Nature is the best source of anti-inflammatory drugs: indexing natural products for their anti-inflammatory bioactivity

Aswad, Miran
Rayan, Mahmoud
Abu-Lafi, Saleh
Falah, Mizied
Raiyn, Jamal
Abdallah, Ziyad
Rayan, Anwar
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Springer International Publishing AG
Objectives The aim was to index natural products for less expensive preventive or curative anti-inflammatory therapeutic drugs. Materials A set of 441 anti-inflammatory drugs representing the active domain and 2892 natural products representing the inactive domain was used to construct a predictive model for bioactivity-indexing purposes. Method The model for indexing the natural products for potential anti-inflammatory activity was constructed using the iterative stochastic elimination algorithm (ISE). ISE is capable of differentiating between active and inactive antiinflammatory molecules. Results By applying the prediction model to a mix set of (active/inactive) substances, we managed to capture 38% of the anti-inflammatory drugs in the top 1% of the screened set of chemicals, yielding enrichment factor of 38. Ten natural products that scored highly as potential antiinflammatory drug candidates are disclosed. Searching the PubMed revealed that only three molecules (Moupinamide, Capsaicin, and Hypaphorine) out of the ten were tested and reported as anti-inflammatory. The other seven phytochemicals await evaluation for their anti-inflammatory activity in wet lab. Conclusion The proposed anti-inflammatory model can be utilized for the virtual screening of large chemical databases and for indexing natural products for potential antiinflammatory activity.
Anti-inflammatory , Chemoinformatics , Ligand-based modeling , Bioactivity index
Aswad, M., Rayan, M., Abu-Lafi, S. et al. Inflamm. Res. (2018) 67: 67.