The study, published in BMC Infectious Diseases, drew on throat swab samples collected from 34,404 pediatric patients aged 18 years or younger who presented with respiratory symptoms at the Affiliated Women and Children’s Hospital of Ningbo University. Rather than relying on a single targeted test, the laboratory team used multiplex polymerase chain reaction, a technique that amplifies and identifies the genetic material of several pathogens simultaneously, to screen every sample for 13 common viral and atypical bacterial respiratory pathogens. Demographic details, pathogen identities and the dates on which samples were collected were then retrieved from the hospital’s laboratory database and analyzed together to reveal who was infected, with what, and when.

The headline number from the surveillance effort is an overall pathogen positivity rate of 69.14 percent, meaning that roughly seven in ten children tested carried detectable genetic evidence of at least one of the pathogens on the panel. That figure underscores how densely pathogenic material circulates among symptomatic children and illustrates the value of broad molecular panels: many of these infections would be difficult to distinguish clinically, since fever, cough and wheezing can be produced by any of a dozen different agents. Multiplex detection allows epidemiologists to see the true composition of that microbial mix rather than inferring it from symptoms alone.

Within that mix, three pathogens stood out. Mycoplasma pneumoniae, an atypical bacterium that lacks a cell wall and attaches itself to the lining of the respiratory tract, was detected in 26.94 percent of the tested children, making it the leading cause of positive findings. Human rhinovirus, the virus best known as the chief culprit behind the common cold, came second at 16.29 percent. Human adenovirus, a DNA virus capable of causing everything from pharyngitis to pneumonia, ranked third at 9.00 percent. The prominence of Mycoplasma pneumoniae is particularly notable because, as an atypical bacterium, it does not respond to the beta-lactam antibiotics often prescribed empirically for respiratory complaints, so knowing that it dominates locally can shape more rational treatment decisions.

The analysis went beyond simple prevalence counts to ask whether pathogen positivity differed across patient groups. The researchers report significant differences in positivity rates between the sexes and across age groups, indicating that the burden of specific respiratory pathogens is not distributed evenly among children. Such demographic patterns matter for clinical practice: if certain age brackets carry a disproportionately high share of detections, pediatricians can calibrate their index of suspicion, and laboratories can anticipate demand for testing among particular populations. Age-structured susceptibility is also a key input for modeling how respiratory pathogens spread through households and schools, where mixing patterns differ sharply from those of adult populations.

Seasonality, a signature feature of respiratory disease that was famously disrupted during the height of the COVID-19 pandemic, re-emerges clearly in the Ningbo data. The study documents evident seasonal variation for certain pathogens, with detection rates rising and falling across the two calendar years of surveillance. Tracking these rhythms is more than an academic exercise. Hospitals can use seasonal profiles to anticipate surges in admissions, stock appropriate diagnostics and therapeutics, and time public health messaging. The post-COVID period offers a natural experiment in how respiratory pathogen ecology rebounds when masking, distancing and reduced mixing recede, and datasets like this one provide the ground truth against which such rebound theories can be tested.

Coinfection emerged as a substantial feature of the pediatric disease landscape. Among the samples that tested positive for at least one pathogen, 19.85 percent harbored more than one, with dual infections representing the most common configuration. Coinfections complicate both biology and bedside care. On the biological side, one pathogen can damage the airway epithelium in ways that facilitate the entry or proliferation of another, potentially deepening disease severity. On the clinical side, a positive result for a common, often mild virus such as rhinovirus does not rule out a concurrent bacterial infection requiring antibiotics. Multiplex panels make such mixed infections visible, which single-pathogen testing would leave hidden.

The authors, a team spanning the hospital’s clinical laboratory, pediatrics department and a municipal key laboratory, frame the findings as an epidemiological reference for managing pediatric respiratory infections in the post-COVID-19 era. Their conclusions highlight the significant roles of Mycoplasma pneumoniae, human rhinovirus and human adenovirus in children in Ningbo and underscore the need for continued surveillance. Sustained monitoring is precisely what allows health systems to detect shifts in pathogen dominance, spot unusual out-of-season activity and respond to outbreaks before they overwhelm pediatric wards. Given that respiratory pathogens can change their circulation patterns within a single season, longitudinal datasets of this scale are among the most valuable tools available to public health authorities.

Methodologically, the study’s strengths lie in its sample size and its systematic approach. More than 34,000 specimens tested over 24 consecutive months with a standardized 13-pathogen molecular panel provide a resolution that smaller, shorter studies cannot match. The retrospective design has inherent limits, of course: it captures children who presented to one hospital with respiratory symptoms, so the findings describe a clinical population rather than the community at large, and throat swabs may vary in sensitivity across pathogens and disease stages. The researchers note that the work used non-identifiable data extracted under an ethics approval and informed consent waiver from the hospital’s institutional review board, in line with the Declaration of Helsinki.

For the wider scientific and clinical community, the Ningbo study adds a detailed post-pandemic datapoint to a growing international effort to understand how respiratory pathogen epidemiology reorganized after COVID-19. Questions remain open about whether Mycoplasma pneumoniae’s leading position reflects a genuine rebound of that bacterium after years of suppressed transmission, a shift in immunity profiles among children who grew up during the pandemic, or local factors specific to eastern China. Continued multi-season, multi-site surveillance, ideally with consistent molecular panels, will be needed to separate these explanations. In the meantime, the study offers pediatricians a clear message: in the post-COVID era, the causes of childhood respiratory infection are numerous, frequently mixed, and follow seasonal scripts that are once again worth learning by heart.

Subject of Research: Prevalence of viral and atypical bacterial respiratory pathogens in pediatric acute respiratory infections in post-COVID-19 Ningbo, China

Article Title: Prevalence of viral and atypical bacterial respiratory pathogens among pediatric patients with acute respiratory infections after COVID-19 in Ningbo, China

Article References: Zhou, C., Lu, W., Chen, Y., Hu, Q., Zhu, L., & Liu, W. (2026). Prevalence of viral and atypical bacterial respiratory pathogens among pediatric patients with acute respiratory infections after COVID-19 in Ningbo, China. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14531-9

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14531-9

Keywords: Mycoplasma pneumoniae, human rhinovirus, human adenovirus, pediatric respiratory infections, multiplex PCR, coinfections, seasonal trends, COVID-19 pandemic, Ningbo China, epidemiology, BMC Infectious Diseases, surveillance

The research, led by Hafs Essaadi and colleagues at Mohammed V University in Rabat, Morocco, together with collaborators at the Mohammed VI Center for Research and Innovation and UM6SS, focused on the viral 3C protease, an enzyme designated 3Cpro that is indispensable to the rhinovirus life cycle. After the virus infects a cell, its genome is translated into a single long polyprotein that must be cleaved into functional viral proteins, and the 3C protease performs most of these cuts. Because the catalytic architecture of 3Cpro is highly conserved across human rhinovirus species, a molecule that disables it could in principle suppress a wide range of rhinovirus strains, making the enzyme an attractive therapeutic target.

To find candidate inhibitors, the team screened a library of 49,437 compounds against the 3C protease of human rhinovirus species C, the rhinovirus group most frequently associated with severe asthma exacerbations. The docking calculations were carried out with AutoDock Vina, a widely used molecular docking engine that predicts how small molecules orient themselves within a protein binding pocket and estimates the binding affinity of each pose. The researchers then applied ADMET-based prioritization, filtering the top-scoring hits for acceptable absorption, distribution, metabolism, excretion, and toxicity profiles, a step designed to weed out compounds that might bind well in silico but fail as drug candidates.

The docking analysis converged on two lead compounds that occupied the catalytic pocket of the protease in orientations predicted to be highly favorable. Both molecules formed stabilizing interactions with key residues of the active site, including His40, Glu71, and Cys147, the latter being the catalytic cysteine that sits at the heart of the enzyme’s cleavage chemistry. When compared with rupintrivir, the best-known experimental rhinovirus 3C protease inhibitor, which functions as an irreversible covalent inhibitor, the two new compounds achieved comparable or better engagement of the catalytic site without forming covalent bonds, a property that could translate into improved safety profiles.

Docking scores alone are a crude measure of binding, so the team subjected the protein-ligand complexes to molecular dynamics simulations lasting 200 nanoseconds each, allowing the atoms to move under realistic physical forces and revealing whether the predicted binding poses remain stable over time. Both compounds stabilized the protease relative to the unbound, or apo, form of the enzyme. Compound 1 produced the lowest protein root-mean-square deviation, holding the overall structure of the protease at 1.21 plus or minus 0.22 angstroms from its starting conformation, while compound 2 yielded the lowest root-mean-square fluctuation for the critical Cys147 residue, at just 0.48 angstroms, indicating that the catalytic nucleophile itself was held unusually rigid in the presence of this ligand.

Ligand mobility within the binding pocket provided further evidence of durable binding. Over the course of the simulations, compound 1 displayed a ligand RMSD of 1.49 plus or minus 0.78 angstroms and compound 2 a value of 2.01 plus or minus 0.39 angstroms, whereas rupintrivir wandered considerably more, with a ligand RMSD of 4.83 plus or minus 0.89 angstroms. Lower ligand RMSD values indicate that a molecule stays anchored in its original binding pose rather than drifting or partially exiting the pocket, suggesting that the two new candidates maintain more persistent contact with the active site than the reference inhibitor under dynamic conditions.

To quantify binding strength more rigorously, the researchers applied the MM/PBSA method, which combines molecular mechanics energies with solvation models to estimate the free energy of binding from simulated trajectories. Both leads outperformed rupintrivir on this metric: compound 1 achieved an effective binding energy of minus 23.59 plus or minus 6.87 kilocalories per mole, and compound 2 reached minus 25.25 plus or minus 5.75 kilocalories per mole, compared with minus 19.43 plus or minus 4.46 kilocalories per mole for rupintrivir. The team complemented these calculations with free energy landscape analysis, a technique that maps the conformational states sampled during simulation and identifies the most thermodynamically stable configurations of each complex, providing an additional layer of confidence that the observed binding modes represent genuine energetic minima rather than transient artifacts.

The significance of a non-covalent mechanism deserves emphasis. Rupintrivir, which reached phase II clinical trials as a nasal spray, irreversibly modifies the catalytic cysteine, and while this reactivity underlies its potency, covalent inhibitors can raise concerns about off-target modification of human enzymes that rely on similar cysteine chemistry. Compounds that achieve strong binding through reversible, non-covalent interactions, as the two leads reported here appear to do, may offer a wider therapeutic window. The ADMET filtering applied during the study further suggests that the candidates were selected not only for potency but also for drug-like behavior, although the authors stress that computational predictions of this kind require experimental confirmation.

Indeed, the study stops short of laboratory validation, and the authors are explicit that compounds 1 and 2 should be regarded as promising candidates for further experimental testing rather than proven antivirals. Enzyme inhibition assays, antiviral activity measurements in infected cell cultures, and eventually pharmacokinetic and toxicity studies in vivo will be needed to determine whether the computational promise translates into real therapeutic value. The data generated during the study are available from the corresponding author upon request, and the work was supported in part by computational resources from the Pediatric Translational Clinical Research Unit.

Nevertheless, the study adds to a growing body of evidence that structure-based computational screening can accelerate antiviral discovery against rhinoviruses, a pathogen family that has historically frustrated drug developers because of its antigenic diversity. By anchoring the search on a conserved, essential enzyme and validating hits through a multi-layered pipeline of docking, long-timescale dynamics, free energy landscape mapping, MM/PBSA energetics, and ADMET profiling, the Moroccan team has delivered a shortlist of chemically tractable starting points. If subsequent experiments bear out the predicted potency of these molecules, the work could represent an early but meaningful step toward the first effective antiviral treatment for the infections that trigger many of the world’s asthma attacks and common colds.

Subject of Research: Computational discovery of non-covalent inhibitors targeting the human rhinovirus 3C protease

Article Title: Computational discovery of novel human rhinovirus 3 C protease inhibitors: molecular docking, dynamic simulations, free energy landscape, MMPBSA and ADMET analysis

Article References: Essaadi, H., Chourir, A., Kourou, J., Makhloufi, F., Hachlaf, O., Abidou, A., Boutayeb, S., Eljaoudi, R., Belyamani, L., Ibrahimi, A., Hakmi, M., & Hafidi, N. E. (2026). Computational discovery of novel human rhinovirus 3 C protease inhibitors: molecular docking, dynamic simulations, free energy landscape, MMPBSA and ADMET analysis. Molecular Diversity. https://doi.org/10.1007/s11030-026-11704-1

Image Credits: AI Generated

DOI: 10.1007/s11030-026-11704-1

Keywords: human rhinovirus, 3C protease, antiviral drug discovery, molecular docking, molecular dynamics simulations, MM/PBSA, free energy landscape, ADMET analysis, virtual screening, rupintrivir, common cold, asthma exacerbation