The results support the hybrid scaffold as a starting point for further anti-inflammatory lead optimization, but the animal experiment did not directly measure COX-2 inhibition or establish COX isoform selectivity. The investigation addressed a well-known limitation in nonsteroidal anti-inflammatory drug research: conventional NSAIDs reduce pain and inflammation by inhibiting cyclooxygenase enzymes, but inhibiting both COX-1 and COX-2 can contribute to gastrointestinal, renal and cardiovascular complications. Ketoprofen is a propionic-acid NSAID with analgesic and anti-inflammatory effects, although its nonselective inhibition of COX isoforms may contribute to the adverse effects associated with this class.

The researchers reasoned that adding a thiazolidin-4-one ring to the ketoprofen framework could change molecular volume, polarity, hydrogen-bonding capacity and three-dimensional orientation in a way that might improve compatibility with the larger, more flexible COX-2 binding channel. That structural hypothesis is linked to a consequential difference between the two main COX isoforms. COX-1 contains a bulkier isoleucine residue at position 523, whereas COX-2 contains the smaller valine at that position.

Together with other local differences, this substitution creates an additional side pocket within the COX-2 active-site channel that is less accessible in COX-1. Selective inhibitors can exploit this additional space by occupying the hydrophobic channel while directing bulky or properly oriented polar groups into the COX-2 side pocket. The investigators used the experimentally resolved structure of human COX-2 bound to rofecoxib, deposited as Protein Data Bank entry 5KIR, as the principal docking target.

They also examined whether the designed molecules could interact with residues including Arg120, Tyr355, Tyr385, Ser530, Glu524, Trp387, Phe518 and Val523. Eight hybrid designs were evaluated computationally, and four were selected for synthesis and biological testing. The synthetic route began with conversion of ketoprofen into its methyl ester, followed by hydrazide formation, condensation with substituted benzaldehydes to create four hydrazone intermediates, and thioglycolic-acid-mediated cyclization to produce the thiazolidin-4-one derivatives.

The final compounds carried para-nitro, para-chloro, para-hydroxy or para-dimethylamino aryl substituents and were designated AR1 through AR4. Ketoprofen methyl ester was obtained in 95% yield, ketoprofen hydrazide in 50%, the hydrazone intermediates in 50% to 70%, and the final thiazolidin-4-one derivatives in 65% to 84%. Infrared and nuclear magnetic resonance measurements supported the expected functional-group transformations, including new ring-related aliphatic signals and carbonyl features in the products.

Docking results were broadly favorable but depended on the scoring method. In the initial GOLD PLP fitness workflow, AR1 ranked highest among the designed compounds with a score of 81.10, followed by AR2 at 77.11, AR4 at 76.31 and AR3 at 74.24. Those four highest-ranking derivatives advanced to synthesis and biological evaluation.

The protocol reproduced the crystallographic ligand pose with a root-mean-square deviation of 0.276 angstroms across 33 matched atom pairs. Tyr355 repeatedly formed hydrogen-bonding contacts, while Arg120 anchored several compounds near the entrance to the COX-2 channel. Substituent-dependent contacts with His90, Leu352, Tyr385, Ser530, Glu524, Trp387, Phe357 and Phe518 changed the internal interaction patterns.

The comparative docking trial with COX-1 produced a provisional computational signal. Ketoprofen generated an acceptable predicted pose in the COX-1 structure 1EQG, whereas the hybrid derivatives and rofecoxib did not generate acceptable poses under the conditions used. This may be consistent with the bulkier hybrids fitting COX-2 more readily than COX-1, but the authors emphasized that failure to obtain a docked pose is not proof of biochemical selectivity.

Docking outcomes depend on receptor preparation, search parameters and scoring functions. Experimental COX-1 and COX-2 inhibition assays were therefore needed to determine whether the predicted isoform preference translated into true biochemical selectivity. The same caution applied to the molecular dynamics results, which were performed only for AR1 rather than for the entire series or the reference drugs.

In the AR1–COX-2 molecular dynamics simulation, the protein C-alpha root-mean-square deviation rose initially and then fluctuated around a stable plateau, while monitoring indicated that the global protein fold remained preserved. AR1 retained recurring interactions with Tyr385, Tyr355, Arg120 and Glu524, supporting a plausible association with the active site over the 100.102-nanosecond production trajectory. Ligand RMSD increased toward the end of the simulation, which was interpreted as conformational adjustment within the pocket rather than clear dissociation.

The simulated system contained 55,873 atoms, including 15,632 water molecules, and ran at 300 kelvin under an NPT ensemble. Because only one candidate underwent dynamic simulation, the result provides support for AR1’s predicted binding mode but does not establish that it is dynamically more stable than the other derivatives or reference compounds. Predicted absorption, distribution, metabolism and excretion properties suggested that the designed series was generally within an oral drug-like range, although aqueous solubility emerged as a limitation.

All eight computationally assessed derivatives had molecular weights below 500 daltons, and predicted human oral absorption ranged from 87.473% to 100%. AR1, AR3, AR5, AR6 and AR8 had no predicted Lipinski Rule-of-Five violations, whereas AR2, AR4 and AR7 had one violation each. The compounds with violations were generally more lipophilic.

Most derivatives also had more negative QPlogS values than the two reference compounds, indicating lower predicted aqueous solubility despite favorable absorption estimates. AR3 combined no Rule-of-Five violation with a predicted oral absorption of 93.751%, while AR1 had a predicted absorption of 87.473% and no violation. The results identified solubility as a principal developability challenge, particularly for the more lipophilic analogues.

Anti-inflammatory activity was assessed with egg-white-induced paw edema in 36 female albino mice allocated equally to six groups: ketoprofen, AR1, AR2, AR3, AR4 and vehicle. The mean body weight was 20.34 grams. Treatments were delivered intraperitoneally 30 minutes before paw swelling was induced.

Ketoprofen was administered at 5 milligrams per kilogram, while the hybrids received molecular-weight-adjusted equimolar doses: 9.35 mg/kg for AR1, 9.14 mg/kg for AR2, 8.78 mg/kg for AR3 and 9.31 mg/kg for AR4. Analysis of baseline-adjusted paw-thickness changes from 60 to 240 minutes showed significant effects of treatment group, time and the treatment-by-time interaction. Ketoprofen significantly reduced edema versus vehicle at 60 minutes by an estimated 0.513 millimeters, with p = 0.028, but not at later time points.

The hybrids displayed a delayed pattern: AR3 and AR2 were significantly below vehicle at 120 minutes, with differences of 0.591 millimeters and 0.504 millimeters, respectively, while AR1, AR2 and AR3 remained significantly below vehicle at 180 and 240 minutes. AR3 emerged as the strongest biological candidate in the tested set. Its model-adjusted change in paw thickness was 0.257 ± 0.104 millimeters at 120 minutes, −0.071 ± 0.104 millimeters at 180 minutes and −0.251 ± 0.104 millimeters at 240 minutes, compared with 0.848 ± 0.123, 0.666 ± 0.123 and 0.421 ± 0.123 millimeters for vehicle.

It also produced lower edema than ketoprofen at 240 minutes by an estimated 0.436 millimeters after Bonferroni adjustment, with p = 0.031. AR4 was less convincing, showing greater edema than ketoprofen at 60 minutes by an estimated 0.495 millimeters, with p = 0.007, and no comparable late-phase advantage. The divergence between computational and biological rankings shows that docking scores alone cannot capture solubility, tissue exposure, distribution following intraperitoneal administration or the complexity of the inflammatory response.

The study therefore identifies AR3 as the best-supported initial lead and AR1 as a computationally promising, biologically active alternative, while calling for biochemical selectivity tests, expanded pharmacological and safety evaluation, pharmacokinetic profiling, solubility optimization and comparative molecular dynamics simulations.

Subject of Research: Computational and mouse evaluation of ketoprofen–thiazolidin-4-one hybrid anti-inflammatory candidates

Article Title: Design and synthesis of thiazolidin-4-one–ketoprofen hybrids as potential COX -2 inhibitors with anti-inflammatory activity

Article References: Mazin, A., Mahdi, M. F., & Kareem Khan, A. (2026). Design and synthesis of thiazolidin-4-one–ketoprofen hybrids as potential COX-2 inhibitors with anti-inflammatory activity. Pharmacia, 73, Article e194751. https://doi.org/10.3897/pharmacia.73.e194751

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e194751

Keywords: ketoprofen hybrids, thiazolidin-4-one, COX-2, anti-inflammatory activity, mouse paw edema, molecular docking, molecular dynamics, ADME prediction, drug discovery, medicinal chemistry, Design, synthesis

The platform, developed by Professor Yoonsu Park’s team in KAIST’s Department of Chemistry, automates the entire sequence from mixing raw materials to synthesis and analysis. Once a researcher prepares the equipment and sets the conditions, a raw-material dispensing robot combines the starting chemicals, and automated pumps continuously feed the resulting solution through a narrow tube at a constant rate. Visible light is then irradiated onto the tube to drive the chemical reaction, and when the reaction is complete the solution is transferred automatically to analytical equipment that determines whether the desired compound has been produced and in what quantity. No manual transfer or measurement intervenes at any stage.

The heart of the system is what chemists call a continuous-flow process, an approach in which raw materials are continuously fed through the reaction zone rather than loaded all at once into a batch vessel. The KAIST team offers an intuitive analogy: it is like continuously supplying ingredients into a small pot rather than putting everything into a large pot at once. Because the reaction takes place inside a narrow tube, light can be distributed evenly throughout the solution — a critical advantage for photochemistry, where uneven illumination in large batch reactors often produces inconsistent results. And because the process runs continuously, production volume can be increased simply by operating the same setup for a longer period, sidestepping one of the most notorious problems in chemical manufacturing.

That scaling problem deserves emphasis, because it is a quiet drag on pharmaceutical research. Even slight differences in molecular structure can require entirely new reaction conditions, and even when a small-scale synthesis succeeds, scaling it up can alter the way light or heat is transferred through the reaction mixture, forcing chemists to re-optimize everything from scratch. A flow platform largely dissolves this difficulty: the reaction environment inside the tube stays the same whether the system runs for an hour or a week, so conditions established at small scale translate far more reliably to larger production runs. For a field where each new molecule can demand its own bespoke recipe, that predictability is a significant prize.

To benchmark the automated system’s performance, the research team applied it to a single-atom editing reaction — a comparatively new technology that selectively replaces a specific atom in a molecule while keeping the overall molecular framework intact. The starting materials in this case were furans, five-membered ring compounds composed of oxygen and carbon that serve as basic molecular scaffolds for the synthesis of pharmaceuticals and other chemical substances. By swapping individual atoms within these frameworks, the platform produced N-substituted pyrroles, including the N-methyl pyrrole scaffold, a fundamental structural motif used throughout pharmaceutical development.

The scope of the demonstration was broad. The team applied the synthetic method to more than 20 furan-based compounds, and even in structurally complex natural products the desired portion could be modified while the rest of the structure was left untouched. That selectivity matters enormously in medicinal chemistry, where a molecule’s biological activity often hinges on the precise arrangement of a handful of atoms. Compounds produced through single-atom editing can change how a drug binds to proteins in the body, which is precisely why the technique has been attracting attention as a tool for refining drug candidates rather than merely generating them.

The practical payoff lies in how drug discovery actually proceeds. Developing a medicine is fundamentally a comparative exercise: researchers produce families of compounds with slightly different structures and test them against one another to see which binds most effectively to a therapeutic target protein or shows the lowest toxicity. Part of an existing compound may be modified, for example, and the variant then screened to determine whether the change improves potency or safety. Each comparison requires a fresh supply of a distinct compound, and the sheer volume of synthesis this entails has historically limited how many candidates a laboratory can explore. By automating production, the KAIST platform is expected to make it far more efficient to obtain the compounds needed for such comparisons, widening the range of drug candidates a team can realistically evaluate.

Professor Park framed the advance in terms of the pace of discovery itself. How quickly and reliably designed molecules can be synthesized, he noted, will determine the speed of future drug development. He added that the platform is expected to provide a foundation for moving toward an era of automated organic synthesis by enabling reaction conditions to be quantified and reproduced. That last point — quantification and reproducibility — may prove as consequential as the automation itself. In conventional laboratory practice, reaction conditions often live in the tacit knowledge of individual chemists; a platform that encodes them as machine-readable parameters makes every experiment a permanent, repeatable asset that other researchers or other machines can rerun on demand.

The study was a collaborative effort within KAIST. Hyeonbhin Byeon and Hojin Hong, both integrated M.S.-Ph.D. students in the Department of Chemistry, participated as co-first authors, while Professor Yoonsu Park and InnoCORE Fellow Ha Eun Kim of the InnoCORE AI-CRED Innovative Drug Research Group served as corresponding authors. The findings were published online on August 7 in JACS Au, an international journal published by the American Chemical Society, under the title Direct Access to the Simplest N-Substituted Pyrroles from Furans Enabled by Tailored Photocatalysts. The work was supported by the Korea Basic Science Institute’s Young Researcher Infrastructure Support Program and the InnoCORE AI-CRED Innovative Drug Research Group.

The broader significance of the work extends beyond a single reaction class. As AI-driven molecular design accelerates, the laboratories that can convert computational proposals into physical compounds fastest will hold a decisive advantage, and platforms like KAIST’s point toward a model in which synthesis becomes a continuous, quantified service rather than a craft performed molecule by molecule. A system that mixes, irradiates, analyzes and reports without human intervention — and that scales production by simply running longer — offers a glimpse of chemistry laboratories operating the way modern factories do: continuously, reproducibly and, when required, entirely unattended. If such platforms become routine, the limiting factor in early drug discovery may shift from the speed of a chemist’s hands to the imagination of the algorithms proposing what to make next.

Subject of Research: Automated continuous-flow photocatalytic synthesis of N-substituted pyrroles for drug candidate production

Article Title: KAIST develops '24/7 unmanned synthesis platform' using robots and light to produce drug candidates

Article References: KAIST develops '24/7 unmanned synthesis platform' using robots and light to produce drug candidates. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: KAIST, automated synthesis, continuous-flow chemistry, photocatalysis, drug discovery, N-methyl pyrrole, furan, single-atom editing, organic synthesis, medicinal chemistry, laboratory automation, JACS Au

The 1,3,4-oxadiazole ring is a five-membered heterocycle comprising one oxygen and two nitrogen atoms, widely investigated in medicinal chemistry for its aromatic stability and bioisosterism with the carbonyl group in amides and esters. Heterocyclic scaffolds make up more than 85 percent of FDA-approved drug molecules, owing to their ability to form various intermolecular interactions including hydrogen bonding, metal coordination, π–π stacking, hydrophobic interactions, and van der Waals contacts. Several biological activities have been reported for 1,3,4-oxadiazoles, including antimicrobial, anti-inflammatory, antioxidant, and anticancer effects, with reported anticancer mechanisms including inhibition of growth factor receptors such as EGFR and VEGFR and induction of apoptosis in several tumor types. However, oxadiazole-based compounds had not previously been explored specifically for oligodendroglioma.

The synthesis proceeded through acid-catalyzed condensation of the appropriate hydrazides with aromatic aldehydes in absolute ethanol under reflux to afford hydrazone intermediates, which were then oxidatively cyclized using iodine and potassium carbonate in dimethyl sulfoxide at 100 °C for three to six hours to yield the final oxadiazole derivatives. Seven compounds were produced, designated A1 through A3 and B1 through B4, with the A series bearing a 5-chloro-2-nitrophenyl substituent and the B series bearing a 4-cyanophenyl substituent at the C-5 position of the oxadiazole ring. Characterization was carried out by FT-IR, proton NMR, carbon-13 NMR, and electron ionization mass spectrometry, with the infrared spectra supporting complete ring closure by the disappearance of the N–H stretching band and the amide carbonyl C=O stretching band of the hydrazones, alongside the appearance of characteristic C=N stretching of the oxadiazole ring and C–O–C asymmetric stretching.

Biological evaluation used the MTT colorimetric assay, which is based on the reduction of a yellow tetrazolium salt by mitochondrial dehydrogenase enzymes in metabolically active cells, producing an insoluble purple formazan product whose absorbance correlates directly with cell viability. Cells were plated at 10,000 cells per well in 96-well microplates, incubated for 24 hours, and exposed to serial concentrations of the test compounds ranging from 10 to 1,000 µg/mL, with cisplatin run in parallel as a reference drug. The IC50 values of all seven compounds were lower than that of cisplatin, which recorded an IC50 of 212.27 µg/mL against HS683 cells. Compounds bearing the 4-cyanophenyl group at C-5 were consistently more active than their A analogs, with IC50 values approximately half those of the matched pairs.

The selectivity index, calculated as the ratio of the IC50 against normal human astrocytes to the IC50 against HS683 cells, showed a clear advantage of the synthesized compounds over cisplatin, whose SI of 1.25 indicates near-equal toxicity toward tumor and normal cells. All seven compounds gave SI values greater than 1, with B2 achieving the highest SI of 14.55, followed by A2 with an SI exceeding 12.15, whose IC50 against normal human astrocytes exceeded 1,000 µg/mL, indicating minimal toxicity toward healthy brain cells. This favorable selectivity profile is particularly significant given that treatment-related adverse effects remain difficult to manage with current oligodendroglioma therapies, which typically involve radiotherapy and chemotherapy with temozolomide or the PCV regimen in conjunction with surgical resection.

Structure–activity relationship analysis revealed that the thiophen-2-yl group at the C-2 position produced the lowest IC50 values in both series, lower than those of their phenyl-substituted counterparts. Within compounds B, the activity order was B2 with the thienyl substituent, followed by B1 with pyridin-4-yl, B4 with 4-methylphenyl, and B3 with 4-fluorophenyl. Notably, pyridin-4-yl was the least active substituent among compounds A but the second-most active among compounds B, indicating that its contribution to activity depends on the electronic and steric character of the C-5 substituent. The thienyl compounds also possessed the highest selectivity indices in both series, suggesting that the thiophen-2-yl group was beneficial not only for cytotoxic potency but also for selectivity toward HS683 cells over normal astrocytes.

Molecular docking studies were performed against three kinase targets selected for their relevance to glioma pathogenesis: phosphatidylinositol 3-kinase alpha, cyclin-dependent kinase 2, and focal adhesion kinase. PI3Kα was included because of its role in the PI3K/AKT/mTOR pathway, CDK2 was included because of its overexpression in low-grade glioma subtypes, and FAK was selected based on its overexpression in glioma. The docking protocol was validated by re-docking the co-crystallized ligands, with root-mean-square deviation values all below 2.0 Å, confirming that the computational approach reliably reproduced experimental binding modes. Against PI3Kα, compounds B1 and B2 formed the strongest predicted interactions in the study, both forming hydrogen-acceptor contacts with LYS890 at distances of approximately 2.95 Å, with per-contact interaction energies of −9.0 and −8.8 kcal/mol respectively, involving the nitrile nitrogen of the 4-cyanophenyl group.

Against CDK2, compounds A produced scores of −6.654 to −7.087 kcal/mol, while compounds B ranged from −5.914 to −6.101 kcal/mol. B1 formed the richest interaction network among compounds B, with six contacts including two hydrogen-donor/acceptor interactions with LEU83 and PHE82, two hydrogen-acceptor contacts with LYS129 and ASN132, and a π–H contact with ILE10. B2 achieved a hydrogen-donor interaction between its sulfur atom and ASP145, suggesting that the sulfur atom of the thiophen-2-yl group is directly involved in the interaction. Against FAK, A2 achieved the strongest score among the synthesized compounds, and in both A2 and B2 the oxadiazole ring nitrogens served as the primary interaction atoms, forming two hydrogen-acceptor contacts with CYS502. This sulfur-specific contact with ASP145 was not observed for the phenyl- or heteroaryl-substituted analogs, providing a computational rationale for the superior activity of the thienyl compounds.

All seven compounds satisfied Lipinski’s rule of five, with molecular weights ranging from 248.24 to 319.68 g/mol and cLogP values ranging from 2.13 to 3.25, indicating moderate lipophilicity suitable for membrane permeation. The synthesized compounds had no hydrogen-bond donors and four to six hydrogen-bond acceptors, all below the maximum recommended limit. Topological polar surface area values ranged from 62.71 to 112.98 Ų, with compounds A showing higher values than compounds B. All final compounds were predicted to have high gastrointestinal absorption, and none were predicted to act as P-glycoprotein substrates, which may indicate a lower likelihood of efflux-mediated resistance. Notably, B1, B3, and B4 were predicted to permeate the blood–brain barrier, a relevant physicochemical feature for compounds intended to target glioma, although these predictions reflect theoretical permeability rather than confirmed central nervous system distribution and would require experimental validation.

The authors acknowledge that the proposed kinase targets are based on molecular docking and require experimental confirmation, and that further evaluation across additional glioma cell lines and in vivo models would help establish the broader therapeutic relevance of B2. Within the context of prior research, thioacetamide-based 1,3,4-oxadiazole derivatives have shown activity against C6 rat glioma cells, while ferulic acid- and caffeic acid-based oxadiazole hybrid derivatives have demonstrated activity against human glioblastoma cell lines U87, T98G, and LN229. Oxadiazole-based Akt/FAK inhibitors have also shown cytotoxic effects against C6 cells, supporting the relevance of FAK as a target within this chemical class. B2 extends this body of evidence to a previously unexamined glioma cell line and substituent pattern, reinforcing its potential as a lead candidate for future anti-glioma development.

Subject of Research: 1,3,4-Oxadiazole derivatives as potential anti-glioma agents: synthesis, characterization, in vitro cytotoxic activity against HS683 cells, and molecular docking

Article Title: 1,3,4-Oxadiazole derivatives as potential anti-glioma agents: synthesis, characterization, in vitro cytotoxic activity against HS683 cells, and molecular docking

Article References: Hashim, R. J., Alsaad, H. N., & Salman, H. H. (2026). 1,3,4-Oxadiazole derivatives as potential anti-glioma agents: synthesis, characterization, in vitro cytotoxic activity against HS683 cells, and molecular docking. Pharmacia, 73, Article e198079. https://doi.org/10.3897/pharmacia.73.e198079

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e198079

Keywords: 1,3,4-oxadiazole, anti-glioma agents, HS683, oligodendroglioma, molecular docking, MTT assay, selectivity index, drug-likeness, medicinal chemistry, kinase inhibitors, Oxadiazole, derivatives

One of the most instructive themes running through the collected articles is the way structure-activity relationships in quinoline chemistry reveal mechanistic logic rather than arbitrary patterns. The observation that a substituted-aniline moiety at the 4-position of aminoquinolines enhances leishmanicidal potency relative to an alkylamine chain suggests that the aromatic amine contributes specific interactions with the parasite’s mitochondrial machinery that flexible aliphatic chains cannot replicate. Similarly, the finding that lipophilic alkenyl or aryl chains favor activity and selectivity when placed at the 2-, 3-, or 6-positions, while O- or N-substituents are preferred at the 8-position, points to distinct binding environments within the parasite cell that reward different physicochemical properties at different locations on the quinoline ring. This positional specificity is a hallmark of a scaffold engaged in meaningful target engagement rather than nonspecific membrane disruption, and it provides medicinal chemists with a rational map for optimization rather than a trial-and-error landscape.

The role of natural products in this optimization process deserves particular attention. The compilation of quinoline-based secondary metabolites active against Leishmania models demonstrates that evolution has already explored portions of quinoline chemical space that synthetic chemists might not otherwise prioritize. The predominance of 2-alkylquinolines among the isolated bioactive metabolites is especially telling, since the alkyl chain at this position appears to be a recurring motif that nature has validated across multiple producing organisms. When such a metabolite serves as the structural platform for synthetic analogues, as occurred with the 2-substituted quinoline derived from the natural 2-alkylquinoline lead, the process represents a form of biomimetic drug design in which the synthetic chemist refines and extends a molecular hypothesis that biology has already partially tested. This approach has historical precedent in antimalarial drug discovery, where quinine itself, a natural quinoline alkaloid, provided the template for generations of synthetic antimalarials.

The antimalarial articles in the collection illustrate two complementary strategies for modernizing the quinoline scaffold. The first strategy retains the classical mechanism of action, targeting β-hematin polymerization, but introduces modern functional groups such as ureas, carbamates, and thioureas to modulate potency and pharmacokinetics. The near-equivalence between the leading compound’s β-hematin inhibition and that of chloroquine, combined with strong in vivo performance in the Plasmodium berghei model and low hematotoxicity, suggests that the classical heme-polymerization target remains viable when the scaffold is appropriately decorated. This is significant because resistance to chloroquine, driven by mutations in parasite transporters that expel the drug from the digestive vacuole, has historically undermined this mechanism. New quinolines that overcome or circumvent these resistance mechanisms while preserving the heme-polymerization target would represent a meaningful advance, particularly for regions where chloroquine resistance is widespread.

The second antimalarial strategy departs from the classical mechanism entirely, targeting the parasite’s dihydrofolate reductase enzyme through quinoline-thiazolidinone hybrids. This approach demonstrates the versatility of the quinoline ring as a carrier of pharmacophoric elements rather than as the pharmacophore itself. The potent enzyme inhibition observed, with several compounds achieving inhibitory concentrations below two micromolar, indicates that the hybrid scaffold accommodates the binding requirements of the folate pathway enzyme while the quinoline portion contributes favorable physicochemical properties. The in vivo performance of the leading hybrid, reducing parasitemia substantially with extended animal survival, provides proof of concept that quinoline-based structures can succeed against targets unrelated to heme metabolism. This mechanistic diversification is strategically important because it reduces the risk that a single resistance mechanism could compromise an entire chemical class.

The hexahydroquinoline review adds a further dimension to this chemical space by examining partially saturated quinoline analogues. The distinction between the two hexahydroquinoline tautomeric forms, 1,4,5,6,7,8-hexahydroquinoline and 1,2,3,4,4a,5-hexahydroquinoline, reflects the conformational flexibility that partial saturation introduces. Unlike the planar aromatic quinoline, hexahydroquinolines adopt three-dimensional shapes that can engage biological targets through different interaction modes. The reported activity of 1,4,5,6,7,8-hexahydro-6-oxo-3-carboxylquinolines against Plasmodium falciparum, Leishmania species, Trypanosoma cruzi, and Toxoplasma gondii suggests that these scaffolds may interact with conserved parasite biology, possibly related to the parasite’s mitochondrial or metabolic functions, that is shared across multiple protozoan species. A scaffold with this breadth of activity could serve as a starting point for developing agents useful against several diseases simultaneously, an efficiency gain that would be particularly valuable given the limited resources available for antiprotozoal drug discovery.

The translational perspective offered in the collection raises questions that extend beyond chemistry into the broader architecture of drug development for neglected diseases. The observation that computational data and experimental findings remain insufficiently integrated reflects a persistent challenge in medicinal chemistry for neglected tropical diseases. Computational predictions of binding affinity, selectivity, and pharmacokinetic behavior are only as useful as the experimental systems available to validate them, and for many protozoan parasites, particularly the intracellular stages of T. cruzi and the liver stages of Plasmodium, robust and reproducible experimental models are technically demanding. Improving this integration requires not only better algorithms and more powerful computing but also standardized biological assays, open sharing of screening data, and collaborative networks that connect computational groups with parasitology laboratories. The editorial’s call for more robust strategies in this area is a recognition that the bottleneck in antiprotozoal drug discovery is often not the generation of candidate molecules but the reliable evaluation of their therapeutic potential.

The immunostimulatory dimension of 4-aminoquinoline activity against Leishmania adds a layer of complexity that distinguishes antiprotozoal drug design from antibacterial or antiviral approaches. Because Leishmania parasites reside within host macrophages, an effective drug must either kill the parasite directly within its intracellular niche or activate the host cell’s own antimicrobial machinery. The reported increase in proinflammatory cytokine and nitric oxide production by infected macrophages treated with 4-aminoquinolines suggests that these compounds operate through both mechanisms simultaneously. This dual action is potentially advantageous because it engages the host immune system in a way that is harder for the parasite to evade through genetic mutation alone. However, it also raises questions about the therapeutic window, since excessive immunostimulation could contribute to inflammatory pathology. Balancing direct parasiticidal activity with controlled immune activation is a design challenge specific to intracellular protozoan infections and one that the quinoline scaffold appears well positioned to address.

The mitochondrial mechanism proposed for 4-aminoquinolines, involving depolarization of the parasite’s mitochondrial membrane potential and subsequent apoptosis-like cell death, connects this chemical class to a broader family of mitochondria-targeted antiprotozoal strategies. Protozoan parasites possess single mitochondria with distinctive bioenergetic features that differ from those of mammalian cells, including alternative electron transport components and unique metabolic enzymes. These differences provide potential selectivity handles that medicinal chemists can exploit. The morphological changes observed in parasites treated with 4-aminoquinolines are consistent with a programmed cell death pathway, a phenomenon that has been increasingly recognized in protozoa and that offers a therapeutic endpoint distinct from the more commonly targeted parasite-specific enzymes or transporters.

Looking forward, the quinoline scaffold’s continued relevance to antiprotozoal drug discovery will depend on how successfully the insights from this collection are translated into optimized clinical candidates. The convergence of positional substitution logic, natural product validation, mechanistic diversity, and demonstrated in vivo efficacy across multiple protozoan models provides a foundation that is more comprehensive than what any single article could offer. The physicochemical parameters highlighted throughout the collection, particularly lipophilicity and acidity, will be critical determinants of whether laboratory potency survives the journey through absorption, distribution, metabolism, and excretion to reach therapeutically relevant concentrations at the site of infection. Compounds that are too lipophilic may suffer from poor solubility and nonspecific tissue accumulation, while those that are insufficiently lipophilic may fail to penetrate the intracellular niches where protozoan parasites reside. The quinoline ring, with its moderate aromatic character and tunable substitution pattern, occupies a favorable middle ground in this balance, which may partly explain its enduring success as a lead structure across multiple generations of antiprotozoal agents.

The collective message of this Research Topic is that the quinoline and related N-heterocycle scaffolds are not relics of a previous era of antiprotozoal chemotherapy but living platforms whose optimization potential remains far from exhausted. The seven articles gathered here demonstrate that new substitution patterns, new hybrid architectures, new partially saturated analogues, and new mechanistic hypotheses continue to emerge from this chemical family. For researchers working in medicinal chemistry, parasitology, and translational medicine, the collection offers both a summary of current achievements and a roadmap for future investigation, one in which rational design informed by structure-activity relationships, validated by biological experimentation, and guided by the practical constraints of the diseases being targeted can converge to produce the next generation of antiprotozoal therapies.

Subject of Research: Editorial: Quinoline and N-heterocycle analogues as lead structures for the development of antiprotozoal agents

Article Title: Editorial: Quinoline and N-heterocycle analogues as lead structures for the development of antiprotozoal agents

Article References: Romero, A. H., Benaim, G., Charris, J., & Cerecetto, H. (2026). Editorial: Quinoline and N-heterocycle analogues as lead structures for the development of antiprotozoal agents. Frontiers in Chemistry, 14, Article 2005043. https://doi.org/10.3389/fchem.2026.2005043

Image Credits: AI Generated

DOI: 10.3389/fchem.2026.2005043

Keywords: quinoline, antiprotozoal agents, leishmaniasis, malaria, Chagas disease, N-heterocycles, medicinal chemistry, drug discovery, 4-aminoquinolines, hexahydroquinoline, trypanosomiasis, neglected tropical diseases

The subject of the analysis is Professor Kelly Chibale, a Zambian-born synthetic organic and medicinal chemist at the University of Cape Town whose personal history mirrors the scientific problem he set out to solve. As a child, he survived several bouts of malaria, including one severe episode that nearly killed him. Trained in chemistry in Zambia, the United Kingdom — including a visiting fellowship at Pfizer in Sandwich — and the United States, he specialised in small-molecule drug discovery for cardiovascular disease, including hypertension, before turning his focus to infectious diseases: malaria, tuberculosis, schistosomiasis and, more recently, antibiotic-resistant microbial infections. The authors of the perspective, led by Fidele Ntie-Kang of the University of Buea, contend that Chibale’s most transformative achievement is not a single molecule but an institution: the Holistic Drug Discovery and Development Centre, known as H3D, founded in 2010 as the first fully integrated drug discovery platform on the African continent.

What made H3D structurally innovative was its pipeline-oriented design. Rather than operating as a fragmented, grant-driven academic laboratory, the centre co-located screening technologies, biology, medicinal chemistry, in vitro ADME systems, drug metabolism and pharmacokinetics (DMPK), early safety and toxicology assessment, and translational project management within a single institutional framework. This co-location enables seamless progression from hit identification through lead optimisation to candidate selection, supporting the iterative, data-driven decision-making that characterises industrial discovery environments. The result, the perspective argues, is a cohesive discovery setting capable of delivering translational outputs that meet industry-level standards while remaining rooted in an African academic context — a proof of concept that end-to-end pharmaceutical innovation can be conducted on the continent.

The scientific credibility of that model rests on rigorous medicinal chemistry. Chibale’s antimalarial programmes have been distinguished by the iterative refinement of structure–activity relationships, allowing progressive optimisation of compound potency and selectivity, alongside careful tuning of physicochemical properties to enhance drug-likeness, solubility and permeability. Central to the H3D strategy has been the early integration of ADME profiling, ensuring that compounds are evaluated not only for biological activity but for their behaviour in living systems. By aligning compound optimisation with clearly defined target product profiles, the projects maintained a translational focus from the outset. Because malaria drug discovery frequently relies on phenotypic screening — the complexity of parasite biology makes target validation difficult — H3D combined whole-cell phenotypic screening with rational medicinal chemistry refinement, balancing empirical screening with mechanistic insight, conducting target deconvolution to elucidate mechanisms of action, and pursuing target-based discovery in parallel.

The defining milestone came with MMV390048, a novel first-in-class small-molecule inhibitor of Plasmodium phosphatidylinositol 4-kinase, advanced from an international effort led out of Africa at H3D in partnership with the Medicines for Malaria Venture into First-in-Human studies conducted at the University of Cape Town, and subsequently into phase 2 clinical trials. The significance, the authors write, is multidimensional. Scientifically, it demonstrated a functional and coherent hit-to-lead discovery capability within an African setting. Institutionally, it validated the H3D operational model as a sustainable platform for end-to-end discovery. Symbolically, it marked a paradigm shift: Africa could originate pharmaceutical innovation rather than serving solely as a site for clinical trials and downstream validation. Chibale’s contributions extend beyond infectious disease — he is a co-inventor on patents for domain-selective inhibitors of angiotensin-I converting enzyme, around which the United Kingdom spin-out company Angiodesign was established.

H3D’s sustainability was engineered as deliberately as its science. The centre operated on a diversified funding model combining government support, philanthropic foundations, product development partnerships, bilateral industry collaborations and competitive international grants. This hybrid architecture minimised dependence on any single funding source, reduced financial vulnerability and enabled long-term strategic planning. Equally consequential was the way the centre redefined academia–industry partnership: negotiations were structured around co-development rather than subcontracting, ensuring shared ownership of scientific direction and outcomes. African investigators contributed meaningfully to strategic priorities and project design, while the partnerships provided access to advanced technologies, industry-standard workflows and global development expertise — strengthening the credibility of African institutions as reliable, competitive contributors to international pharmaceutical research.

But a single centre, however excellent, could not close the continent’s capacity gaps. The logical next step was network expansion, and it came through the Grand Challenges African Drug Discovery Accelerator, or GC ADDA. Its origins trace to seed funding from the Bill and Melinda Gates Foundation under Grand Challenges Africa in 2018 and 2020, awarded to 16 scientists across Africa to pursue structured, collaborative drug discovery with international partners. Many of those initial grantees became founding members of the GC ADDA network, which was established by the H3D Foundation with funding support from the Gates Foundation and LifeArc. The consortium now operates as a pan-African accelerator with representation in four of Africa’s five geographical regions, integrating competitive project selection, milestone-driven funding, access to expertise in medicinal chemistry and DMPK, industry mentorship and translational guidance.

The accelerator model directly targets the persistent

Subject of Research: The role of Professor Kelly Chibale and the H3D Centre in establishing integrated, African-led drug discovery capacity and pan-African innovation networks

Article Title: Redefining the geography of pharmaceutical innovation: Kelly Chibale as a harbinger for integrated drug discovery in Africa

Article References: Ntie-Kang, F., Cheuka, P. M., Amewu, R. K., Kigondu, E. V. M., & Masimirembwa, C. (2026). Redefining the geography of pharmaceutical innovation: Kelly Chibale as a harbinger for integrated drug discovery in Africa. Frontiers in Drug Discovery, 6, Article 1884834. https://doi.org/10.3389/fddsv.2026.1884834

Image Credits: AI Generated

DOI: 10.3389/fddsv.2026.1884834

Keywords: Kelly Chibale, H3D Centre, drug discovery, Africa, GC ADDA, medicinal chemistry, malaria, MMV390048, scientific sovereignty, pharmaceutical innovation, Global South, capacity building

The research tackles a well-known bottleneck. Traditional experimental screening is expensive, slow, and constrained by the chemical diversity of available compound libraries. Computational models that estimate biological activity directly from molecular structure—known as quantitative structure–activity relationship, or QSAR, models—promise a faster route, but their reliability depends heavily on how they are built. The authors note that many published QSAR efforts suffer from insufficient feature optimization and ambiguity about whether the task is regression, predicting a continuous activity value, or classification, sorting compounds into active and inactive categories. That ambiguity undermines both interpretability and the consistency of performance evaluation.

To address these problems, the team assembled a dataset of 532 structurally diverse compounds with experimentally reported analgesic activity values drawn from published literature. Each molecule was characterized by 227 molecular descriptors spanning constitutional, topological, geometrical, electronic, and physicochemical properties. The activity score was treated as a continuous target for regression, while a statistically derived threshold converted it into a binary active-or-inactive label for classification. Before training, all inputs were normalized with min–max scaling so that no single feature dominated the learning process.

The most consequential step was feature selection. Using a stepwise elimination procedure, the researchers iteratively removed low-importance descriptors while monitoring model performance, combining the Pearson correlation coefficient with a relative prediction error metric as the selection criterion. The descriptor set shrank from 227 variables to 105, and the effect was unambiguous: predictive performance improved steadily as weakly correlated features were pruned, reaching an optimum at 105 descriptors before declining beyond that point. The retained features describe molecular connectivity, polarity, and hydrogen-bonding potential—properties known to modulate receptor binding affinity and pharmacodynamic behavior. The result is a leaner model that generalizes better, trains faster, and resists overfitting, a chronic hazard in high-dimensional neural modeling.

The network itself is a feed-forward multilayer perceptron implemented in MATLAB, with an input layer of 72 neurons feeding three hidden layers of 22, 9, and 2 neurons, each using the hyperbolic tangent sigmoid activation function, and a single linear output neuron. Hyperparameters, including the number of hidden neurons, learning rate, and regularization factors, were tuned through grid search to minimize the average absolute relative error. Training relied on the Levenberg–Marquardt algorithm, a second-order optimization method prized for its rapid convergence and stability in nonlinear parameter spaces. The final model converged in fewer than 50 iterations, outperforming conventional gradient-descent training in both speed and stability, and regression plots showed near-linear agreement between predicted and experimental values across both training and validation sets.

The headline numbers place the model among the best-performing approaches reported for comparable QSAR tasks. Comparable studies using shallow or single-hidden-layer networks typically report correlation coefficients between 0.85 and 0.93. This framework achieved R = 0.959 for regression and 98.01 percent accuracy for classification. In their comparative analysis, the authors contrast their results with deep neural networks used for triple-negative breast cancer inhibitor and GPCR agonist discovery, multilayer perceptrons classifying lung surfactant inhibitors, principal-component neural networks applied to 95 analgesic compounds, and multiple linear regression models built on small sets of pyrimidine derivatives. They attribute their edge to the joint optimization of architecture and feature selection, which together improved the model’s capacity to capture complex nonlinear structure–activity relationships.

What elevates the work beyond raw predictive power is its attention to interpretability. The descriptor classes retained by the model—molecular connectivity indices, polarity-related parameters, hydrogen-bonding capacity, and lipophilicity descriptors—are tied to receptor accessibility, membrane permeability, and ligand–target interaction potential, the very factors that govern analgesic potency. This gives medicinal chemists a foothold for rational compound optimization rather than a black-box score. The authors are candid about the limits, however: because neural networks are inherently nonlinear, complete mechanistic interpretability remains out of reach, and they propose incorporating explainable AI methods or fragment-level attribution analysis in future iterations to extract deeper structural insight.

The team also acknowledges a gap in the competitive landscape. Modern ensemble methods such as Random Forest and gradient boosting can achieve competitive performance on moderate-sized datasets while offering better interpretability, but benchmarking against them fell outside the scope of the present study—a limitation the authors explicitly flag, with comparative evaluation planned as future work. They are equally clear that the model is computational and does not replace experimental validation. Its purpose is to reduce experimental burden by prioritizing compounds before laboratory testing, and prospective validation on newly designed or synthesized molecules is identified as the critical next step for translational applicability.

There is also a sustainability dimension. By cutting dependence on exhaustive laboratory screening, the framework aligns with eco-efficient pharmacological innovation—minimizing experimental waste while enabling broader exploration of chemical space. The authors frame the hybrid feature-selection-plus-neural-network strategy as a reliable, interpretable, and resource-conscious approach to predictive pharmacology, one that complements rather than replaces experimental workflows and remains compatible with translational drug development strategies.

Looking ahead, the researchers outline several extensions: adapting the optimized framework to other pharmacological classes, implementing transfer learning for multitarget predictions, and integrating explainable AI tools to illuminate mechanism. For a field where the vast majority of early-stage candidates never reach the clinic, a model that can reliably flag the most promising analgesic candidates before synthesis—while explaining, at least in part, which molecular features drive its predictions—represents a meaningful step toward faster, cheaper, and more rational drug discovery. The dataset itself is restricted by licensing agreements and cannot be redistributed, but the methodological blueprint—rigorous descriptor reduction, explicit task definition, and systematic architecture optimization—offers a template other labs can follow as artificial intelligence continues to reshape how new medicines are found.

Subject of Research: Deep learning-based QSAR modeling for predicting analgesic activity in early-stage drug discovery

Article Title: Integrative deep learning strategies to enhance early-stage drug discovery: optimizing computational structure–activity modeling for pharmacotherapeutic innovation

Article References: Rezazi, S., Si-Moussa, C., & Hanini, S. (2026). Integrative deep learning strategies to enhance early-stage drug discovery: optimizing computational structure–activity modeling for pharmacotherapeutic innovation. Journal of Pharmacy & Pharmaceutical Sciences, 29, Article 16155. https://doi.org/10.3389/jpps.2026.16155

Image Credits: AI Generated

DOI: 10.3389/jpps.2026.16155

Keywords: artificial intelligence, drug discovery, QSAR, neural networks, analgesics, molecular descriptors, feature selection, Levenberg-Marquardt algorithm, virtual screening, pharmacology, predictive modeling, medicinal chemistry

Leishmaniasis remains one of the most burdensome parasitic diseases worldwide. According to World Health Organization estimates cited in the study, roughly 700,000 to 1 million new cases occur each year, with clinical outcomes ranging from disfiguring skin lesions to fatal visceral disease affecting the spleen, liver, and bone marrow. The parasites responsible, including Leishmania donovani, L. infantum, L. amazonensis, and L. braziliensis, are transmitted by sand flies and exist in distinct life-cycle stages: a motile promastigote form in the insect vector and an intracellular amastigote form that survives inside mammalian macrophages. Existing drugs such as miltefosine, amphotericin B, and pentavalent antimonials fall short of ideal profiles, and the clinical pipeline, while recently invigorated by candidates like LXE408 and DNDI-6174 developed through the Drugs for Neglected Diseases initiative, still needs new chemotypes with broad-spectrum coverage.

The research builds on a rational biological premise. Trypanosomatid parasites, the family that includes Leishmania, Trypanosoma cruzi, and Trypanosoma brucei, depend heavily on polyamine metabolism. Polyamines such as spermidine stabilize DNA, support translation, and underpin stress adaptation and cell proliferation. Critically, spermidine is also required to build trypanothione, a unique dithiol that replaces glutathione as the parasites’ major intracellular redox buffer. This trypanothione-dependent network is absent in mammalian cells, creating a pathogen-selective biochemical vulnerability. The clinical success of eflornithine, an inhibitor of ornithine decarboxylase, has long validated polyamine metabolism as a druggable target, and prior diamine-based scaffolds, from aminooxy analogues to N-arylspermidines, have shown antileishmanial activity.

Guided by this framework, the team, led by Guillermo R. Labadie of the Instituto de Química Rosario in Argentina, had previously assembled a first-generation library of thirty N,N′-disubstituted aliphatic diamines. Those compounds, made by one-pot reductive amination of aliphatic diamine linkers with substituted benzaldehydes, showed promising activity against the extracellular stages of T. cruzi, T. brucei, and L. donovani, and some later proved active against the clinically relevant intracellular stage of T. cruzi. The new study extends that chemistry into a second generation of fifty-two analogues, systematically varying both the length of the diamine linker, from three to twelve carbon atoms, and the identity of the terminal aromatic groups.

The synthetic design was deliberate. A 4-isopropyl substituent was introduced to probe the effect of increased hydrophobicity relative to the oxygenated benzyl groups explored earlier. A 4-nitrobenzaldehyde derivative was included to test whether a strong electron-withdrawing group might mimic the behavior of nitro-containing antiparasitic drugs such as nifurtimox, benznidazole, and fexinidazole, whose bioactivation in trypanosomatids relies on type I nitroreductases absent from mammalian hosts. Bulky aromatic systems, including 2-naphthyl and biphenyl aldehydes, were incorporated to examine the influence of extended π-surfaces and steric demand, while heteroaromatic aldehydes based on furan and pyrrole were chosen to modulate polarity and electronic distribution. Finally, a focused series of twelve derivatives built on para-halogenated and para-methyl benzaldehydes with C8, C10, and C12 linkers was synthesized to refine the structure–activity relationship around the most promising long-chain analogues.

Biological screening revealed clear patterns. Forty-five of the fifty-two compounds showed pIC50 values above 5.0 against at least one parasite species, and several exceeded pIC50 6.0, corresponding to submicromolar potency. The parasites differed in susceptibility: T. brucei was the most sensitive, followed by T. cruzi, with L. donovani generally less responsive. Sixteen compounds outperformed the reference drug nifurtimox against T. brucei, and seventeen did so against T. cruzi. Against L. donovani, only compound 3i, a biphenyl-substituted diamine with a three-carbon linker, surpassed amphotericin B, though 57 percent of the library beat pentamidine. The most active compound overall against T. brucei was 3i, with a pIC50 of 7.96 and a selectivity index of 591 relative to Vero cells.

Structure–activity analysis highlighted the interplay between linker length and aromatic substitution. Bulkier aromatic groups, such as naphthyl and biphenyl, tended to favor activity in analogues with shorter linkers of six carbons or fewer, while longer C10 and C12 linkers generally improved activity in the unsubstituted benzyl, para-halogenated, nitro, and heteroaromatic series. Within the para-fluoro series, activity increased consistently with chain length, and compound 12m, bearing a twelve-carbon linker, emerged as the most potent, with pIC50 values of 6.36 against L. donovani, 6.80 against T. cruzi, and 7.17 against T. brucei. The authors note that solubility limitations affected several of the bulkier derivatives, particularly in the T. cruzi and T. brucei assays, and caution that apparent trends in those series should be interpreted carefully.

Based on potency, selectivity, and chemical diversity, nine representative hits were advanced for expanded evaluation against L. amazonensis, L. braziliensis, and L. infantum, covering both promastigote and intracellular amastigote stages in a macrophage infection model. The results were striking: nearly all compounds showed pIC50 values above 6.0 against the amastigote stage across the three species, with generally higher potency against this clinically relevant intracellular form than against promastigotes. Compound 8e, a C8 linker bearing 3-methoxy-4-benzyloxy substituents, achieved the highest activity against L. amazonensis amastigotes at pIC50 7.70 and L. braziliensis amastigotes at pIC50 7.46. Compound 12m was strongest against L. infantum amastigotes at pIC50 7.40. The nitro analogue 10g showed a striking species-dependent profile, with pIC50 values of 7.40 against L. amazonensis and 7.10 against L. infantum but markedly reduced activity below 5.40 against L. braziliensis, a difference the authors speculate may reflect variation in nitroreductase expression or other intrinsic determinants of nitro-compound susceptibility, though they emphasize this hypothesis requires dedicated mechanistic study.

Selectivity was assessed against both Vero cells and bone-marrow-derived macrophages, the same host cells used in the intracellular assays. All compounds showed selectivity indices above 10 in Vero cells except 10g and 4e against L. braziliensis. In the more physiologically relevant BMDM counterscreen, compounds 8c, 12a, and 12m maintained selectivity indices above 10 against amastigotes of all three Leishmania species. The authors note that higher cytotoxicity in primary macrophages compared with immortalized epithelial cells likely reflects intrinsic biological differences, including the high endocytic and phagocytic activity of macrophages that may increase intracellular compound exposure. Combining potency, selectivity, and predicted physicochemical properties calculated with the SwissADME platform, compound 12a, the unsubstituted benzyl analogue with a twelve-carbon linker, emerged as the most balanced lead, complying with Lipinski’s rule and showing moderate predicted aqueous solubility. Compound 12m, with its para-fluoro substitution that may confer improved metabolic stability, represents an attractive complementary lead.

The authors acknowledge that the intracellular infection model cannot fully distinguish direct antiparasitic killing from host cell-mediated effects, and that further mechanistic work will be needed. They also note that for cutaneous leishmaniasis, topical administration could offer an alternative to oral delivery, potentially mitigating concerns about the poor aqueous solubility predicted for several analogues. Future optimization will focus on reducing lipophilicity while preserving potency and selectivity, through the incorporation of additional polar functional groups or a reduction in the aromatic content of the scaffold. For now, the study delivers a validated, synthetically accessible chemotype with demonstrated broad-spectrum activity against multiple Leishmania species and a clear structural map to guide the next round of lead optimization.

Subject of Research: Discovery of second-generation N,N′-disubstituted aliphatic diamines as potent antileishmanial hit compounds

Article Title: Second-generation N,N′-disubstituted aliphatic diamines: discovery of potent hits for multi-species leishmaniasis treatment

Article References: Recio-Balsells, A. I., Panozzo-Zenere, E. A., Coser, E. M., Ferreira, B. A., Coelho, A. C., Wilkinson, S. R., Tekwani, B. L., & Labadie, G. R. (2026). Second-generation N,N′-disubstituted aliphatic diamines: discovery of potent hits for multi-species leishmaniasis treatment. Frontiers in Chemical Biology, 5, Article 1888764. https://doi.org/10.3389/fchbi.2026.1888764

Image Credits: AI Generated

DOI: 10.3389/fchbi.2026.1888764

Keywords: leishmaniasis, N,N′-disubstituted diamines, antiparasitic drug discovery, trypanosomatids, polyamine metabolism, structure-activity relationship, Leishmania amazonensis, Leishmania braziliensis, Leishmania infantum, intracellular amastigotes, neglected tropical diseases, medicinal chemistry

The team’s strategy departs from the standard playbook. Rather than hunting for yet another molecule that binds the bacterial RNA polymerase active site, they targeted the protein-protein interaction between RNA polymerase and CarD, an essential transcription factor that the pathogen cannot survive without. Rifampin, the cornerstone of tuberculosis therapy since the 1980s, works by binding RNA polymerase directly and shortened treatment from 18 months to six to nine months when it entered regimens alongside isoniazid, pyrazinamide, and ethambutol. But rifampin carries well-documented liabilities: long treatment times, activation of the human pregnane X receptor, which induces Cyp3A4 and complicates HIV-tuberculosis coinfection therapy, and the steady accumulation of resistance mutations within RNA polymerase itself. Newer agents such as bedaquiline, approved by the FDA for multidrug-resistant tuberculosis, and delamanid, authorized in Europe but not yet by the FDA, already show acquired resistance, driven in part by mutations in the transcriptional regulator mmpR. Since 2000, only five first-in-class antibiotics have reached the market, and none of them target M. tuberculosis.

CarD offers a different kind of leverage. After bacterial RNA polymerase binds a promoter and forms the closed complex, the DNA must unwind to generate the open promoter complex, a step widely considered rate-limiting for gene expression. CarD binds to that open complex and stabilizes it, boosting transcription from promoters with short-lived open complexes and dampening transcription from promoters whose open complexes persist longer. Genetic experiments have underscored how indispensable this function is: attempts to delete the carD gene from the M. tuberculosis genome were lethal, and conditional depletion of CarD left the bacterium hypersensitive to reactive oxygen species and rifampin, unable to replicate and persist in mice. Most mutations introduced into CarD through homologous recombination were not tolerated, suggesting that even small structural perturbations cripple the protein. Recent cryo-electron microscopy structures of M. tuberculosis transcription complexes now include CarD, giving medicinal chemists a structural map of the interaction they hope to disrupt.

To monitor the CarD-RNA polymerase interaction in a screening-compatible format, the researchers engineered cysteine mutations into CarD and labeled it with the BODIPY-FL fluorophore. In their fluorescence polarization assay, labeled CarD binds to a complex of RNA polymerase and a native rrnAP3 promoter DNA fragment, and the resulting increase in polarization signal reports on that association. Because both the RNA polymerase and DNA contacts are required for CarD’s highest-affinity binding, the N-terminal and C-terminal domains of CarD and the linker between them all represent potential drug-binding sites. Structural analysis of the CarD C-terminal domain has revealed several potentially druggable pockets, some adjacent to residues critical for promoter DNA interaction and others in the interdomain region, where a small molecule could conceivably freeze the protein in a conformation incompatible with function.

The new study extended an earlier screen of roughly 24,000 compounds to a much larger chemical space. First, the team screened a 4,719-compound drug repurposing library at 20 micromolar to benchmark assay performance. Several compounds initially appeared active, but a substantial fraction showed fluorescence interference, and after filtering, only a small number met hit criteria. One confirmed hit was fidaxomicin, a known RNA polymerase inhibitor that the group had previously characterized as indirectly blocking CarD binding. Notably, the screen did not flag rifampin, which inhibits RNA polymerase without affecting CarD binding, a result the authors cite as validation of the assay’s specificity. Among the apparent hits, the peptide GO-203 looked potent in the primary assay, but follow-up characterization revealed atypical dose-response behavior and fluorescence artifacts. Fluorescence intercalator displacement assays showed that GO-203 and its polycationic R9-containing fragment bind DNA directly, meaning the apparent inhibition arose from DNA binding rather than genuine disruption of the CarD-RNA polymerase interface.

That lesson shaped the main campaign. The team screened 82,516 small molecules from the DART Neurosciences collection, cherry-picked for drug-like properties, each at 20 micromolar in 384-well format. The screen achieved an overall Z-factor of 0.62 and an average per-plate Z-factor of 0.78, values indicating a robust high-throughput assay. Hit selection was deliberately aggressive: compounds needed millipolarization values at least three standard deviations below the negative control and at or above the positive control, yielding 1,242 candidates. Exclusion of compounds exceeding 110 percent of the positive control signal, those with excessive parallel fluorescence intensity, and those flagged for toxicity, chemical reactivity, promiscuity, or PAINS substructures narrowed the pool to 1,054. A counter screen that read plates before DNA addition, designed to catch compounds that fluoresce or quench on their own, further reduced the list to 341, and an intensity threshold cut it to 326 compounds advancing to concentration-response testing.

Concentration-response curves applied additional filters, including molecular weight above 200, Hill slopes below 2, and IC50 values under 100 micromolar, leaving 232 compounds for cluster analysis. Using DataWarrior with Tanimoto similarity clustering at a 79 percent threshold, the team identified four main clusters with average pIC50 values above 4.5, corresponding to IC50 values around 30 micromolar, plus 204 singletons. Fresh powder samples of 22 compounds from four clusters were purchased for reconfirmation. Fluorescence interference proved a persistent obstacle: IC50 values had to be calculated from concentration ranges free of interference, eight compounds yielded values with defined confidence intervals, seven had undefined confidence limits, and six were excluded outright. Eleven purchased analogs from the two most promising clusters showed no significant activity, a sobering result for conventional lead optimization.

Orthogonal counter screens helped clarify what the hits were not doing. In fluorescence intercalator displacement assays using a 60-base-pair lacUV5 duplex and ethidium bromide, none of the compounds displaced the DNA intercalator, ruling out nonspecific DNA binding. In a plasmid-based in vitro transcription assay that detects RNA transcripts bearing 12 repeats of the malachite green aptamer, none of the compounds inhibited RNA polymerase activity. Together, these results support a mechanism distinct from DNA binding or direct polymerase inhibition, consistent with disruption of the CarD-RNA polymerase interaction, although the authors are careful to note that direct binding to CarD or the interface has not yet been demonstrated.

Antibacterial testing added a layer of complexity. Minimum inhibitory concentrations against M. tuberculosis H37Rv, measured by the microplate alamar blue assay, ranged from 1.4 micrograms per milliliter, about 4.3 micromolar, for compound 2B-d to above 100 micrograms per milliliter for several others. Minimum bactericidal concentrations were consistently above 100 micrograms per milliliter for nearly all compounds, indicating limited killing at the tested doses. Compound 2B-d stood out with an MIC90 of 1.4 micrograms per milliliter and a Vero cell TC50 of 24 micromolar, yielding a selectivity index of 5.6, a moderate but real safety margin. Intriguingly, 2B-d showed weak biochemical potency in the fluorescence polarization assay, with an IC50 of 65 micromolar, despite strong whole-cell activity, a discrepancy the authors attribute to possible differences in permeability, efflux, or target accessibility, and they cannot yet rule out that the whole-cell activity arises from mechanisms unrelated to CarD-RNA polymerase inhibition.

Structurally, the most reliable hits from Clusters 1 and 2A share a striking chemotype: two bicyclic heterocycles connected through a methylene linker attached to the nitrogen of a tetrahydropyridine ring, with similar conformational flexibility and planarity. Within Cluster 1, a single methyl substitution at the R2 position lowered the IC50 roughly threefold to 7 micromolar, while enlarging the R1 substituent or replacing the pyrimidine with a carbocyclic ring proved detrimental. Clusters 3 and 4, built around 2-methoxy-5-aminopyridine amide and benzyl-piperazinyl-pyridinamine scaffolds respectively, were largely sidelined by fluorescence interference. The authors argue that the combined 15-compound chemotype from Clusters 1 and 2A, in which eight members have IC50 values below 50 micromolar and six show MIC90 values below 100 micrograms per milliliter, provides a starting point for structure-activity exploration, though they acknowledge that modest potency, fluorescence interference, and weak analog activity currently preclude conventional optimization. Future work will need NMR spectroscopy and X-ray crystallography to confirm direct target engagement, define the binding site, and establish whether these molecules act on CarD itself or on the CarD-RNA polymerase interface, with polar substitutions at the R positions and extended methylene linkers flagged as promising directions. CarD homologues also appear in Chlamydiae, Firmicutes, and Spirochaetes, pathogens responsible for chlamydia, Clostridioides difficile colitis, and Lyme disease, so a validated inhibitor could eventually reach well beyond tuberculosis.

Subject of Research: High-throughput screening for inhibitors of the CarD-RNA polymerase protein-protein interaction in Mycobacterium tuberculosis

Article Title: High-throughput screening to identify inhibitors of the MTB CARD•RNA polymerase protein-protein interaction

Article References: Velazquez, G. M., Sexton, J. Z., Franzblau, S. G., Shetye, G. S., Hossain, A., & Garcia, G. A. (2026). High-throughput screening to identify inhibitors of the MTB CARD•RNA polymerase protein-protein interaction. Frontiers in Tuberculosis, 4, Article 1937953. https://doi.org/10.3389/ftubr.2026.1937953

Image Credits: AI Generated

DOI: 10.3389/ftubr.2026.1937953

Keywords: tuberculosis, Mycobacterium tuberculosis, CarD, RNA polymerase, protein-protein interaction, high-throughput screening, fluorescence polarization, drug discovery, antibiotic resistance, drug repurposing, transcription, medicinal chemistry

The histamine receptor family offers a striking example of how a single small molecule can orchestrate profoundly different physiological outcomes depending on which of its four recognized receptor subtypes it engages. Histamine itself binds to all four receptor classes with nanomolar affinity, yet the cellular context of each receptor dictates vastly different consequences. At the H3 receptor, histamine functions predominantly as a neuromodulator, while at the H4 receptor it acts as a recruiter and modulator of immune cell behavior. This duality has made the receptor pair an attractive testing ground for medicinal chemistry programs that aim to disentangle central nervous system effects from peripheral inflammatory ones. The structural similarity between the two receptors, however, makes this disentanglement far from trivial, and it is precisely this challenge that scaffold hopping approaches are designed to address.

The concept of scaffold hopping, though formally named only in recent decades, has been an implicit part of medicinal chemistry practice since the earliest days of antihistamine development. The transition from first-generation ethanolamine antihistamines such as diphenhydramine to tricyclic phenothiazines like promethazine represented an early, if unintentional, exercise in changing the molecular framework while preserving the pharmacophoric elements needed for receptor binding. Subsequent refinements produced second-generation antihistamines with markedly reduced sedative liability, and the same structural exploration also yielded compounds with entirely different primary indications, including antipsychotic agents that retain antihistamine activity as a side effect. These historical examples illustrate a central principle: changing the scaffold can alter absorption, distribution, metabolism, and off-target profiles without necessarily abolishing the interaction with the intended receptor, provided the key binding features are retained.

For the H3 and H4 receptors specifically, the conserved amino acid residues that anchor the endogenous ligand provide a useful starting point for rational design. The negatively charged aspartate residue located in the third transmembrane helix, conventionally labeled Asp3.32, forms an ionic interaction with the protonated amine of histamine and of virtually all synthetic agonists and antagonists directed at these receptors. A second conserved residue, glutamate at position 5.46 in the fifth transmembrane helix, engages the imidazole ring of histamine through hydrogen bonding. Ligands that lack an imidazole group, such as the non-imidazole H3 antagonist FUB 661, must find alternative ways to occupy this region of the binding pocket or dispense with that interaction altogether, often compensating with additional hydrophobic or polar contacts elsewhere. Understanding which interactions are dispensable and which are essential is one of the central questions that structure-activity relationship studies attempt to answer.

The distinction between ligands that preferentially engage H3 versus H4 receptors has historically tracked with molecular shape and conformational flexibility. H3 receptor ligands tend to tolerate, and often benefit from, a degree of conformational freedom, with longer linker chains connecting the aromatic recognition element to the basic amine. This flexibility presumably allows the ligand to adopt binding poses that accommodate the slightly different geometry of the H3 orthosteric site. H4 receptor ligands, by contrast, are frequently more compact and rigid, with the pharmacophoric elements held in a tighter spatial arrangement. The prototypical H4 antagonist JNJ-7777120 exemplifies this compact architecture, and its high selectivity over H3 has made it a reference compound for the field. The observation that rigidifying or compacting a scaffold can shift selectivity toward H4, while extending and flexing it can favor H3, provides a practical design heuristic that the present work exploits systematically.

Ring opening as a scaffold hopping maneuver deserves particular attention because it occupies an intermediate position on the spectrum of structural change. Unlike wholesale heterocycle replacement, which can dramatically alter electronic properties and binding geometry, ring opening preserves much of the spatial relationship between substituents while introducing conformational freedom and often improving synthetic accessibility. When applied to a rigid bicyclic or fused-ring chemotype, ring opening converts a constrained framework into an acyclic analogue whose torsional angles can be probed systematically through homologation, that is, the stepwise insertion or removal of methylene units in the linker. Each homologation step shifts the distance between the aromatic group and the basic nitrogen, allowing the medicinal chemist to map the optimal spacing for receptor affinity with fine granularity.

Bioisosteric replacement, the third strategy employed in this study, complements the other two by addressing the electronic and hydrogen-bonding dimensions of ligand-receptor recognition. Replacing an amide linker with a urea, or vice versa, changes the hydrogen-bond donor and acceptor pattern while keeping the overall molecular dimensions roughly constant. The literature on H4 receptor ligands offers instructive cautionary examples here: urea derivatives designed to preserve the hydrogen-bond donor present in the indole NH of JNJ-7777120 analogues have generally shown disappointing H4 affinity, suggesting that the precise geometry and context of that donor, not merely its presence, matters for productive binding. Amide-linked analogues remain comparatively underexplored, which makes the systematic evaluation of anilide and benzylamide scaffolds in this work a meaningful contribution to filling that gap in the SAR landscape.

The reported affinities themselves tell a coherent story about how these structural manipulations played out empirically. Within the LINS05-derived set, which descends from more flexible chemotypes, the best compound achieved a pKi of 6.27 at H3, corresponding to a submicromolar dissociation constant, with measurable selectivity over H4. Within the LINS01-derived set, built from a more compact starting point, most compounds reached nanomolar H3 affinity, and the standout compound 11 attained a pKi of 7.02 with good H3 selectivity. Interestingly, the same series also yielded compound 14, which inverted the selectivity profile, showing its best affinity at H4 with a pKi of 5.23 while retaining a pKi of 6.27 at H3. This inversion within a single congener series is scientifically valuable because it demonstrates that relatively modest structural changes can redirect selectivity between two closely related paralogs, offering a starting point for the design of H4-selective probes from a chemotype that historically favored H3.

It is worth contextualizing what these pKi values mean in practical terms. A pKi of 7.02 corresponds to a Ki of roughly 95 nanomolar, while a pKi of 6.27 corresponds to approximately 540 nanomolar. These affinities fall short of the best-in-class H3 antagonists reported in the literature, some of which achieve low-nanomolar or even subnanomolar binding, and they are well below the pKi of 8.3 exhibited by JNJ-7777120 at H4. However, the purpose of an exploratory scaffold hopping campaign is not typically to produce a clinical candidate on the first pass but rather to establish that a new framework can engage the target at all and to generate a preliminary SAR map that guides subsequent optimization. Viewed through that lens, the identification of multiple novel frameworks with measurable, reproducible affinity constitutes a successful outcome, and the nanomolar H3 affinity of compound 11 provides a credible launching point for affinity maturation.

The computational component of the study, molecular docking, serves as the interpretive bridge between synthetic chemistry and receptor pharmacology. Docking the synthesized compounds into homology or crystallographic models of H3 and H4 allows the researchers to propose specific interaction patterns, such as the salt bridge between the protonated amine and Asp3.32, aromatic stacking or hydrophobic contacts within the lipophilic pocket, and hydrogen bonds involving the linker region. By comparing docked poses across the congener series, one can rationalize why a particular homologue outperforms its neighbors, or why a bioisosteric replacement diminished affinity. Such rationalizations remain hypotheses until tested by further synthesis or by higher-resolution structural methods, but they convert raw affinity data into actionable design principles for the next synthetic cycle.

Looking forward, several avenues naturally follow from this work. The most potent H3-selective compound invites optimization through additional homologation and substituent variation on the aromatic ring, with the goal of pushing affinity into the low-nanomolar range while maintaining or improving selectivity. The H4-preferring compound 14 suggests that the LINS01-derived scaffold, despite its origins, can be steered toward the immune-cell receptor, and targeted modifications to the linker region might amplify this preference. Beyond affinity optimization, subsequent studies would need to characterize functional activity, determining whether these ligands act as neutral antagonists, inverse agonists, or partial agonists, since H3 and H4 receptors are constitutively active and inverse agonism carries distinct therapeutic implications. Pharmacokinetic properties, including brain penetration for H3-directed candidates and metabolic stability for both directions, will ultimately determine whether any of these novel chemotypes can progress beyond the exploratory stage. In the meantime, the systematic SAR data generated here enriches the collective knowledge base for a receptor pair whose therapeutic potential, spanning narcolepsy, cognitive disorders, obesity, and inflammatory disease, continues to motivate sustained medicinal chemistry attention.

Subject of Research: Exploratory scaffold hopping strategies led to identification of novel histamine H3 and H4 receptor ligands

Article Title: Exploratory scaffold hopping strategies led to identification of novel histamine H3 and H4 receptor ligands

Article References: Lopes, F. B., Mönnich, D., Fernandes, G. A. B., Pockes, S., & Fernandes, J. P. S. (2026). Exploratory scaffold hopping strategies led to identification of novel histamine H3 and H4 receptor ligands. Frontiers in Drug Discovery, 6, Article 1944403. https://doi.org/10.3389/fddsv.2026.1944403

Image Credits: AI Generated

DOI: 10.3389/fddsv.2026.1944403

Keywords: scaffold hopping, histamine H3 receptor, histamine H4 receptor, bioisosterism, structure-activity relationships, molecular docking, drug discovery, piperazine ligands, benzofuran derivatives, ligand efficiency, medicinal chemistry, radioligand binding assays

Tuberculosis remains the leading cause of death from infectious diseases worldwide, with an estimated 10.6 million new cases and 1.6 million associated deaths each year. The disease is caused by Mycobacterium tuberculosis, a bacterium that forms granulomatous lesions in the lungs and can exploit the body’s own protective structures to spread. Chronic pulmonary aspergillosis, a progressive fungal infection acquired through inhalation of conidia, affects an estimated 1.8 million people annually. Meanwhile, Escherichia coli has become the pathogen associated with the highest mortality rate linked to antimicrobial resistance, ranking in the highest quartile of the WHO’s 2024 Bacterial Priority Pathogens List. The researchers chose quinoline derivatives because this class of aromatic nitrogen heterocycles has demonstrated antimicrobial, antifungal, and antituberculosis properties, making them privileged structures in medicinal chemistry capable of modulating multiple biological targets.

The four compounds studied, designated QNL1 through QNL4, are derivatives of 1,4-dihydro-4-oxo-quinoline-3-carbohydrazide. QNL1 and QNL2 carry a chlorine atom at carbon 7 of the quinoline ring, while QNL3 and QNL4 have it at carbon 6. The phenyl ring attached through the carbohydrazide linker bears either two methoxy groups at positions C3 and C4 (QNL1 and QNL3) or three methoxy groups at C3, C4, and C5 (QNL2 and QNL4). These subtle differences in halogen position and methoxy substitution pattern proved to have measurable consequences for electronic behavior, molecular polarity, and predicted biological activity.

To characterize the electronic structure of each derivative, the team employed Density Functional Theory calculations using the B3LYP hybrid functional and the 6-311++G(d,p) basis set, implemented in the ORCA 5.0.4 program. The molecules were optimized both in vacuum and in dimethyl sulfoxide (DMSO) solvent, with the Conductor-like Polarizable Continuum Model (CPCM) used to account for solvation effects. From the optimized geometries, the researchers extracted frontier molecular orbital energies, the HOMO-LUMO energy gap, electronegativity, ionization potential, electron affinity, chemical hardness, softness, electrophilicity index, and nucleophilicity index. These conceptual DFT descriptors provide a quantitative framework for understanding molecular reactivity and predicting how the compounds might behave in biological environments.

The geometric optimization revealed that none of the four molecules adopts a completely planar conformation. The quinoline nucleus itself remains nearly planar, with an average angular deviation of only 0.266 degrees between the fused rings, but significant conformational variations arise from rotation of the substituent groups. The researchers validated their computational approach by comparing calculated bond lengths and angles against crystallographic data for a related quinolinium compound. The calculated C8-C7 bond lengths were 1.452 angstroms in DMSO and 1.459 angstroms in vacuum, compared to an experimental value of 1.368 angstroms, with the difference attributed to the replacement of a hydrogen atom by a carbonyl group in the derivatives. Average deviations between calculated and experimental parameters ranged from 0.010 to 0.091 angstroms in vacuum and 0.005 to 0.084 angstroms in DMSO, confirming the reliability of the computational method.

Analysis of the frontier molecular orbitals showed that the HOMO isosurface is predominantly distributed over the methoxy-substituted benzene ring and the N’-methylidenoformohydrazide chain in all derivatives, regions associated with electron density donation during electrophilic attack. The position of the chlorine atom on the quinoline ring exerts little influence on the most reactive region, since the HOMO is not significantly localized over the quinoline portion. However, the number of methoxy groups plays a critical role: as methoxy substitution increases, electronic density disperses more homogeneously over the benzene ring, reducing susceptibility to localized chemical attack. In DMSO, the solvent’s high dielectric constant spreads the HOMO over a broader region of the molecule and lowers its energy. The LUMO, conversely, is distributed mainly over the quinoline region in vacuum, with derivatives bearing more methoxy groups showing lower LUMO energies and greater capacity to accept electron density.

The ADMET evaluation employed multiple computational platforms including SwissADME, ADMETlab 3.0, admetSAR 3.0, pkCSM, Pred-hERG 5.0, StopTox, and the ADMET Prediction Service from the Laboratory of Molecular Modeling. QNL1 and QNL3 emerged as the leading compounds, both achieving oral bioavailability scores of 0.55 and demonstrating high intestinal absorption exceeding 95 percent. Their Caco-2 permeability values of approximately -4.92 in units of 10⁻⁶ cm/s indicate intermediate membrane penetration. Both compounds share identical molecular weights of 385.08 g/mol, topological polar surface areas of 92.78 square angstroms, and hydrogen bond donor counts of 2. Their logP values of 2.76 and 2.86 reflect a favorable balance between hydrophilic and lipophilic characteristics conducive to passive membrane diffusion.

Toxicity predictions revealed low cardiotoxic risk for both lead compounds, with hERG channel inhibition probabilities of approximately 0.08 for QNL1 and 0.06 for QNL3. The subtle difference in cardiotoxic risk between the two was attributed to the shift in chlorine position from ortho to meta on the quinoline ring. Both compounds showed moderate potential for CYP3A4 inhibition and moderate risk for drug-induced liver injury, warranting further experimental investigation. Acute toxicity predictions indicated low toxicity via inhalation, oral, and dermal routes, though both compounds showed a 65 percent probability of causing eye irritation or corrosion. The AMES toxicity test produced the highest predicted probability among all toxicological parameters evaluated, suggesting potential for DNA damage that must be confirmed experimentally before these compounds can advance.

Virtual target prediction using SwissTargetPrediction identified vascular endothelial growth factor receptor 2 (KDR) as the primary biological target for both QNL1 and QNL3, with association scores of 1300 and 1447 respectively. KDR is a high-affinity receptor tyrosine kinase crucial for angiogenesis and vascular permeability. In tuberculosis, granuloma formation creates local hypoxia that drives peripheral angiogenesis, and modulating the VEGF pathway may improve granuloma perfusion and reduce bacterial spread. The kinase class dominated the predicted target profile, increasing from 56 percent of predicted targets for QNL1 to 60 percent for QNL3, suggesting that the latter compound may exhibit greater selectivity while maintaining its primary mechanism of action.

The study concludes that QNL3 represents the priority candidate for further development as an oral drug, owing to its superior balance between systemic distribution and cardiovascular safety compared to QNL1. While QNL1 exhibits favorable physicochemical properties for absorption, QNL3’s metabolic profile and lower predicted cardiotoxic risk position it ahead in the ADMET framework. The preservation of pharmacophore characteristics across both lead compounds suggests structural elements compatible with interaction with VEGFR-2, justifying their inclusion in comparative analyses and additional screening. The researchers emphasize that these findings contribute to the rational design of new therapeutic strategies against tuberculosis, aspergillosis, and bacterial infections, highlighting the importance of integrating quantum mechanical calculations with predictive pharmacokinetic modeling in early-stage drug discovery.

Subject of Research: Computational mapping of electronic structure and ADMET properties of halogenated quinoline derivatives as potential antimicrobial and antituberculosis drug candidates

Article Title: Mapping the electronic and biological landscape of halogenated aryl quinoline derivatives via computational approaches

Article References: Sales, M. A., do Nascimento Gonçalves, C., dos Santos, A. L. S., da Rocha, M. N., Marinho, M. M., & Marinho, E. S. (2026). Mapping the electronic and biological landscape of halogenated aryl quinoline derivatives via computational approaches. Discover Chemistry, 3(1), Article 436. https://doi.org/10.1007/s44371-026-00886-0

Image Credits: AI Generated

DOI: 10.1007/s44371-026-00886-0

Keywords: quinoline derivatives, DFT calculations, ADMET prediction, tuberculosis, drug discovery, KDR receptor, virtual screening, medicinal chemistry, antimicrobial resistance, hERG cardiotoxicity, molecular orbital analysis, oral bioavailability