The research team, led by Sweta Yadav and Puja Khare of CSIR-Central Institute of Medicinal and Aromatic Plants in Lucknow, India, together with colleagues from the Drug Standardization Research Institute, focused on four genotypes of Andrographis paniculata, designated G1, G5, G6, and G11. This species, commonly known as king of bitters, is prized in traditional medicine for its andrographolide content, a compound with documented antiviral and anti-inflammatory properties. Because the plant is cultivated for its leaves, contamination from airborne metals is a direct threat to both productivity and the safety of the final herbal product. The researchers grew or sampled the genotypes at two polluted sites and one control site, then measured a battery of morphological, physiological, and metabolic responses.

The first key finding concerned leaf surface architecture. The two genotypes with rough and wrinkled leaf surfaces, G11 and G5, turned out to be the most vulnerable. Their epidermal cells collapsed more frequently under the burden of deposited dust, and this structural damage translated into reduced growth and higher accumulation of lead, cadmium, and arsenic in their leaves. In contrast, the smoother-leaved genotypes fared considerably better. The result underscores a principle that has emerged from other studies of particulate matter capture in urban trees and crops: microscopic surface texture largely determines how much dust a leaf traps, and trapping more dust is not a sign of health but a pathway to toxicity.

Where the metals ended up inside the leaf proved just as important as how much arrived. Using subcellular fractionation, the team tracked the distribution of toxic metals across cellular compartments, including organelles, cell walls, and soluble fractions. In the G1 genotype, the concentration of toxic metals in organelles and soluble fractions was notably lower than in the other genotypes. This matters because organelles such as chloroplasts and mitochondria are the metabolic powerhouses of the cell, and metals sequestered in vulnerable compartments disrupt photosynthesis and respiration. Genotypes that keep metals out of these sensitive regions, or exclude them altogether, can maintain function even under heavy deposition. G1’s ability to limit internal metal exposure helps explain why it accumulated less metal overall and grew better at both polluted sites.

The metabolic story centered on carbohydrate metabolism, a network of enzymes that governs how plants store and mobilize energy. The researchers measured the activities of sucrose synthase, sucrose phosphate synthase, neutral invertase, and acid invertase, enzymes that together control the synthesis and breakdown of sucrose, the main transport sugar in plants. Their activities varied across genotypes and pollution levels in a pattern the authors describe as a trade-off between energy storage and combating oxidative stress. When dust and its metal payload generate reactive oxygen species, plants must divert energy and reducing power into antioxidant defense, and the sugar-metabolism enzymes reflect this shifting priority. Soluble sugars themselves also act as protective osmolytes and signaling molecules under stress, so their total and reducing fractions provided a readout of each genotype’s metabolic state.

Multivariate statistical analysis tied these threads together. The variation in carbohydrate-metabolism enzymes and sugar pools among the genotypes was linked to the subcellular distribution of the airborne toxic metals. In other words, where a plant stores or excludes its metal burden shapes how its sugar economy responds. Genotypes that confined metals away from metabolic compartments could keep their sucrose-processing machinery running closer to normal, while those with metals invading organelles and soluble fractions showed more distorted enzyme profiles. This connection between metal localization and carbon metabolism offers breeders a potentially measurable marker: enzyme activity patterns or sugar profiles could serve as indicators of a genotype’s tolerance before expensive field trials are complete.

Nitrogen metabolism told a subtler story. The enzyme glutamate dehydrogenase, which participates in ammonia assimilation and amino acid metabolism, increased in activity across all genotypes at the low-polluted site but decreased at the highly polluted site. This dose-dependent response suggests that moderate pollution may trigger a compensatory metabolic push, perhaps to supply amino acids for stress-protein synthesis and antioxidant compounds, whereas severe pollution overwhelms the machinery, depressing nitrogen processing altogether. Nitrogen metabolism is tightly coupled to carbon metabolism, and its collapse under high pollution likely compounds the energy deficits created by damaged photosynthetic tissue, accelerating the growth declines observed in the sensitive genotypes.

The broader context makes these findings timely. Atmospheric deposition of heavy metals is a growing concern for agricultural systems worldwide, with traffic, industry, and coal combustion releasing particles that settle on croplands. Previous work by some of the same team had shown that Andrographis paniculata genotypes differ in their ability to exclude lead and cadmium taken up through roots, and that PM10-bound metals at traffic junctions affect the species’ physiology. The new study extends this picture to the foliar route, showing that the leaf surface itself is a decisive battleground. Research on Chinese cabbage, wheat, soybean, and vegetables has similarly demonstrated that foliar uptake of atmospherically deposited metals can rival or exceed root uptake, making leaf-level traits a legitimate target for crop improvement.

For medicinal plant cultivation, the practical implications are considerable. Selecting genotypes such as G1, which combines lower metal accumulation with higher growth under pollution, could allow farmers near roads or industrial zones to produce safer, more abundant harvests without relocating. The study’s identification of dust assimilation capacity, metabolic adaptability, and subcellular metal localization as the three key factors governing resilience provides a framework for screening other cultivars and even other species. It also feeds into the emerging concept of phyto-exclusion, in which crops are bred or chosen specifically to keep contaminants out of the harvested organs rather than to tolerate them internally, a strategy that directly addresses food and herbal medicine safety.

There remain open questions. The study examined four genotypes at a limited number of sites, and the relative contributions of leaf texture, cuticle chemistry, trichome density, and stomatal behavior to dust capture were not fully disentangled. Long-term experiments will be needed to determine whether the metabolic signatures observed here hold across seasons and pollution gradients, and whether the tolerant G1 genotype maintains its advantageous metal partitioning when grown on contaminated soils as well as under atmospheric exposure. Still, the central message is clear and actionable: resilience to air pollution is written into plant genomes, and understanding that variation, from the leaf surface down to the organelle, is essential for sustainable agriculture in an increasingly dusty and metal-laden atmosphere. As urbanization and industrial activity intensify across the growing regions of Asia and beyond, studies like this one transform air pollution from an unavoidable hazard into a manageable breeding challenge.

Subject of Research: Genotypic variation in morpho-physiological and metabolic responses of Andrographis paniculata to atmospheric dust and heavy metal deposition

Article Title: Differential morpho-physiological and metabolic responses of various genotypes of Andrographis paniculata to atmospheric dust stress

Article References: Yadav, S., Kashyap, S., Ansari, S. A., Khan, A. S., & Khare, P. (2026). Differential morpho-physiological and metabolic responses of various genotypes of Andrographis paniculata to atmospheric dust stress. Environmental Monitoring and Assessment, 198(10), Article 1079. https://doi.org/10.1007/s10661-026-15819-8

Image Credits: AI Generated

DOI: 10.1007/s10661-026-15819-8

Keywords: Andrographis paniculata, atmospheric dust, heavy metals, lead, cadmium, arsenic, subcellular distribution, carbohydrate metabolism, sucrose synthase, glutamate dehydrogenase, genotypic variability, medicinal plants

The urgency behind the work stems from a familiar and worsening problem. Vector-borne diseases such as dengue, chikungunya, filariasis and West Nile fever continue to burden public health systems worldwide, while mosquito populations have grown steadily resistant to the synthetic chemicals deployed against them. Resistance typically arises through enhanced detoxification and reduced sensitivity of the target protein, eroding the effectiveness of organophosphates and carbamates that act on the cholinergic nervous system. Plant-derived phytochemicals, which are biodegradable, less persistent in the environment and often less toxic to non-target organisms, have attracted growing interest as alternatives. Previous studies have shown larvicidal effects of plant extracts ranging from Cassia fistula flowers to Calotropis procera leaves, but crude extracts blur the identity of the active molecule. What distinguishes the new study is its focus on a single, purified, structurally characterized compound.

Andrograpanin itself has an interesting pedigree. It is a deoxygenated analog of andrographolide, the principal bitter diterpenoid of A. paniculata, a plant widely known as the ‘king of bitters.’ For the study, fresh leaves were collected from Palayamkottai in Tamil Nadu, India, authenticated by the Siddha Central Research Institute in Chennai, and processed from 1.5 kilograms of shade-dried material. Successive Soxhlet extraction with hexane, chloroform and methanol yielded a methanol extract that showed the highest bioactivity. Silica gel column chromatography, eluted with a chloroform-ethyl acetate mixture, then delivered andrograpanin as a colorless crystalline solid melting at 103 to 104 degrees Celsius. Infrared, proton and carbon NMR, and GC-MS analyses confirmed a labdane diterpenoid with the formula C20H30O3 and a molecular mass of 318, featuring the gamma-lactone carbonyl and exomethylene groups characteristic of the compound.

Before any docking could begin, the team needed biological evidence that the molecule actually kills mosquitoes. Using standardized World Health Organization guidelines with five replicates per assay, and probit analysis to derive lethal concentrations, the researchers tested ovicidal, larvicidal and pupicidal activity against both species. The results were striking for a natural product. At just 2 parts per million, andrograpanin killed 72 percent of Ae. aegypti eggs and 78 percent of Cx. quinquefasciatus eggs. Larval LC50 values came in at 1.18 ppm for Ae. aegypti and 1.10 ppm for Cx. quinquefasciatus, with LC90 values of 2.74 and 2.55 ppm respectively. Pupae proved slightly hardier, with LC50 values of 1.33 and 1.25 ppm. These potencies, achieved by a single purified phytochemical at parts-per-million concentrations, provided the biological anchor for the computational question that followed: what molecular target might explain this activity?

The obvious candidate was acetylcholinesterase, the enzyme that sits at the heart of insect neurochemistry. Acetylcholinesterase hydrolyzes the neurotransmitter acetylcholine in the synaptic cleft, terminating each nerve impulse and resetting the synapse for the next signal. Block the enzyme, and acetylcholine accumulates, firing postsynaptic receptors continuously until the insect convulses, becomes paralyzed and dies. This is precisely the mechanism exploited by organophosphate and carbamate insecticides, which makes AChE1 a validated and well-characterized target. If andrograpanin could be shown to occupy the same binding pocket, it would generate a plausible mechanistic explanation for the observed mosquitocidal activity.

Because no experimental crystal structures existed for AChE1 from either mosquito species, the team built homology models using SWISS-MODEL, retrieving protein sequences from UniProtKB and selecting the crystal structure of an insecticide-resistant acetylcholinesterase mutant from Anopheles gambiae (PDB ID 6ARY) as the template. The resulting models captured the conserved catalytic domain, including the deep substrate-binding gorge where ligand recognition occurs. Validation was rigorous: Ramachandran plot analysis via PROCHECK placed 94.8 percent of Ae. aegypti residues in the most favored region with no disallowed positions, while the Cx. quinquefasciatus model showed 88.7 percent in the highly preferred region and also no disallowed residues. QMEAN scoring assessed global model quality, and CASTp analysis identified the principal binding pocket and the active-site residues involved in the enzyme’s hydrolase function, defining the docking arena.

The docking itself was performed with AutoDock Tools using a Lamarckian Genetic Algorithm, with each experiment comprising ten runs, 150 individuals in the population and 500,000 energy evaluations on a grid of 60 by 60 by 60 points at 0.375 angstrom spacing. The receptor was held rigid while the ligands were flexible. Andrograpanin emerged with a predicted binding energy of minus 6.36 kcal/mol against Ae. aegypti AChE1 and minus 6.45 kcal/mol against Cx. quinquefasciatus AChE1, with a ligand efficiency of 0.28 in both cases. In the Ae. aegypti model, the compound formed two conventional hydrogen bonds, one with the polar residue HIS47 at 3.02 angstroms and one involving the backbone of ILE91 at 2.11 angstroms, along with hydrophobic contact with TYR43 and carbon-hydrogen bonds with TYR45. In Cx. quinquefasciatus, it hydrogen-bonded with ASN65 and the GLY96 backbone, and made carbon-hydrogen contacts with SER44 and PRO64, all clustered around the catalytic gorge.

Temephos, docked under identical conditions as the reference standard, fared measurably worse. Against Ae. aegypti AChE1 it scored minus 4.36 kcal/mol with a ligand efficiency of 0.16, and against Cx. quinquefasciatus AChE1 it scored minus 4.06 kcal/mol with an efficiency of 0.20. Converted to inhibition constants through the thermodynamic relationship ΔG = RT ln(Ki) at 298.15 kelvin, the numbers diverge dramatically: andrograpanin’s Ki values ranged from 18.69 to 21.76 micromolar, while temephos ranged from 636.46 to 1056.07 micromolar, roughly a fifty-fold difference in predicted binding favorability. The comparison gains context from earlier docking studies of plant compounds against mosquito AChE1, which have reported scores from about minus 5.2 to minus 8.5 kcal/mol for molecules such as β-isocostic acid, longifolene and α-solanine. Andrograpanin’s values sit squarely within that range, though the authors caution that cross-study comparisons are complicated by differences in receptor structures, algorithms and scoring functions.

The novelty of the work lies in its integration. Rather than docking a hypothetical ligand or a crude extract, the team combined a purified, spectroscopically confirmed compound with experimentally validated ovicidal, larvicidal and pupicidal bioassays and a head-to-head computational comparison with a commercial insecticide under identical docking conditions. That convergence of biological and computational evidence strengthens the case for andrograpanin as a lead molecule for sustainable mosquito control, and the interaction profile, with hydrogen bonds and hydrophobic contacts surrounding the substrate-binding pocket, suggests the compound could interfere with substrate access or stabilization of the enzyme-substrate complex.

Yet the authors are unusually candid about the limits of their evidence. Molecular docking predicts a static binding pose and cannot fully capture protein flexibility, solvent effects or conformational dynamics, and the study lacks molecular dynamics simulations that would test whether the docked complexes remain stable over time. The absence of archived SWISS-MODEL project files also prevented reporting of detailed template alignment statistics. Most importantly, no direct acetylcholinesterase inhibition assay has yet been performed, so the proposed mechanism remains a computational hypothesis rather than demonstrated biochemistry. The docking energies, while more favorable than temephos’s, represent only moderate predicted affinities and should not be read as proof of potent enzyme inhibition. The path forward, the researchers argue, runs through enzyme inhibition assays, molecular dynamics simulations with MM/PBSA or MM/GBSA binding free-energy calculations, toxicity testing against non-target organisms and field trials. If those steps confirm what the docking suggests, a bitter leaf from southern India may yet yield a weapon against two of humanity’s most persistent disease vectors.

Subject of Research: Molecular docking of the plant diterpenoid andrograpanin with acetylcholinesterase 1 from Aedes aegypti and Culex quinquefasciatus mosquitoes

Article Title: Molecular docking analysis of andrograpanin interactions with acetylcholinesterase from Aedes aegypti and Culex quinquefasciatus

Article References: Vilvest, J., Milton, M. C. J., Yagoo, A., & Stalin, A. (2026). Molecular docking analysis of andrograpanin interactions with acetylcholinesterase from Aedes aegypti and Culex quinquefasciatus. Discover Chemistry, 3(1), Article 477. https://doi.org/10.1007/s44371-026-00933-w

Image Credits: AI Generated

DOI: 10.1007/s44371-026-00933-w

Keywords: andrograpanin, acetylcholinesterase, molecular docking, Aedes aegypti, Culex quinquefasciatus, mosquito control, Andrographis paniculata, temephos, botanical insecticides, homology modeling, insecticide resistance, vector-borne disease

The research, led by Mythri B C and Channayya Hiremath of the CSIR-Central Institute of Medicinal and Aromatic Plants with collaborators across India, evaluated twenty-three kalmegh genotypes during the rainy season of 2024. The team planted the genotypes in triplicate under a randomized complete block design at four environmentally diverse sites: Bangalore, Hyderabad, Lucknow and Pantanagar. This spread of locations was deliberate. Southern, central and northern Indian growing conditions differ in rainfall, temperature and soil characteristics, and those differences can dramatically reshape both how much biomass a plant produces and which secondary metabolites it accumulates in its leaves and stems. By testing the same genetic material in all four environments simultaneously, the researchers could ask a deceptively simple question with profound commercial implications: which genotypes are genuinely excellent, and which merely happen to excel in one lucky location?

The answer required disentangling three statistical effects that are often confounded in single-site trials. The first is the genotype effect, the intrinsic genetic capacity of each line. The second is the environment effect, the overall push or pull that each location exerts on all genotypes grown there. The third, and most troublesome, is the genotype-by-environment interaction, often abbreviated GEI, which describes how the relative ranking of genotypes changes across locations. Analysis of variance revealed significant effects of genotype, environment and GEI for all five measured traits: fresh herb yield, dry herb yield, andrographolide content, neo-andrographolide content and 14-deoxy-11,12-didehydroandrographolide content. In practical terms, this means that no breeder can simply pick the best kalmegh line from one trial and expect it to dominate everywhere. The interaction term is large enough that it actively reshuffles the league table from site to site.

To visualize and quantify this reshuffling, the team deployed two of the most widely used frameworks in modern plant breeding: the AMMI model and the GGE biplot. AMMI, which stands for Additive Main Effects and Multiplicative Interaction, works by first removing the average genotype and environment effects through standard analysis of variance, then applying principal component analysis to the leftover interaction matrix. The resulting interaction principal component axes, or IPCAs, compress a sprawling table of genotype-by-location performance into a few interpretable dimensions. The GGE biplot takes a complementary approach, focusing on the genotype main effect plus the genotype-by-environment interaction, the two components that matter when a breeder wants to know which cultivar to recommend for which region. Plotting genotypes and environments together in the same bi-plot space allows researchers to identify winning genotypes for each environment, detect groups of locations that behave similarly, and assess how stable each genotype is around its mean performance.

Beyond these graphical tools, the researchers computed quantitative stability metrics, including the modified AMMI Stability Value, known as MASV, and a simultaneous selection index, abbreviated SI. These indices condense the interaction information into single numbers per genotype, making it easier to rank candidates that combine high performance with low sensitivity to environmental fluctuation. The MASV approach, refined in earlier work on Indian breeding programs, penalizes genotypes that carry large interaction scores on the significant IPCA axes, while the selection index integrates yield and stability into a joint criterion. Together with the AMMI and GGE analyses, these metrics provided a multi-angle assessment that guards against the quirks of any single statistical model, a concern that has been debated extensively in the agronomy literature comparing AMMI and GGE methodologies.

The headline finding is a study in nuance: no single genotype was superior for all five traits. Instead, the analysis carved the germplasm into specialists. Genotypes G1 and G18 emerged as stable, high performers for both fresh and dry herb yield, meaning farmers growing them across the tested regions could expect dependable biomass without wild swings from site to site. For the flagship molecule andrographolide, the compounds most associated with the plant’s anti-inflammatory and hepatoprotective credentials, genotypes G16 and G17 delivered stable content across environments. Meanwhile, G8 proved the most reliable source for the other two diterpenoids tracked in the study, neo-andrographolide and 14-deoxy-11,12-didehydroandrographolide. This pattern of trait-specific stability is not a disappointment but a roadmap: it tells breeders exactly which lines to cross or combine in breeding programs aimed at different end goals, whether that goal is raw herbal biomass for the nutraceutical trade or maximized diterpenoid concentration for standardized pharmaceutical extracts.

The pharmacological stakes are considerable. Andrographolide and its labdane diterpenoid relatives have attracted intense research interest for applications ranging from upper respiratory infection treatment, supported by randomized clinical evaluations of kalmegh extracts, to cardioprotection, with experimental studies showing that andrographolide can mitigate adverse cardiac remodeling after myocardial infarction by enhancing the Nrf2 signaling pathway. Synthetic chemists have also used andrographolide as a scaffold for deriving new ent-labdane diterpene derivatives with cytotoxic activity against cancer cell lines, and computational screens have explored kalmegh phytochemicals as antiviral candidates. Every one of these downstream applications depends on a reliable, standardized supply of raw material with consistent diterpenoid profiles, which is precisely what unstable, environment-sensitive cultivars fail to deliver. A batch of kalmegh grown in one region might meet pharmacopoeial thresholds for andrographolide while the same genotype grown elsewhere falls short, creating quality-control headaches for manufacturers and pricing uncertainty for farmers.

This is why the genotype-by-environment framework matters beyond the academic exercise. Multi-environment trial analysis, once the exclusive domain of staple crop breeding, has become essential for medicinal and aromatic plants whose value lies in specific secondary metabolites rather than calories. Previous work by some of the same research groups has applied GGE biplot methods to lemongrass clone selection and to geranium morphology and chemistry, and an earlier study by Hiremath and colleagues specifically examined andrographolide and neo-andrographolide stability in kalmegh using AMMI and GGE approaches. The current study extends that lineage by adding a fourth environment, a broader genotype panel and the third diterpenoid, 14-deoxy-11,12-didehydroandrographolide, giving a more complete picture of the crop’s chemical and agronomic variability across India’s diverse kalmegh-growing regions.

The authors are careful to flag the limits of their conclusions, and that caution is scientifically important. Because the trial covered a single rainy season, the stability parameters they report reflect spatial variation only. Season-to-season weather fluctuation, including the vagaries of monsoon timing and intensity, can introduce additional interaction effects that a one-year snapshot cannot capture. Before any of the identified genotypes, G1, G18 for yield, G16 and G17 for andrographolide, or G8 for the other diterpenoids, can be released for commercial cultivation, the team emphasizes that multi-year, multi-location evaluation is required to confirm that their stability holds across time as well as space. This is a standard but frequently skipped step in medicinal crop improvement, and its explicit inclusion here signals a rigorous path from statistical identification to practical deployment.

Even so, the study delivers an immediately usable asset to the kalmegh value chain. Breeders now have named, stable genotypes to use as parents for combining high yield with high diterpenoid content; farmers and cultivation companies have shortlisted candidates matched to their regions; and phytochemical suppliers have evidence-based guidance on where to source material with consistent active compound levels. The work also demonstrates how modern statistical genetics, from AMMI’s interaction principal components to the visual intuition of GGE biplots and the numerical discipline of stability indices, can be brought to bear on a traditional medicinal plant that has historically been cultivated with little formal breeding. As global demand for evidence-based botanical therapeutics continues to grow, the marriage of classical field trials with quantitative genetics offers a template for upgrading other underbred medicinal crops, ensuring that the chemistry that makes these plants valuable can be reproduced reliably, harvest after harvest, field after field.

Subject of Research: Genotype-by-environment interaction analysis of herb yield and diterpenoid content in the medicinal plant Andrographis paniculata (kalmegh)

Article Title: Unravel genotype by environment interaction for herb yield and important diterpenoids to enhance the therapeutic potential of kalmegh (Andrographis paniculata, Acanthaceae): AMMI and GGE biplot-based approach

Article References: B C, M., S, G. P., Likitha, A. G., Hiremath, C., T M, A. K., A C, J., Gupta, N., Upadhyay, R. K., & Shanker, K. (2026). Unravel genotype by environment interaction for herb yield and important diterpenoids to enhance the therapeutic potential of kalmegh (Andrographis paniculata, Acanthaceae): AMMI and GGE biplot-based approach. Plant Biosystems, 160(5), Article 268. https://doi.org/10.1007/s44473-026-00283-6

Image Credits: AI Generated

DOI: 10.1007/s44473-026-00283-6

Keywords: kalmegh, Andrographis paniculata, andrographolide, diterpenoids, genotype-by-environment interaction, AMMI, GGE biplot, multi-environment trials, medicinal plant breeding, stability analysis, herb yield, phytochemistry