MOLECULAR DOCKING STRATEGY FOR MULTI-TARGET INHIBITOR DISCOVERY OF SELECTED PLANT CONSTITUENTS IN BAUHINIA ACUMINATA

Year 2022, Volume: 46 Issue: 1, 144 - 159, 29.01.2022

Neelima Kudumula

https://doi.org/10.33483/jfpau.987023

Abstract

Objective: Traditional medicine is often considered to be a kind of complementary or alternative medicine (CAM) nowadays. Therefore, documenting and identifying the herbs that are effective in treating various diseases is vital for future disease control programs. This study aims to perform a molecular docking analysis of the thirteen plant components in Bauhinia acuminata against the target proteins in lung cancer (PDB IDs: 2ITY), breast cancer (1A52), diabetes (3L4U), obesity (IT02), inflammation (5COX) and corona viral infections (6VYO).

Material and Method: All the plant components used for the present study were retrieved from the plant Bauhinia acuminata and were evaluated for their biological activity results using molinspiration. Further in-silico docking analysis was performed using AutoDock Vina software and the binding interactions were visualized using Discovery studio program.

Result and Discussion: The docking scores and analysis of the interactions of the plant components with targets suggest that all the selected plant components showed excellent binding to the chosen targets when compared to that of the standard drugs. As a result of the docking process on 6 different targets, the selected plant components like Quercetin, Beta-sitosterol, and Rheagenine were observed to show good binding energy values against all the 5 targets except 6VYO as shown in (Table 9). These results can further pave the way for getting better insights in identifying and designing potential lead candidates. 

Keywords

AutoDock Vina, Bauhinia acuminata, discovery studio, molecular docking, plant components

Thanks

The authors are thankful to the Principal and Management of Sarojini Naidu Vanita Pharmacy Maha Vidyalaya, Osmania University, Hyderabad, India, for providing research facilities.

BAUHINIA ACUMINATA'DAKİ SEÇİLMİŞ FİTO BİLEŞENLERİN ÇOK HEDEFLİ İNHİBİTÖR KEŞFİ İÇİN MOLEKÜLER YERLEŞTİRME STRATEJİSİ

Abstract

Amaç: Günümüzde geleneksel tıp genellikle bir tür tamamlayıcı veya alternatif tıp (CAM) olarak kabul edilmektedir. Bu nedenle, çeşitli hastalıkların tedavisinde etkili olan bitkilerin belgelenmesi ve tanımlanması gelecekteki hastalık kontrol programları için hayati öneme sahiptir. Bu çalışma Bauhiniaacuminata'daki on üç bitki bileşeninin akciğer kanseri (PDB IDs: 2ITY), meme kanseri (1A52), diyabet (3L4U), obezite (IT02), inflamasyon (5COX) ve korona viral enfeksiyonlarındaki (6VYO) hedef proteinlere karşı moleküler kenetlenme analizini gerçekleştirmeyi amaçlamaktadır.

Gereç ve Yöntem: Bu çalışmada kullanılan tüm bitki bileşenleri Bauhiniaacuminata bitkisinden alınmış ve molinspirasyon kullanılarak biyolojik aktivite sonuçları açısından değerlendirilmiştir. Ayrıca AutoDockVına yazılımı kullanılarak siliko içi yerleştirme analizi yapıldı ve bağlanma etkileşimleri Discoverystudio programı kullanılarak görselleştirildi.

Sonuç ve Tartışma: Yerleştirme puanları ve bitki bileşenlerinin hedeflerle etkileşimlerinin analizi, seçilen tüm bitki bileşenlerinin standart ilaçlarınkine kıyasla seçilen hedeflere mükemmel bağlanma gösterdiğini göstermektedir. 6 Farklı hedefe kenetlenme işlemi sonucunda, Quercetin, Beta-sitosterol ve Rheagenin gibi seçilen bitki bileşenlerinin, gösterildiği gibi 6VYO hariç tüm 5 hedefe karşı iyi bağlanma enerjisi değerleri gösterdiği gözlenmiştir (Tablo 9). Bu sonuçlar potansiyel potansiyel adayları belirleme ve tasarlama konusunda daha iyi kavrayışlar elde etmenin önünü daha da açabilir.

Keywords

AutoDock Vina, Bauhinia acuminata, bitki bileşenleri, discovery studio, moleküler yerleştirme

References

• REFERENCES 1. Qi, Z. (2013).WHO traditional medicine strategy. 2014-2023. Geneva: World Health Organization. [CrossRef].
• 2. Chintamunnee, V., Mahomoodally, MF. (2012). Herbal medicine is commonly used against non-communicable diseases in the tropical island of Mauritius. Journal of Herbal Medicine,2(4),113-125.[CrossRef]
• 3. Gurib-Fakim, A. (2006). Medicinal plants: traditions of yesterday and drugs of tomorrow. Molecular Aspects of Medicine,27(1), 1-93. [CrossRef]
• 4. Lin, LL., Shan, JJ., Xie, T. (2016). Application of traditional Chinese medical herbs in prevention and treatment of the respiratory syncytial virus. Evidence Based Complement.Alternaive Medicine,1-13.[CrossRef]
• 5. Liang-Tzung, Lin., Wen-Chan, Hsu., Chun-Ching, Lin. (2014). Antiviral natural products and herbal medicines. Journal of Traditional and Complement Medicine, 4(1), 24-35. [CrossRef]
• 6. Sebastian, D. (2018). Pharmacognostic standardization and bioassay-guided fractionation of in Bauhinia acuminata relation to anti-lung cancer activity. Shodhganga@Inflibnet. University of Madras. [CrossRef]
• 7. Divya, Sebastian., Albin T, Fleming. (2017). Synthesis of Silver Nanoparticles from Bauhinia acuminata Aqueous Leaf Extract and Molecular Docking Analysis of Various Cancer Receptors.International Journal of Science and Research, 6(3), 50-55. [CrossRef]
• 8. Manobendro Nath, Ray*., Tarannum, Naz., Alam, Khan., Md. Hanif, Ali. (2017). Antidiabetic Potential of Methanolic Extract of Leave and Bark of Bangladeshi Medicinal Plant Bauhinia acuminata L on Mice. Journal of Diabetes and Metabolism, 8(9) [CrossRef]
• 9. Anusha,Govindula*.,Musku, Sadhana Reddy., Medi,Manjula., Musku, Soumya Reddy., Nusrath, Perumalla, Kalyan. (2019). Invivo Antihyperlipidemic Activity and Preliminary Phytochemical Screening of Bauhinia Acuminata, International Journal of Pharma Sciences and Scientific Research, 5(4), 62-68.[CrossRef]
• 10. Sanjay, Dutta.,Sanowar, Hossain.,Ekramul, Islam.,Uzzal, Haque., Shahnaj Parvin*. (2020). Assessment of Antioxidant and Anti-inflammatory Activities of Stem Bark of Bauhinia acuminata L. Biomedical journal of Scientific and Technical research,24(5), 18519-18527. [CrossRef]
• 11. Pulakuntla, Swetha Reddy., Kiran Bharat, Lokhande.,Shuchi, Nagar., Vaddi, Damodara Reddy., P, Sushma Murthy., K, Venkateswara Swamy.(2018). Molecular Modeling, Docking, Dynamics and Simulation of Gefitinib and its Derivatives with EGFR in Non-small Cell Lung Cancer. CurrentComputerAided Drug Design,14(3), 246-252. [CrossRef]
• 12. Angeles, C.,Tecalco-Cruz 1., Josué O Ramírez-Jarquín 2., Eduardo Cruz-Ramos1. (2019). Estrogen Receptor Alpha and its Ubiquitination in Breast Cancer Cells.Current Drug Targets,20(6), 690-704.[CrossRef]
• 13. Amina, M.,Dirir., Marianne, Daou., Ahmed F, Yousef., Lina F, Yousef. (2021). A review of alpha-glucosidase inhibitors from plants as potential candidates for the treatment of type-2 diabetis. Phytochemistry Reviews. [CrossRef]
• 14. Winfried, März1., Wolfgang, Köenig. (2003). HMG CoA Reductase inhibition: anti-inflammatory effects beyond lipid lowering? Journal of Cardiovascular Risk, 10(3), 169-79.[CrossRef]
• 15. Ravi, G.,Kurumbail., Anna M, Stevens., James K,Gierse., Joseph J, McDonald, Roderick A. Stegeman., Jina Y. Pak., Daniel ildehaus., Julie M. iyashiro, Thomas D., Penning., Karen, Seibert., Peter C, Isakson & William C. Stallings. (1996). Structural basis for selective inhibition of cyclooxygenase-2 by anti-inflammatory agents.Nature, 384, 644-648. [CrossRef]
• 16. Selamiercan∗., ErcanÇınar. (2021). A molecular docking study of potential inhibitors and repurposed drugs against SARS-CoV-2 main protease enzyme. Journal of the Indian Chemical Society,98(3), 100041.[CrossRef]
• 17. Protein Data Bank (PDB) https://www.rcsb.org/[CrossRef]
• 18. AutoDockVina. v.1.2.0,thefreeGUIforAutoDock Vina. [http://autodock.scripps.edu/]. [CrossRef]
• 19. Pharmit: interactive exploration of chemical space. https://pharmit.csb.pitt.edu.[CrossRef]
• 20. MuniSireesha, S., Dipankar, Bhowmik., Soujanya, D., Brijıtha, G and Jyothi, V. (2021) Computatıonal validatıon of tacrıne analogs as antialzheimer’s agents against acetylcholinesterases. International Journal of Biology, Pharmacy and Allied Sciences, 10(10), 243-254.[CrossRef]
• 21. Barnum, D., Greene, J., Smellie, A. and Sprague, P. (1996). Identification of common functional configurations among molecules. Journal of Chemical Information and Computer Sciences 36, 563–571. [CrossRef]
• 22. Neelima, Kudumula., Noota, Divya., Nagamalla, Sravika., Saketha, Priya., Pachava, Anusha., Mudavath, Sai Jyotsna. (2021).Molecular Properties, Bioactivity Scores, and Toxicity Predictions of the Phytoconstituents Present in Bauhinia Acuminata. International Journal of Scientific Research and Management, 09(07), 408-414. [CrossRef]