Comparative in silico analyses of Cannabis sativa, Prunella vulgaris and Withania somnifera compounds elucidating the medicinal properties against rheumatoid arthritis.

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Journal of molecular graphics & modelling, ISSN: 1873-4243, Vol: 74, Page: 296-304

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Zaka, Mehreen; Sehgal, Sheikh Arslan; Shafique, Shagufta; Abbasi, Bilal Haider
Elsevier BV
Chemistry; Computer Science; Materials Science
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article description
From last decade, there has been progressive improvement in computational drug designing. Several diseases are being cured from different plant extracts and products. Rheumatoid Arthritis (RA) is the most shared disease among auto-inflammatory diseases. Tumour necrosis factor (TNF)-α is associated with RA pathway and has adverse effects. Extensive literature review showed that plant species under study (Cannabis sativa, Prunella vulgaris and Withania somnifera) possess anti-inflammatory, anti-arthritic and anti-rheumatic properties. 13 anti-inflammatory compounds were characterised and filtered out from medicinal plant species and analysed for RA by targeting TNF-α through in silico analyses. By using ligand based pharmacophore generation approach and virtual screening against natural products libraries we retrieved twenty unique molecules that displayed utmost binding affinity, least binding energies and effective drug properties. The docking analyses revealed that Ala-22, Glu-23, Ser-65, Gln-67, Tyr-141, Leu-142, Asp-143, Phe-144 and Ala-145 were critical interacting residues for receptor-ligand interactions. It is proposed that the RA patients should use reported compounds for the prescription of RA by targeting TNF-α. This report is opening new dimensions for designing innovative therapeutic targets to cure RA.