The study, published in Discover Chemistry, screened the Pan-African Natural Products Library, known as p-ANAPL, a curated collection of compounds derived from African medicinal plants. Rather than relying on docking scores alone, the researchers built a multi-stage pipeline that begins with ADMET filtering, which predicts how a molecule is absorbed, distributed, metabolized, excreted, and whether it poses toxicity risks. This approach acknowledges a hard truth in drug discovery: a compound that binds tightly but fails Lipinski’s Rule of Five, or blocks the hERG potassium channel critical for heart rhythm, is a dead end no matter how impressive its binding energy appears on paper.

The target protein was murine COX-2, taken from the Protein Data Bank under identifier 4PH9 at a remarkably high resolution of 1.81 angstroms. Crucially, this crystal structure contained ibuprofen bound in the active site, giving the team a known answer to validate their docking protocol. When they re-docked ibuprofen and compared the result to the original crystallographic pose, the heavy-atom root-mean-square deviation came out at just 0.85 angstroms, well below the commonly accepted 2.0 angstrom threshold. This gave the researchers confidence that their computational setup was faithfully reproducing the physics of drug binding in the COX-2 channel.

With the protocol validated, all 520 compounds in the p-ANAPL library were screened using a hierarchical approach: high-throughput virtual screening first, then standard precision docking to refine the top 33 candidates, and finally extra precision docking on the best five. Two molecules rose above the rest: 152CSB2 and Thix6g, both of which outscored ibuprofen in the extra precision ranking. The researchers emphasized that selection was not based on docking scores alone but on a combination of binding scores, interaction patterns with key residues, and ADMET acceptability, a more holistic criterion that reduces the risk of false positives.

Both lead compounds anchored themselves in the NSAID-binding channel through contacts with Arg-120 and Tyr-355, the catalytic gatekeepers that normally admit arachidonic acid. 152CSB2 formed three hydrogen bonds, including donor interactions with Arg-121 and Tyr-356 plus an acceptor bond with Met-523, along with a salt bridge to the guanidinium group of Arg-120, mirroring the classic binding mode of competitive NSAIDs. Thix6g, meanwhile, relied on two hydrogen bonds and a battery of aromatic interactions, including stacked pi-pi contacts with Tyr-356 and pi-amide contacts with Gly-527, suggesting a different but equally stabilizing strategy for occupying the pocket.

To confirm these poses were not fleeting artifacts of a static snapshot, the team ran 200-nanosecond molecular dynamics simulations using the Desmond package. The protein backbone of both complexes remained stable, with RMSD values hovering between 2.8 and 3.2 angstroms for 152CSB2 and around 3.0 to 3.2 angstroms for Thix6g. The ligand RMSD for Thix6g stayed remarkably close to its initial binding mode throughout the simulation, while 152CSB2 showed an initial adjustment period before settling into a stable configuration. Hydrophobic contacts between 152CSB2 and residues Tyr-356, Val-524, and Tyr-386 persisted for 32, 62, and 88 percent of the simulation time respectively, providing a dynamic picture of sustained binding that no single docking frame could capture.

Binding free energy calculations using the MM-GBSA method, performed on 400 equally spaced frames from the final 100 nanoseconds of trajectory, delivered the study’s most striking result. 152CSB2 posted a binding free energy of minus 32.12 kilocalories per mole, while Thix6g managed only minus 0.29 kilocalories per mole, a dramatic gulf that reflects fundamental differences in how the two molecules fit their target. The van der Waals contribution for 152CSB2 reached minus 16.97 kilocalories per mole against just minus 6.30 for Thix6g, pointing to superior steric complementarity. Thix6g was further penalized by high ligand strain energy and unfavorable desolvation costs, meaning the molecule had to contort itself into a less natural shape to squeeze into the active site.

The researchers then deployed density functional theory calculations at the B3LYP/6-311++G(d,p) level to probe the electronic personalities of the lead compounds. Both 152CSB2 and Thix6g showed lower ionization potentials than ibuprofen, meaning they donate electron density more readily, a property that could enhance their interactions with electron-poor residues in the COX-2 pocket. 152CSB2 also exhibited the smallest HOMO-LUMO gap at 0.28 atomic units, the highest softness, and the largest electrophilicity index, collectively marking it as the most electronically reactive of the three molecules. The frontier molecular orbital distribution for 152CSB2 spread across an extended aromatic system with a conjugated ethylenic bond, whereas Thix6g’s orbitals localized around oxygen-bearing phenyl groups, hinting at distinct mechanisms of electronic engagement with the protein.

Despite the promise, the authors are careful to frame these findings as computational hypotheses rather than proven drug candidates. MM-GBSA values are semi-quantitative ranking estimates, not experimentally measured affinities, and predicted ADMET profiles must be validated in the laboratory before any lead optimization can begin. The team also notes that the hierarchical HTVS-to-SP-to-XP screening workflow, though perhaps computationally unnecessary for a library of only 520 compounds, was retained as a scalable demonstration that can be applied to much larger African natural product collections in the future.

Nevertheless, the study represents a meaningful step toward harnessing Africa’s largely untapped botanical diversity for modern drug discovery. By combining rigorous structural biology, molecular dynamics, quantum chemistry, and pharmacokinetic filtering into a single pipeline, the researchers have shown that natural compounds from the continent’s medicinal plants can compete with, and in some respects outperform, blockbuster synthetic drugs like ibuprofen at the molecular level. 152CSB2, with its combination of stable binding, favorable ADMET characteristics, and distinctive electronic profile, now stands as the most compelling candidate for the in vitro and in vivo studies that will determine whether a digital lead can become a real medicine for inflammatory disease.

Subject of Research: In silico screening of the Pan-African Natural Products Library for selective COX-2 inhibitors

Article Title: In silico evaluation of p-ANAPL library against inhibiting the cognate isoform cyclooxygenase Cox-2

Article References: Gawoua Teumen, D., Amana, B. A., Eyia Andiga, L. G., Moto Ongagna, J., Amoa, P. P., Govender, K. K., & Bikele Mama, D. (2026). In silico evaluation of p-ANAPL library against inhibiting the cognate isoform cyclooxygenase Cox-2. Discover Chemistry, 3(1), Article 478. https://doi.org/10.1007/s44371-026-00924-x

Image Credits: AI Generated

DOI: 10.1007/s44371-026-00924-x

Keywords: COX-2, p-ANAPL, molecular docking, ADMET, molecular dynamics, MM-GBSA, DFT, natural products, virtual screening, anti-inflammatory, drug discovery, inflammation