. A regression analysis revealed that roughly half the variation in overall water chemistry across all ponds could be explained simply by the percentage of impervious cover, such as roads and pavement, surrounding each pond.

When the researchers turned to the living communities, they found that phytoplankton assemblages were broadly similar across pond types, a reflection of broad ecological niches and effective dispersal among these small water bodies. But the details mattered. Agricultural and managed ponds hosted more chlorophyte green algae and larger cyanobacteria, while stormwater ponds were dominated by small picoplankton-sized cyanobacteria. Variance partitioning showed that environmental factors alone explained nearly 62 percent of the variation in community composition, with the full model accounting for about 70 percent, whereas land use independent of environment explained under 2 percent and season contributed nothing significant. In other words, it is the chemistry of the water, not the calendar or the map alone, that structures who lives in these ponds.

The study’s most provocative findings emerged from its machine learning analysis. Using classification and regression tree modeling, the team predicted cyanobacterial counts from dozens of chemical and land use variables. The first split in the entire dataset was not phosphorus, not temperature, but extractable nickel. Ponds with nickel concentrations above 0.0029 milligrams per liter harbored cyanobacterial densities nearly three times those of the rest, and these nickel-rich samples came almost exclusively from stormwater and agricultural ponds. Nitrate was the closest competing variable, and water temperature, conductivity and ammonia all ranked prominently in the model’s variable importance scores.

Even more striking was what did not matter. Total phosphorus and reactive phosphorus, long cast as the primary villains of cyanobacterial blooms, ranked only tenth or lower in importance, with importance scores of just 4.7 and 4.3. In these moderately disturbed, pre-bloom systems, the classical paradigm of phosphorus control appeared to loosen. Instead, the data pointed to a tight coupling between nickel and nitrogen metabolism. Cyanobacteria rely on the nickel-dependent enzyme urease to hydrolyze urea into ammonia and carbon dioxide, providing a bioavailable nitrogen source, and the co-occurrence of elevated nickel and ammonia in the CART hotspots is consistent with enhanced urease activity under urban contamination regimes.

The urban provenance of the nickel itself is well documented in the broader literature. Copper and zinc wash from vehicles, brake wear, tires, road surfaces and buildings, while nickel contamination traces to fossil fuel combustion, construction activity and waste disposal. Stormwater ponds, ringed by asphalt and receiving concentrated runoff, accumulate these metals readily, and the study found copper, zinc and nickel positively associated with cyanobacterial concentrations in urban ponds. At the moderate concentrations observed, nickel appears to act as a micronutrient rather than a toxin, though at higher levels it inhibits photosynthesis, promotes reactive oxygen species and can even stimulate toxin production in sensitive species.

Conductivity also emerged as a meaningful predictor, with cyanobacteria strongly associated with specific conductance above 1,184 microsiemens per centimeter, a threshold dominated by stormwater and managed ponds. While salts are generally treated as indirect indicators of landscape runoff rather than direct bloom drivers, the finding echoes earlier work showing that elevated ionic concentrations correlate with cyanobacterial and periphyton abundance in both natural and disturbed systems. Warm summer temperatures, peaking near 24 degrees Celsius in July, amplified the model’s predictive power, consistent with the widely observed synergy between warming and nutrient or contaminant loading.

The study confirmed that cyanobacteria fare disproportionately well in chemically and physically altered systems: the highest concentrations occurred in stormwater and agricultural ponds, while natural ponds, though biologically diverse, hosted the fewest. Although classical surface blooms were not observed during the sampling season, the team documented elevated numbers of potentially harmful taxa, including Microcystis and small coccoid cyanobacteria, in the modified ponds. This pre-bloom state is precisely where early-warning signals matter most, and the authors argue that nickel-mediated nitrogen processing could be an overlooked early driver of eutrophication before blooms become visible.

The practical implications are considerable. Managing cyanobacteria has long focused on curbing point-source phosphorus, capping nitrogen inputs and altering water flows, approaches that are often blunt and only partially effective against diffuse non-point pollution. This research suggests that in constructed ponds, the micronutrient dimension of contamination, and specifically the role of nickel in nitrogen cycling, deserves a place in monitoring and design strategies. As urbanization expands and climate change intensifies runoff, the humble stormwater pond may prove to be both a sentinel and a trigger in the global rise of harmful algal blooms, and the trace metals that trickle off our roads may be quietly shaping which microbes thrive in the waters we build.

Subject of Research: Anthropogenic and environmental factors driving plankton communities and cyanobacteria in constructed ponds and wetlands.

Article Title: Anthropogenic and environmental factors driving planktic community and Cyanobacteria selection in constructed ponds and wetlands

Article References: Schulz, N. A., Hamilton, P. B., Lapen, D., Sunohara, M., & Vermaire, J. C. (2026). Anthropogenic and environmental factors driving planktic community and Cyanobacteria selection in constructed ponds and wetlands. Environmental Advances, 25, Article 100752. https://doi.org/10.1016/j.envadv.2026.100752

Image Credits: AI Generated

DOI: 10.1016/j.envadv.2026.100752

Keywords: cyanobacteria, harmful algal blooms, stormwater ponds, nickel, nitrogen, phosphorus, phytoplankton, urease, urban runoff, water quality, machine learning, constructed wetlands