African Plant Compounds Emerge as Digital Leads Against River Blindness Parasite

Onchocerciasis, better known as river blindness, remains one of the most stubborn neglected tropical diseases on the planet. Caused by the filarial nematode Onchocerca volvulus and transmitted through the bites of female blackflies of the Simulium damnosum complex, the disease is a leading cause of preventable visual impairment and severe dermatological illness across endemic communities. According to the World Health Organization’s 2024 progress report, more than 99 percent of infected individuals live in sub-Saharan Africa and Yemen, and at least 252.3 million people required preventive chemotherapy with ivermectin in 2024 alone. Roughly 14.6 million infected people already suffer from skin disease, while 1.15 million have experienced vision loss. Against this backdrop, a new computational study has turned to the chemical treasures of Central African medicinal plants in search of the next generation of anti-filarial drug candidates.

The cornerstone of current onchocerciasis control is mass drug administration with ivermectin, a regimen recommended for ten to fifteen years. The drug is microfilaricidal, meaning it kills the larval stage of the parasite, but it does not eliminate the adult worms that continue to reproduce. Long-term annual treatment alone has proven insufficient to interrupt transmission in several foci, including parts of Cameroon where transmission has continued despite more than fifteen years of community-directed treatment with ivermectin. The 2025 verification of Niger as the first African country to eliminate onchocerciasis demonstrates that elimination is achievable, but it also underscores the urgent need for safe, macrofilaricidal alternatives that can shorten elimination timelines and counter emerging resistance or sub-optimal drug response in the remaining endemic areas.

Enter a team of researchers led by Maraf Mbah Bake of the University of Yaoundé I, working with collaborators in Cameroon, Germany, South Africa, Iraq and Spain. Writing in the journal Discover Chemistry, the team describes a systematic computational hunt for inhibitors of two detoxification enzymes from O. volvulus, using the ConMedNP library, a curated collection of roughly 3,500 secondary metabolites isolated from Central African medicinal plants. Their strategy combined ADMET-based filtering, tiered molecular docking, MMGBSA binding-energy rescoring, pharmacological activity prediction and 200-nanosecond molecular dynamics simulations, a pipeline designed to separate genuine binders from computational noise.

The molecular targets were the sigma-class and pi-class glutathione S-transferases of the parasite, known as Ov-GST1 and Ov-GST2. These enzymes conjugate glutathione to hydrophobic electrophiles, shielding the worm from oxidative damage and facilitating the excretion of xenobiotics, including drugs. Three GST isoforms have been characterized in O. volvulus, but the sigma and pi classes are particularly attractive because they underpin the parasite’s survival under oxidative stress. Crucially, the two isoforms differ structurally: Ov-GST1 possesses a larger, more solvent-exposed and flexible substrate-binding pocket, whereas Ov-GST2 has a smaller, more rigid cavity with greater substrate selectivity. These differences offered the researchers a structural basis for ligand selectivity that their screening pipeline was designed to exploit.

The workflow began with the crystal structures of Ov-GST2, co-crystallized with the inhibitor S-hexylglutathione, and Ov-GST1, co-crystallized with glutathione, retrieved from the Protein Data Bank. Each structure was carefully prepared, with protonation states assigned at physiological pH and restrained energy minimization performed using the OPLS3 force field. All 3,500 ConMedNP compounds were then profiled with QikProp against descriptors calibrated to the properties of 95 percent of approved drugs, including solubility, permeability, polar surface area and oral absorption. Docking proceeded through three sequential tiers of increasing stringency, high-throughput virtual screening, standard precision and extra precision, ultimately shortlisting ten hits against Ov-GST2 and eight against Ov-GST1.

A critical validation step lent credibility to the entire exercise. The researchers redocked the co-crystallized native ligands into their respective receptors under identical extra-precision settings, obtaining heavy-atom RMSD values of 1.023 angstroms for S-hexylglutathione and 0.954 angstroms for glutathione, both comfortably below the 2.0-angstrom threshold conventionally accepted as evidence of an accurate docking protocol. The native ligands also reproduced the expected hydrogen bonds with key residues such as Ser63, Gln49, Gln62 and Arg95 in Ov-GST2, and Glu87, Ser88, Trp63 and Tyr32 in Ov-GST1, matching previously reported experimental findings. With the protocol thus anchored, the team applied MMGBSA rescoring, an implicit-solvent estimate of binding free energy more discriminating than the empirical docking score, to rank the shortlisted hits.

Four compounds with the most favorable combined docking, MMGBSA and ADMET profiles advanced to the molecular dynamics stage: AN_UY_186_1 and AN_UY_088 against Ov-GST2, and BMC_00091 and SO_UY_018 against Ov-GST1. The two Ov-GST2 hits are homoisoflavanones, a subclass of flavonoids whose 4H-chromen-4-one core packs against the hydrophobic floor of the enzyme’s H-site while their 7-hydroxyl and methoxy substituents donate hydrogen bonds to the backbone of Leu50, and their C3 benzyl group engages Phe38 through pi-pi stacking. Strikingly, this pharmacophore mirrors the binding mode reported for antibacterial homoisoflavanones isolated from Hyacinthaceae species in 2007, suggesting a recurring chemical logic rather than a computational accident.

The 200-nanosecond simulations, run in Desmond with the OPLS4 force field in physiological salt conditions, revealed clear winners. AN_UY_088 held its position within the Ov-GST2 active site with protein backbone RMSD oscillating between 1.4 and 2.4 angstroms and ligand RMSD between 3 and 5 angstroms, forming persistent hydrogen bonds with Tyr7 and pi-pi stacking with Phe38. On the sigma-class side, SO_UY_018 proved the most stable complex, maintaining hydrophobic contacts with Phe123 and Ile127 and a positively charged interaction with Arg38 across roughly a third of the simulation. A Bayesian activity-spectrum analysis using PASS further corroborated the scaffold-level plausibility of the hits, predicting antibacterial, antiparasitic, anthelmintic and anti-inflammatory probabilities consistent with known pharmacophores.

Perhaps the most intriguing finding is the convergence with the team’s own prior work. In a 2024 study, the same group screened the South African Natural Compounds Database, a chemically and geographically distinct library of about 600 compounds, against Ov-GST2 and again landed on homoisoflavanones. That the same scaffold class is independently selected against the same target from two different African natural-product collections suggests the homoisoflavanone signature is reproducible across libraries rather than an artifact of any one collection’s composition. Meanwhile, the best Ov-GST1 lead, SO_UY_018, is not a homoisoflavanone but a larger, more extended scaffold that exploits the sigma-class enzyme’s distinctive Phe33, Phe123 and Ile127 hydrophobic patch, indicating that scaffold selection is target-dependent rather than library-dependent.

The authors are careful to frame these results as computational predictions, not proven cures. They acknowledge that MMGBSA values overestimate absolute affinities, that virtual screening is prone to false positives, and that even 200 nanoseconds of dynamics may undersample slow protein motions and rare unbinding events. Notably, the natural-product hits bind non-glutathionyl pharmacophores, meaning they are unlikely to be competitively displaced by the high intracellular concentration of glutathione, an advantage over substrate-mimetic peptide inhibitors, and their drug-like ADMET profiles make them plausible oral candidates, unlike the peptide native ligands. What happens next is the decisive test: recombinant enzyme inhibition assays, anthelmintic assays on O. volvulus microfilariae and adult worms, and in vitro ADMET studies will determine whether these digital leads, born from the flora of Central Africa, can graduate into the macrofilaricidal medicines that river blindness elimination efforts so urgently need.

Subject of Research: Computational identification of natural-product inhibitors of Onchocerca volvulus glutathione S-transferases

Article Title: Discovering potent Onchocerca volvulus inhibitors from the ConMedNP library through virtual screening, MMGBSA, and molecular dynamics simulations

Article References: Mbah Bake, M., Tsahnang Fofack, H. M., Petry, S., Tsague Meupe Bahoken, B., Bebga, G., Singh, T., Mbouombouo Ndassa, I., Mohammad-Salim, H., & de Julián-Ortiz, J. V. (2026). Discovering potent Onchocerca volvulus inhibitors from the ConMedNP library through virtual screening, MMGBSA, and molecular dynamics simulations. Discover Chemistry, 3(1), Article 465. https://doi.org/10.1007/s44371-026-00910-3

Image Credits: AI Generated

DOI: 10.1007/s44371-026-00910-3

Keywords: Onchocerca volvulus, river blindness, ConMedNP library, virtual screening, MMGBSA, molecular dynamics, glutathione S-transferases, homoisoflavanones, natural products, drug discovery, neglected tropical diseases, ADMET