AN OVERVIEW OF ARTIFICIAL INTELLIGENCE AS TOOL FOR DRUG DESIGN TO TREAT INFECTIOUS DISEASE

Main Article Content

Astalakshmi N
Keerthi Vasan P
Harini C
Parameshwari B
Sridhar R
Premkumar N
Karthik R
Kaviya K
Sakthi P
Surendra Kumar M

Keywords

Artificial intelligence, Sedate plan, Computer supported medicate plan, Machine learning

Abstract

Drug discovery aims to find new compounds with specific drugs to treat diseases. Over the past few decades, Artificial Perception (AI) contributes to the discovery of computer security. The widespread use of mechanical literature (particularly within education) continues to drive this expansion across many fields and advances in computer hardware and software. This article includes discussion of AI in drug development, Application of artificial intelligence, various drug detection methods discovery, necessity of drug discovery, (AIDD) tools and resources

Abstract 286 | Pdf Downloads 124

References

1. Aloy, P, and RB Russell. 2006. 'Structural systems biology: modelling protein interactions', Nat Rev Mol Cell Biol 188-97.
2. Alqahtani, A. 2022. 'Application of artificial intelligence in discovery and development of anticancer and antidiabetic therapeutic agents', Evidence-Based Complementary and Alternative Medicine.
3. ASHA, S, and M VIDYAVATHI. 2010. ' Role of human liver microsomes in in vitro metabolism of drugs-a review', ApplBiochemBiotechno: 1699-722.
4. B.V. Chaudhari, S. P. Jaiswal and N. A. Porwar. 'Role of artificial intelligence in drug discovery and development: a review', World journal of pharmacy and pharmaceutical sciences, 12: 422-32.
5. Crimi, Alessandro. 2021. https://medium.com/geekculture/5-cool-ai-powered-drug-discovery-tools-1d7e976ffc2a.
6. David, Alessia, Suhail Islam, EvgenyTankhilevich, and Michael J.E. Sternberg. 2022. 'The AlphaFold Database of Protein Structures', A Biologist’s guide.science direct.
7. Dong, Michael W. 2022. 'Small-Molecule Drug Discovery: Processes, Perspectives, Candidate Selection, and Career Opportunities for Analytical Chemists', LCGC North America: 344-50.
8. Duran-Frigola, M, and P Aloy. 2013. 'Analysis of chemical and biological features yields mechanistic insights into drug side effects', ChemBiol: 594-603.
9. Elbadawi, M, S Gaisford, and AW Basit. 2021 'Advanced machine-learning techniques in drug discovery', Drug Discovery Today, 26: 769-77.
10. Ferreira, LG, and G Oliva. 2018. 'AD Andricopulo - Anais da from medicinal chemistry to human health: current approaches to drug discovery for cancer and neglected tropicaldiseases', academia Brasileira.
11. Gupta, S.K. 2011. Drug Discovery and clinical research.
12. jayasutha, j. "TOXICOLOGICAL APPROACHES TO DRUG DISCOVERY." In. Srm college of pharmacy, srm university.
13. Jumper, J, R Evans, A Pritzel, and et al. 2021. 'Highly accurate protein structure prediction with AlphaFold', nature joural: 583-89.
14. Kim, H, E Kim, I Lee, B Bae, M Park, and H Nam. 2020. 'Artificial intelligence in drug discovery: a comprehensive review of data-driven and machine learning approaches ', Biotechnology and Bioprocess Engineering: 895-930.
15. M, Xiang, Cao Y, Fan W, Chen L, and Mo Y. 2012. 'Computer-aided drug design: lead discovery and optimization', Combinatorial chemistry & high throughput screening., 15: 28-37.
16. MaciejWójcikowski, Piotr Zielenkiewicz, and PawelSiedlecki. 2015. 'Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field', Journal Cheminform., 7.
17. Mak, KK, and MR Pichika. 2019. 'Artificial intelligence in drug development: present status and future prospects', Drug discovery today., 24: 773-80.
18. Mandal, S, MN Moudgil, and SK Mandal. 2009. 'Rational drug design', Eur J Pharmacol 90-100.
19. Padole, SS, AJ Asnani, and DR Chaple. 2022. 'A review of approaches in computer-aided drug design in drug discovery ', GSC Biological and pharmaceutical.
20. parkhe, Ganesh, and TruptiThange. 2022. 'A review: artificial intelligence in drug discovery and development', International Journal of Research Publication and Reviews, 3: 501-10.
21. Paul, D, G Sanap, S Shenoy, D Kalyane, K Kalia, and RK Tekade. 2021. 'Artificial intelligence in drug discovery and development', Drug Discovery Today, 26: 80.
22. PoteSonaliArun, SonaliPote, Poonam kasar, AnkitaShinde, AkshayKoshti, and ShubhamDalvi. 2023. ' A Review on drug design', JETIR, 10.
23. Ramesh, N., C. Kambhampati, J. R. T. Monson, and P. J. Drew. 2004. 'Artificial intelligence in medicine', Ann R CollSurg Engl, 86: 334-38.
24. RickTurner, J. 2010. 'new drug development', Springer, Chapter first online: 1-10.
25. Rose, Peter W., and et.al. 2017. 'The RCSB protein data bank: integrative view of protein, gene and 3D structural information', Nucleic Acids Research, 45: D271-D81.
26. Sahoo, A, and GM Dar. 2021. 'A comprehensive review on the application of artificial intelligence in drug discovery', The Applied Biology & Chemistry Journal 2: 34-48.
27. SatavisaPati. 2021. https://analyticsindiamag.com/top-6-ai-powered-drug-discovery-tools-in-2021/.
28. Schneider, G, and U Fechner. 2005. 'Computer-based de novo design of drug-like molecules', Nat Rev Drug Discov 649-63.
29. Selassie, C, and RP Verma. 2017. 'History ofquantitative structure– activity relationships.In: Abraham DJ editor', Burger’s Medicinal CheFDA. Centre for Drug Evaluation and Research – Drug Safety Priorities.
30. Senthil, Subash, T Malathi, and M SurendraKumar. 2023. 'Novel approaches in drug design', journal of developing drugs, 12: 1-4.
31. Staszak, M, K Staszak, K Wieszczycka, A Bajek, K Roszkowski, and B Tylkowski. 2022. 'Machine learning in drug design: Use of artificial intelligence to explore the chemical structure–biological activity relationship.', Wiley Interdisciplinary Reviews: Computational Molecular Science, 12: e1568.
32. Tripathi, N, MK Goshisht, SK Sahu, and C Arora. 2021. 'Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review', Molecular Diversity., 25: 1643-64.
33. Wang, L, J Ding, L Pan, D Cao, H Jiang, and X Ding. 2019. 'Artificial intelligence facilitates drug design in the big data era', Chemometrics and Intelligent Laboratory Systems., 194: 38-50.
34. Wójcikowski, M, P Zielenkiewic, and P Siedlecki. 2015. 'Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field', J Cheminform.
35. Zhong, F, J Xing, X Li, X Liu, Z Fu, Z Xiong, D Lu, X Wu, J Zhao, X Tan, and F Li. 2018. 'Artificial intelligence in drug design', Science China Life Sciences, 61: 191-204.